diff --git a/configs/cascade_rcnn/README.md b/configs/cascade_rcnn/README.md index cd8730264e89515a0fe6a1f7f3933060b0cd5953..b84fa895af027b467aa6b6060ab8afe89634a18a 100644 --- a/configs/cascade_rcnn/README.md +++ b/configs/cascade_rcnn/README.md @@ -4,12 +4,12 @@ | 骨架网络 | 网络类型 | 每张GPU图片个数 | 学习率策略 |推理时间(fps) | Box AP | Mask AP | 下载 | 配置文件 | | :------------------- | :------------- | :-----: | :-----: | :------------: | :-----: | :-----: | :-----------------------------------------------------: | :-----: | -| ResNet50-FPN | Cascade Faster | 1 | 1x | ---- | 41.1 | - | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_rcnn_r50_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/cascade_rcnn/cascade_rcnn_r50_fpn_1x_coco.yml) | -| ResNet50-FPN | Cascade Mask | 1 | 1x | ---- | 41.8 | 36.3 | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_mask_rcnn_r50_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/cascade_rcnn/cascade_mask_rcnn_r50_fpn_1x_coco.yml) | -| ResNet50-vd-SSLDv2-FPN | Cascade Faster | 1 | 1x | ---- | 44.4 | - | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/cascade_rcnn/cascade_rcnn_r50_vd_fpn_ssld_1x_coco.yml) | -| ResNet50-vd-SSLDv2-FPN | Cascade Faster | 1 | 2x | ---- | 45.0 | - | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/cascade_rcnn/cascade_rcnn_r50_vd_fpn_ssld_2x_coco.yml) | -| ResNet50-vd-SSLDv2-FPN | Cascade Mask | 1 | 1x | ---- | 44.9 | 39.1 | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_mask_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/cascade_rcnn/cascade_mask_rcnn_r50_vd_fpn_ssld_1x_coco.yml) | -| ResNet50-vd-SSLDv2-FPN | Cascade Mask | 1 | 2x | ---- | 45.7 | 39.7 | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_mask_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/cascade_rcnn/cascade_mask_rcnn_r50_vd_fpn_ssld_2x_coco.yml) | +| ResNet50-FPN | Cascade Faster | 1 | 1x | ---- | 41.1 | - | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_rcnn_r50_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/cascade_rcnn/cascade_rcnn_r50_fpn_1x_coco.yml) | +| ResNet50-FPN | Cascade Mask | 1 | 1x | ---- | 41.8 | 36.3 | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_mask_rcnn_r50_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/cascade_rcnn/cascade_mask_rcnn_r50_fpn_1x_coco.yml) | +| ResNet50-vd-SSLDv2-FPN | Cascade Faster | 1 | 1x | ---- | 44.4 | - | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/cascade_rcnn/cascade_rcnn_r50_vd_fpn_ssld_1x_coco.yml) | +| ResNet50-vd-SSLDv2-FPN | Cascade Faster | 1 | 2x | ---- | 45.0 | - | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/cascade_rcnn/cascade_rcnn_r50_vd_fpn_ssld_2x_coco.yml) | +| ResNet50-vd-SSLDv2-FPN | Cascade Mask | 1 | 1x | ---- | 44.9 | 39.1 | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_mask_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/cascade_rcnn/cascade_mask_rcnn_r50_vd_fpn_ssld_1x_coco.yml) | +| ResNet50-vd-SSLDv2-FPN | Cascade Mask | 1 | 2x | ---- | 45.7 | 39.7 | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_mask_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/cascade_rcnn/cascade_mask_rcnn_r50_vd_fpn_ssld_2x_coco.yml) | ## Citations diff --git a/configs/dcn/README.md b/configs/dcn/README.md index 3248a387c018c71b48d22c3aa20cd972db2defbb..8d59858f0389bff1fc25ca5131f1f523235a9395 100644 --- a/configs/dcn/README.md +++ b/configs/dcn/README.md @@ -2,17 +2,17 @@ | 骨架网络 | 网络类型 | 卷积 | 每张GPU图片个数 | 学习率策略 |推理时间(fps)| Box AP | Mask AP | 下载 | 配置文件 | | :------------------- | :------------- | :-----: |:--------: | :-----: | :-----------: |:----: | :-----: | :----------------------------------------------------------: | :----: | -| ResNet50-FPN | Faster | c3-c5 | 1 | 1x | - | 42.1 | - | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_dcn_r50_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/dcn/faster_rcnn_dcn_r50_fpn_1x_coco.yml) | -| ResNet50-vd-FPN | Faster | c3-c5 | 1 | 1x | - | 42.7 | - | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_dcn_r50_vd_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/dcn/faster_rcnn_dcn_r50_vd_fpn_1x_coco.yml) | -| ResNet50-vd-FPN | Faster | c3-c5 | 1 | 2x | - | 43.7 | - | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_dcn_r50_vd_fpn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/dcn/faster_rcnn_dcn_r50_vd_fpn_2x_coco.yml) | -| ResNet101-vd-FPN | Faster | c3-c5 | 1 | 1x | - | 45.1 | - | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_dcn_r101_vd_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/dcn/faster_rcnn_dcn_r101_vd_fpn_1x_coco.yml) | -| ResNeXt101-vd-FPN | Faster | c3-c5 | 1 | 1x | - | 46.5 | - | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_dcn_x101_vd_64x4d_fpn_1x_coco.pdparams) |[配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/dcn/faster_rcnn_dcn_x101_vd_64x4d_fpn_1x_coco.yml) | -| ResNet50-FPN | Mask | c3-c5 | 1 | 1x | - | 42.7 | 38.4 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_dcn_r50_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/dcn/mask_rcnn_dcn_r50_fpn_1x_coco.yml) | -| ResNet50-vd-FPN | Mask | c3-c5 | 1 | 2x | - | 44.6 | 39.8 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_dcn_r50_vd_fpn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/dcn/mask_rcnn_dcn_r50_vd_fpn_2x_coco.yml) | -| ResNet101-vd-FPN | Mask | c3-c5 | 1 | 1x | - | 45.6 | 40.6 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_dcn_r101_vd_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/dcn/mask_rcnn_dcn_r101_vd_fpn_1x_coco.yml) | -| ResNeXt101-vd-FPN | Mask | c3-c5 | 1 | 1x | - | 47.3 | 42.0 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_dcn_x101_vd_64x4d_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/dcn/mask_rcnn_dcn_x101_vd_64x4d_fpn_1x_coco.yml) | -| ResNet50-FPN | Cascade Faster | c3-c5 | 1 | 1x | - | 42.1 | - | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_rcnn_dcn_r50_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/dcn/cascade_rcnn_dcn_r50_fpn_1x_coco.yml) | -| ResNeXt101-vd-FPN | Cascade Faster | c3-c5 | 1 | 1x | - | 48.8 | - | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_rcnn_dcn_x101_vd_64x4d_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/dcn/cascade_rcnn_dcn_x101_vd_64x4d_fpn_1x_coco.yml) | +| ResNet50-FPN | Faster | c3-c5 | 1 | 1x | - | 42.1 | - | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_dcn_r50_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/dcn/faster_rcnn_dcn_r50_fpn_1x_coco.yml) | +| ResNet50-vd-FPN | Faster | c3-c5 | 1 | 1x | - | 42.7 | - | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_dcn_r50_vd_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/dcn/faster_rcnn_dcn_r50_vd_fpn_1x_coco.yml) | +| ResNet50-vd-FPN | Faster | c3-c5 | 1 | 2x | - | 43.7 | - | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_dcn_r50_vd_fpn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/dcn/faster_rcnn_dcn_r50_vd_fpn_2x_coco.yml) | +| ResNet101-vd-FPN | Faster | c3-c5 | 1 | 1x | - | 45.1 | - | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_dcn_r101_vd_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/dcn/faster_rcnn_dcn_r101_vd_fpn_1x_coco.yml) | +| ResNeXt101-vd-FPN | Faster | c3-c5 | 1 | 1x | - | 46.5 | - | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_dcn_x101_vd_64x4d_fpn_1x_coco.pdparams) |[配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/dcn/faster_rcnn_dcn_x101_vd_64x4d_fpn_1x_coco.yml) | +| ResNet50-FPN | Mask | c3-c5 | 1 | 1x | - | 42.7 | 38.4 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_dcn_r50_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/dcn/mask_rcnn_dcn_r50_fpn_1x_coco.yml) | +| ResNet50-vd-FPN | Mask | c3-c5 | 1 | 2x | - | 44.6 | 39.8 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_dcn_r50_vd_fpn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/dcn/mask_rcnn_dcn_r50_vd_fpn_2x_coco.yml) | +| ResNet101-vd-FPN | Mask | c3-c5 | 1 | 1x | - | 45.6 | 40.6 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_dcn_r101_vd_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/dcn/mask_rcnn_dcn_r101_vd_fpn_1x_coco.yml) | +| ResNeXt101-vd-FPN | Mask | c3-c5 | 1 | 1x | - | 47.3 | 42.0 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_dcn_x101_vd_64x4d_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/dcn/mask_rcnn_dcn_x101_vd_64x4d_fpn_1x_coco.yml) | +| ResNet50-FPN | Cascade Faster | c3-c5 | 1 | 1x | - | 42.1 | - | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_rcnn_dcn_r50_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/dcn/cascade_rcnn_dcn_r50_fpn_1x_coco.yml) | +| ResNeXt101-vd-FPN | Cascade Faster | c3-c5 | 1 | 1x | - | 48.8 | - | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_rcnn_dcn_x101_vd_64x4d_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/dcn/cascade_rcnn_dcn_x101_vd_64x4d_fpn_1x_coco.yml) | **注意事项:** diff --git a/configs/deformable_detr/README.md b/configs/deformable_detr/README.md index ea6840fb5c69b60e6d48708d8b732ebb56e0476a..0531c99d1dcd3e59104340cfa5928b23a32a76c2 100644 --- a/configs/deformable_detr/README.md +++ b/configs/deformable_detr/README.md @@ -10,7 +10,7 @@ Deformable DETR is an object detection model based on DETR. We reproduced the mo | Backbone | Model | Images/GPU | Inf time (fps) | Box AP | Config | Download | |:------:|:--------:|:--------:|:--------------:|:------:|:------:|:--------:| -| R-50 | Deformable DETR | 2 | --- | 44.1 | [config](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/deformable_detr/deformable_detr_r50_1x_coco.yml) | [model](https://paddledet.bj.bcebos.com/models/deformable_detr_r50_1x_coco.pdparams) | +| R-50 | Deformable DETR | 2 | --- | 44.1 | [config](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/configs/deformable_detr/deformable_detr_r50_1x_coco.yml) | [model](https://paddledet.bj.bcebos.com/models/deformable_detr_r50_1x_coco.pdparams) | **Notes:** diff --git a/configs/detr/README.md b/configs/detr/README.md index 2dc370f3aef79149878554dffe782f6d3f045f54..80bcd674a7cbe2aed194d804b8ea0465694e5b22 100644 --- a/configs/detr/README.md +++ b/configs/detr/README.md @@ -10,7 +10,7 @@ DETR is an object detection model based on transformer. We reproduced the model | Backbone | Model | Images/GPU | Inf time (fps) | Box AP | Config | Download | |:------:|:--------:|:--------:|:--------------:|:------:|:------:|:--------:| -| R-50 | DETR | 4 | --- | 42.3 | [config](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/detr/detr_r50_1x_coco.yml) | [model](https://paddledet.bj.bcebos.com/models/detr_r50_1x_coco.pdparams) | +| R-50 | DETR | 4 | --- | 42.3 | [config](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/configs/detr/detr_r50_1x_coco.yml) | [model](https://paddledet.bj.bcebos.com/models/detr_r50_1x_coco.pdparams) | **Notes:** diff --git a/configs/face_detection/README.md b/configs/face_detection/README.md index ce1a03a2f337fd8e297313442c178848d450d887..8b23e78463e9c89bb5f0fe5601d02b558c5dffb3 100644 --- a/configs/face_detection/README.md +++ b/configs/face_detection/README.md @@ -11,8 +11,8 @@ | 网络结构 | 输入尺寸 | 图片个数/GPU | 学习率策略 | Easy/Medium/Hard Set | 预测时延（SD855）| 模型大小(MB) | 下载 | 配置文件 | |:------------:|:--------:|:----:|:-------:|:-------:|:---------:|:----------:|:---------:|:--------:| -| BlazeFace | 640 | 8 | 1000e | 0.885 / 0.855 / 0.731 | - | 0.472 |[下载链接](https://paddledet.bj.bcebos.com/models/blazeface_1000e.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/face_detection/blazeface_1000e.yml) | -| BlazeFace-FPN-SSH | 640 | 8 | 1000e | 0.907 / 0.883 / 0.793 | - | 0.479 |[下载链接](https://paddledet.bj.bcebos.com/models/blazeface_fpn_ssh_1000e.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/face_detection/blazeface_fpn_ssh_1000e.yml) | +| BlazeFace | 640 | 8 | 1000e | 0.885 / 0.855 / 0.731 | - | 0.472 |[下载链接](https://paddledet.bj.bcebos.com/models/blazeface_1000e.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/face_detection/blazeface_1000e.yml) | +| BlazeFace-FPN-SSH | 640 | 8 | 1000e | 0.907 / 0.883 / 0.793 | - | 0.479 |[下载链接](https://paddledet.bj.bcebos.com/models/blazeface_fpn_ssh_1000e.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/face_detection/blazeface_fpn_ssh_1000e.yml) | **注意:** - 我们使用多尺度评估策略得到`Easy/Medium/Hard Set`里的mAP。具体细节请参考[在WIDER-FACE数据集上评估](#在WIDER-FACE数据集上评估)。 diff --git a/configs/face_detection/README_en.md b/configs/face_detection/README_en.md index bf798b3c0b01654239df07338c6dc7174958024f..66b66c3110f7f02af31c9985e37860a6da450dba 100644 --- a/configs/face_detection/README_en.md +++ b/configs/face_detection/README_en.md @@ -11,8 +11,8 @@ | Network structure | size | images/GPUs | Learning rate strategy | Easy/Medium/Hard Set | Prediction delay（SD855）| Model size(MB) | Download | Configuration File | |:------------:|:--------:|:----:|:-------:|:-------:|:---------:|:----------:|:---------:|:--------:| -| BlazeFace | 640 | 8 | 1000e | 0.885 / 0.855 / 0.731 | - | 0.472 |[link](https://paddledet.bj.bcebos.com/models/blazeface_1000e.pdparams) | [Configuration File](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/face_detection/blazeface_1000e.yml) | -| BlazeFace-FPN-SSH | 640 | 8 | 1000e | 0.907 / 0.883 / 0.793 | - | 0.479 |[link](https://paddledet.bj.bcebos.com/models/blazeface_fpn_ssh_1000e.pdparams) | [Configuration File](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/face_detection/blazeface_fpn_ssh_1000e.yml) | +| BlazeFace | 640 | 8 | 1000e | 0.885 / 0.855 / 0.731 | - | 0.472 |[link](https://paddledet.bj.bcebos.com/models/blazeface_1000e.pdparams) | [Configuration File](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/face_detection/blazeface_1000e.yml) | +| BlazeFace-FPN-SSH | 640 | 8 | 1000e | 0.907 / 0.883 / 0.793 | - | 0.479 |[link](https://paddledet.bj.bcebos.com/models/blazeface_fpn_ssh_1000e.pdparams) | [Configuration File](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/face_detection/blazeface_fpn_ssh_1000e.yml) | **Attention:** - We use a multi-scale evaluation strategy to get the mAP in `Easy/Medium/Hard Set`. Please refer to the [evaluation on the WIDER FACE dataset](#Evaluated-on-the-WIDER-FACE-Dataset) for details. diff --git a/configs/fcos/README.md b/configs/fcos/README.md index cdd4334235a30283ac9b8c9902098fdc94364c11..feb1365c7f28efb55ab55352ee07138c52e5271b 100644 --- a/configs/fcos/README.md +++ b/configs/fcos/README.md @@ -12,9 +12,9 @@ FCOS (Fully Convolutional One-Stage Object Detection) is a fast anchor-free obje | Backbone | Model | images/GPU | lr schedule |FPS | Box AP | download | config | | :-------------- | :------------- | :-----: | :-----: | :------------: | :-----: | :-----------------------------------------------------: | :-----: | -| ResNet50-FPN | FCOS | 2 | 1x | ---- | 39.6 | [download](https://paddledet.bj.bcebos.com/models/fcos_r50_fpn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/fcos/fcos_r50_fpn_1x_coco.yml) | -| ResNet50-FPN | FCOS+DCN | 2 | 1x | ---- | 44.3 | [download](https://paddledet.bj.bcebos.com/models/fcos_dcn_r50_fpn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/fcos/fcos_dcn_r50_fpn_1x_coco.yml) | -| ResNet50-FPN | FCOS+multiscale_train | 2 | 2x | ---- | 41.8 | [download](https://paddledet.bj.bcebos.com/models/fcos_r50_fpn_multiscale_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/fcos/fcos_r50_fpn_multiscale_2x_coco.yml) | +| ResNet50-FPN | FCOS | 2 | 1x | ---- | 39.6 | [download](https://paddledet.bj.bcebos.com/models/fcos_r50_fpn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/fcos/fcos_r50_fpn_1x_coco.yml) | +| ResNet50-FPN | FCOS+DCN | 2 | 1x | ---- | 44.3 | [download](https://paddledet.bj.bcebos.com/models/fcos_dcn_r50_fpn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/fcos/fcos_dcn_r50_fpn_1x_coco.yml) | +| ResNet50-FPN | FCOS+multiscale_train | 2 | 2x | ---- | 41.8 | [download](https://paddledet.bj.bcebos.com/models/fcos_r50_fpn_multiscale_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/fcos/fcos_r50_fpn_multiscale_2x_coco.yml) | **Notes:** diff --git a/configs/gfl/README.md b/configs/gfl/README.md index 7a11a09187e67b2182c6e7db56a23e7834e3912d..d5f5960b4e173a6651dead33d4605bdbb69514e5 100644 --- a/configs/gfl/README.md +++ b/configs/gfl/README.md @@ -8,11 +8,11 @@ We reproduce the object detection results in the paper [Generalized Focal Loss: | Backbone | Model | batch-size/GPU | lr schedule |FPS | Box AP | download | config | | :-------------- | :------------- | :-----: | :-----: | :------------: | :-----: | :-----------------------------------------------------: | :-----: | -| ResNet50 | GFL | 2 | 1x | ---- | 41.0 | [model](https://paddledet.bj.bcebos.com/models/gfl_r50_fpn_1x_coco.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_gfl_r50_fpn_1x_coco.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/gfl/gfl_r50_fpn_1x_coco.yml) | -| ResNet101-vd | GFL | 2 | 2x | ---- | 46.8 | [model](https://paddledet.bj.bcebos.com/models/gfl_r101vd_fpn_mstrain_2x_coco.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_gfl_r101vd_fpn_mstrain_2x_coco.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/gfl/gfl_r101vd_fpn_mstrain_2x_coco.yml) | -| ResNet34-vd | GFL | 2 | 1x | ---- | 40.8 | [model](https://paddledet.bj.bcebos.com/models/gfl_r34vd_1x_coco.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_gfl_r34vd_1x_coco.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/gfl/gfl_r34vd_1x_coco.yml) | -| ResNet18-vd | GFL | 2 | 1x | ---- | 36.6 | [model](https://paddledet.bj.bcebos.com/models/gfl_r18vd_1x_coco.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_gfl_r18vd_1x_coco.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/gfl/gfl_r18vd_1x_coco.yml) | -| ResNet50 | GFLv2 | 2 | 1x | ---- | 41.2 | [model](https://paddledet.bj.bcebos.com/models/gflv2_r50_fpn_1x_coco.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_gflv2_r50_fpn_1x_coco.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/gfl/gflv2_r50_fpn_1x_coco.yml) | +| ResNet50 | GFL | 2 | 1x | ---- | 41.0 | [model](https://paddledet.bj.bcebos.com/models/gfl_r50_fpn_1x_coco.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_gfl_r50_fpn_1x_coco.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/gfl/gfl_r50_fpn_1x_coco.yml) | +| ResNet101-vd | GFL | 2 | 2x | ---- | 46.8 | [model](https://paddledet.bj.bcebos.com/models/gfl_r101vd_fpn_mstrain_2x_coco.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_gfl_r101vd_fpn_mstrain_2x_coco.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/gfl/gfl_r101vd_fpn_mstrain_2x_coco.yml) | +| ResNet34-vd | GFL | 2 | 1x | ---- | 40.8 | [model](https://paddledet.bj.bcebos.com/models/gfl_r34vd_1x_coco.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_gfl_r34vd_1x_coco.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/gfl/gfl_r34vd_1x_coco.yml) | +| ResNet18-vd | GFL | 2 | 1x | ---- | 36.6 | [model](https://paddledet.bj.bcebos.com/models/gfl_r18vd_1x_coco.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_gfl_r18vd_1x_coco.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/gfl/gfl_r18vd_1x_coco.yml) | +| ResNet50 | GFLv2 | 2 | 1x | ---- | 41.2 | [model](https://paddledet.bj.bcebos.com/models/gflv2_r50_fpn_1x_coco.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_gflv2_r50_fpn_1x_coco.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/gfl/gflv2_r50_fpn_1x_coco.yml) | **Notes:** diff --git a/configs/gn/README.md b/configs/gn/README.md index ec10831f9e9383d1a16ffc4c3088e283da492ba9..d4cba9c31c1caac5dea0860515c83b289f54dd93 100644 --- a/configs/gn/README.md +++ b/configs/gn/README.md @@ -4,10 +4,10 @@ | 骨架网络 | 网络类型 | 每张GPU图片个数 | 学习率策略 |推理时间(fps)| Box AP | Mask AP | 下载 | 配置文件 | | :------------- | :------------- | :-----------: | :------: | :--------: |:-----: | :-----: | :----: | :----: | -| ResNet50-FPN | Faster | 1 | 2x | - | 41.9 | - | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_fpn_gn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/gn/faster_rcnn_r50_fpn_gn_2x_coco.yml) | -| ResNet50-FPN | Mask | 1 | 2x | - | 42.3 | 38.4 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_fpn_gn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/gn/mask_rcnn_r50_fpn_gn_2x_coco.yml) | -| ResNet50-FPN | Cascade Faster | 1 | 2x | - | 44.6 | - | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_rcnn_r50_fpn_gn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/gn/cascade_rcnn_r50_fpn_gn_2x_coco.yml) | -| ResNet50-FPN | Cacade Mask | 1 | 2x | - | 45.0 | 39.3 | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_mask_rcnn_r50_fpn_gn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/gn/cascade_mask_rcnn_r50_fpn_gn_2x_coco.yml) | +| ResNet50-FPN | Faster | 1 | 2x | - | 41.9 | - | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_fpn_gn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/gn/faster_rcnn_r50_fpn_gn_2x_coco.yml) | +| ResNet50-FPN | Mask | 1 | 2x | - | 42.3 | 38.4 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_fpn_gn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/gn/mask_rcnn_r50_fpn_gn_2x_coco.yml) | +| ResNet50-FPN | Cascade Faster | 1 | 2x | - | 44.6 | - | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_rcnn_r50_fpn_gn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/gn/cascade_rcnn_r50_fpn_gn_2x_coco.yml) | +| ResNet50-FPN | Cacade Mask | 1 | 2x | - | 45.0 | 39.3 | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_mask_rcnn_r50_fpn_gn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/gn/cascade_mask_rcnn_r50_fpn_gn_2x_coco.yml) | **注意：** Faster R-CNN baseline仅使用 `2fc` head，而此处使用[`4conv1fc` head](https://arxiv.org/abs/1803.08494)（4层conv之间使用GN），并且FPN也使用GN，而对于Mask R-CNN是在mask head的4层conv之间也使用GN。 diff --git a/configs/hrnet/README.md b/configs/hrnet/README.md index 1c6fec7bd7c2f498f0a6d38db47b4c091df08820..6b5432fb7d133939cf2b76e9f716f69f4b0b4dc2 100644 --- a/configs/hrnet/README.md +++ b/configs/hrnet/README.md @@ -30,5 +30,5 @@ | Backbone | Type | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download | Configs | | :---------------------- | :------------- | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: | :-----: | -| HRNetV2p_W18 | Faster | 1 | 1x | - | 36.8 | - | [model](https://paddledet.bj.bcebos.com/models/faster_rcnn_hrnetv2p_w18_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/hrnet/faster_rcnn_hrnetv2p_w18_1x_coco.yml) | -| HRNetV2p_W18 | Faster | 1 | 2x | - | 39.0 | - | [model](https://paddledet.bj.bcebos.com/models/faster_rcnn_hrnetv2p_w18_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/hrnet/faster_rcnn_hrnetv2p_w18_2x_coco.yml) | +| HRNetV2p_W18 | Faster | 1 | 1x | - | 36.8 | - | [model](https://paddledet.bj.bcebos.com/models/faster_rcnn_hrnetv2p_w18_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/hrnet/faster_rcnn_hrnetv2p_w18_1x_coco.yml) | +| HRNetV2p_W18 | Faster | 1 | 2x | - | 39.0 | - | [model](https://paddledet.bj.bcebos.com/models/faster_rcnn_hrnetv2p_w18_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/hrnet/faster_rcnn_hrnetv2p_w18_2x_coco.yml) | diff --git a/configs/keypoint/README.md b/configs/keypoint/README.md index 4ca9b07474caca53ca529fc19bd5b239acb742e4..d53fd8d6d0f4d65a0182e3c5a47f26fb08d43bfa 100644 --- a/configs/keypoint/README.md +++ b/configs/keypoint/README.md @@ -186,7 +186,7 @@ python deploy/python/mot_keypoint_unite_infer.py --mot_model_dir=output_inferenc ### 完整部署教程及Demo -​ 我们提供了PaddleInference(服务器端)、PaddleLite(移动端)、第三方部署(MNN、OpenVino)支持。无需依赖训练代码，deploy文件夹下相应文件夹提供独立完整部署代码。 详见 [部署文档](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/deploy/README.md)介绍。 +​ 我们提供了PaddleInference(服务器端)、PaddleLite(移动端)、第三方部署(MNN、OpenVino)支持。无需依赖训练代码，deploy文件夹下相应文件夹提供独立完整部署代码。 详见 [部署文档](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/deploy/README.md)介绍。 ## 自定义数据训练 @@ -242,7 +242,7 @@ python deploy/python/det_keypoint_unite_infer.py \ ## BenchMark -我们给出了不同运行环境下的测试结果，供您在选用模型时参考。详细数据请见[Keypoint Inference Benchmark](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/keypoint/KeypointBenchmark.md)。 +我们给出了不同运行环境下的测试结果，供您在选用模型时参考。详细数据请见[Keypoint Inference Benchmark](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/configs/keypoint/KeypointBenchmark.md)。 ## 引用 diff --git a/configs/keypoint/README_en.md b/configs/keypoint/README_en.md index f6f049824eb5aa185b767f37648bed429196d913..e89f778b98b4b32e6645e8682253b83b313dde29 100644 --- a/configs/keypoint/README_en.md +++ b/configs/keypoint/README_en.md @@ -190,7 +190,7 @@ python deploy/python/mot_keypoint_unite_infer.py --mot_model_dir=output_inferenc ### Complete Deploy Instruction and Demo -​ We provide standalone deploy of PaddleInference(Server-GPU)、PaddleLite(mobile、ARM)、Third-Engine(MNN、OpenVino), which is independent of training codes。For detail, please click [Deploy-docs](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/deploy/README_en.md)。 +​ We provide standalone deploy of PaddleInference(Server-GPU)、PaddleLite(mobile、ARM)、Third-Engine(MNN、OpenVino), which is independent of training codes。For detail, please click [Deploy-docs](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/deploy/README_en.md)。 ## Train with custom data @@ -225,7 +225,7 @@ For more configs, please refer to [KeyPointConfigGuide](../../docs/tutorials/Key ## BenchMark -We provide benchmarks in different runtime environments for your reference when choosing models. See [Keypoint Inference Benchmark](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/keypoint/KeypointBenchmark.md) for details. +We provide benchmarks in different runtime environments for your reference when choosing models. See [Keypoint Inference Benchmark](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/configs/keypoint/KeypointBenchmark.md) for details. ## Reference diff --git a/configs/mask_rcnn/README.md b/configs/mask_rcnn/README.md index 020fe99f78e5d1c84c47929381090c6311694529..cb726502c44b925b3f7dcf6bab1fae4b97df798c 100644 --- a/configs/mask_rcnn/README.md +++ b/configs/mask_rcnn/README.md @@ -4,18 +4,18 @@ | 骨架网络 | 网络类型 | 每张GPU图片个数 | 学习率策略 |推理时间(fps) | Box AP | Mask AP | 下载 | 配置文件 | | :------------------- | :------------| :-----: | :-----: | :------------: | :-----: | :-----: | :-----------------------------------------------------: | :-----: | -| ResNet50 | Mask | 1 | 1x | ---- | 37.4 | 32.8 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_r50_1x_coco.yml) | -| ResNet50 | Mask | 1 | 2x | ---- | 39.7 | 34.5 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_r50_2x_coco.yml) | -| ResNet50-FPN | Mask | 1 | 1x | ---- | 39.2 | 35.6 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_r50_fpn_1x_coco.yml) | -| ResNet50-FPN | Mask | 1 | 2x | ---- | 40.5 | 36.7 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_fpn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_r50_fpn_2x_coco.yml) | -| ResNet50-vd-FPN | Mask | 1 | 1x | ---- | 40.3 | 36.4 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_vd_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_r50_vd_fpn_1x_coco.yml) | -| ResNet50-vd-FPN | Mask | 1 | 2x | ---- | 41.4 | 37.5 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_vd_fpn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_r50_vd_fpn_2x_coco.yml) | -| ResNet101-FPN | Mask | 1 | 1x | ---- | 40.6 | 36.6 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r101_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_r101_fpn_1x_coco.yml) | -| ResNet101-vd-FPN | Mask | 1 | 1x | ---- | 42.4 | 38.1 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r101_vd_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_r101_vd_fpn_1x_coco.yml) | -| ResNeXt101-vd-FPN | Mask | 1 | 1x | ---- | 44.0 | 39.5 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_x101_vd_64x4d_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_x101_vd_64x4d_fpn_1x_coco.yml) | -| ResNeXt101-vd-FPN | Mask | 1 | 2x | ---- | 44.6 | 39.8 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_x101_vd_64x4d_fpn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_x101_vd_64x4d_fpn_2x_coco.yml) | -| ResNet50-vd-SSLDv2-FPN | Mask | 1 | 1x | ---- | 42.0 | 38.2 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_r50_vd_fpn_ssld_1x_coco.yml) | -| ResNet50-vd-SSLDv2-FPN | Mask | 1 | 2x | ---- | 42.7 | 38.9 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_r50_vd_fpn_ssld_2x_coco.yml) | +| ResNet50 | Mask | 1 | 1x | ---- | 37.4 | 32.8 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mask_rcnn/mask_rcnn_r50_1x_coco.yml) | +| ResNet50 | Mask | 1 | 2x | ---- | 39.7 | 34.5 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mask_rcnn/mask_rcnn_r50_2x_coco.yml) | +| ResNet50-FPN | Mask | 1 | 1x | ---- | 39.2 | 35.6 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mask_rcnn/mask_rcnn_r50_fpn_1x_coco.yml) | +| ResNet50-FPN | Mask | 1 | 2x | ---- | 40.5 | 36.7 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_fpn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mask_rcnn/mask_rcnn_r50_fpn_2x_coco.yml) | +| ResNet50-vd-FPN | Mask | 1 | 1x | ---- | 40.3 | 36.4 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_vd_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mask_rcnn/mask_rcnn_r50_vd_fpn_1x_coco.yml) | +| ResNet50-vd-FPN | Mask | 1 | 2x | ---- | 41.4 | 37.5 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_vd_fpn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mask_rcnn/mask_rcnn_r50_vd_fpn_2x_coco.yml) | +| ResNet101-FPN | Mask | 1 | 1x | ---- | 40.6 | 36.6 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r101_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mask_rcnn/mask_rcnn_r101_fpn_1x_coco.yml) | +| ResNet101-vd-FPN | Mask | 1 | 1x | ---- | 42.4 | 38.1 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r101_vd_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mask_rcnn/mask_rcnn_r101_vd_fpn_1x_coco.yml) | +| ResNeXt101-vd-FPN | Mask | 1 | 1x | ---- | 44.0 | 39.5 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_x101_vd_64x4d_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mask_rcnn/mask_rcnn_x101_vd_64x4d_fpn_1x_coco.yml) | +| ResNeXt101-vd-FPN | Mask | 1 | 2x | ---- | 44.6 | 39.8 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_x101_vd_64x4d_fpn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mask_rcnn/mask_rcnn_x101_vd_64x4d_fpn_2x_coco.yml) | +| ResNet50-vd-SSLDv2-FPN | Mask | 1 | 1x | ---- | 42.0 | 38.2 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mask_rcnn/mask_rcnn_r50_vd_fpn_ssld_1x_coco.yml) | +| ResNet50-vd-SSLDv2-FPN | Mask | 1 | 2x | ---- | 42.7 | 38.9 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mask_rcnn/mask_rcnn_r50_vd_fpn_ssld_2x_coco.yml) | ## Citations diff --git a/configs/mot/jde/README.md b/configs/mot/jde/README.md index ff2d5a94dce1777bbac48f6a5e923c2090d1c06d..c96925d9c59b9fd08b513b56b15446a6ed6427ac 100644 --- a/configs/mot/jde/README.md +++ b/configs/mot/jde/README.md @@ -31,19 +31,19 @@ PP-tracking provides an AI studio public project tutorial. Please refer to this | backbone | input shape | MOTA | IDF1 | IDS | FP | FN | FPS | download | config | | :----------------- | :------- | :----: | :----: | :---: | :----: | :---: | :---: | :---: | :---: | -| DarkNet53 | 1088x608 | 72.0 | 66.9 | 1397 | 7274 | 22209 | - |[model](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_1088x608.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/jde/jde_darknet53_30e_1088x608.yml) | -| DarkNet53 | 864x480 | 69.1 | 64.7 | 1539 | 7544 | 25046 | - |[model](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_864x480.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/jde/jde_darknet53_30e_864x480.yml) | -| DarkNet53 | 576x320 | 63.7 | 64.4 | 1310 | 6782 | 31964 | - |[model](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_576x320.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/jde/jde_darknet53_30e_576x320.yml) | +| DarkNet53 | 1088x608 | 72.0 | 66.9 | 1397 | 7274 | 22209 | - |[model](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_1088x608.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mot/jde/jde_darknet53_30e_1088x608.yml) | +| DarkNet53 | 864x480 | 69.1 | 64.7 | 1539 | 7544 | 25046 | - |[model](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_864x480.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mot/jde/jde_darknet53_30e_864x480.yml) | +| DarkNet53 | 576x320 | 63.7 | 64.4 | 1310 | 6782 | 31964 | - |[model](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_576x320.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mot/jde/jde_darknet53_30e_576x320.yml) | ### JDE Results on MOT-16 Test Set | backbone | input shape | MOTA | IDF1 | IDS | FP | FN | FPS | download | config | | :----------------- | :------- | :----: | :----: | :---: | :----: | :---: | :---: | :---: | :---: | | DarkNet53(paper) | 1088x608 | 64.4 | 55.8 | 1544 | - | - | - | - | - | -| DarkNet53 | 1088x608 | 64.6 | 58.5 | 1864 | 10550 | 52088 | - |[model](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_1088x608.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/jde/jde_darknet53_30e_1088x608.yml) | +| DarkNet53 | 1088x608 | 64.6 | 58.5 | 1864 | 10550 | 52088 | - |[model](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_1088x608.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mot/jde/jde_darknet53_30e_1088x608.yml) | | DarkNet53(paper) | 864x480 | 62.1 | 56.9 | 1608 | - | - | - | - | - | -| DarkNet53 | 864x480 | 63.2 | 57.7 | 1966 | 10070 | 55081 | - |[model](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_864x480.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/jde/jde_darknet53_30e_864x480.yml) | -| DarkNet53 | 576x320 | 59.1 | 56.4 | 1911 | 10923 | 61789 | - |[model](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_576x320.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/jde/jde_darknet53_30e_576x320.yml) | +| DarkNet53 | 864x480 | 63.2 | 57.7 | 1966 | 10070 | 55081 | - |[model](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_864x480.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mot/jde/jde_darknet53_30e_864x480.yml) | +| DarkNet53 | 576x320 | 59.1 | 56.4 | 1911 | 10923 | 61789 | - |[model](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_576x320.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mot/jde/jde_darknet53_30e_576x320.yml) | **Notes:** - JDE used 8 GPUs for training and mini-batch size as 4 on each GPU, and trained for 30 epoches. diff --git a/configs/mot/jde/README_cn.md b/configs/mot/jde/README_cn.md index 7f1dda46935b653bad3ad82b2610c34111e4f287..2651e3254876621b3aa33853c397d7eb49a5183f 100644 --- a/configs/mot/jde/README_cn.md +++ b/configs/mot/jde/README_cn.md @@ -29,9 +29,9 @@ PP-Tracking 提供了AI Studio公开项目案例，教程请参考[PP-Tracking | 骨干网络 | 输入尺寸 | MOTA | IDF1 | IDS | FP | FN | FPS | 下载链接 | 配置文件 | | :----------------- | :------- | :----: | :----: | :---: | :----: | :---: | :---: | :---: | :---: | -| DarkNet53 | 1088x608 | 72.0 | 66.9 | 1397 | 7274 | 22209 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_1088x608.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/jde/jde_darknet53_30e_1088x608.yml) | -| DarkNet53 | 864x480 | 69.1 | 64.7 | 1539 | 7544 | 25046 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_864x480.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/jde/jde_darknet53_30e_864x480.yml) | -| DarkNet53 | 576x320 | 63.7 | 64.4 | 1310 | 6782 | 31964 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_576x320.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/jde/jde_darknet53_30e_576x320.yml) | +| DarkNet53 | 1088x608 | 72.0 | 66.9 | 1397 | 7274 | 22209 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_1088x608.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mot/jde/jde_darknet53_30e_1088x608.yml) | +| DarkNet53 | 864x480 | 69.1 | 64.7 | 1539 | 7544 | 25046 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_864x480.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mot/jde/jde_darknet53_30e_864x480.yml) | +| DarkNet53 | 576x320 | 63.7 | 64.4 | 1310 | 6782 | 31964 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_576x320.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mot/jde/jde_darknet53_30e_576x320.yml) | ### JDE在MOT-16 Test Set上结果 @@ -39,10 +39,10 @@ PP-Tracking 提供了AI Studio公开项目案例，教程请参考[PP-Tracking | 骨干网络 | 输入尺寸 | MOTA | IDF1 | IDS | FP | FN | FPS | 下载链接 | 配置文件 | | :----------------- | :------- | :----: | :----: | :---: | :----: | :---: | :---: | :---: | :---: | | DarkNet53(paper) | 1088x608 | 64.4 | 55.8 | 1544 | - | - | - | - | - | -| DarkNet53 | 1088x608 | 64.6 | 58.5 | 1864 | 10550 | 52088 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_1088x608.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/jde/jde_darknet53_30e_1088x608.yml) | +| DarkNet53 | 1088x608 | 64.6 | 58.5 | 1864 | 10550 | 52088 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_1088x608.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mot/jde/jde_darknet53_30e_1088x608.yml) | | DarkNet53(paper) | 864x480 | 62.1 | 56.9 | 1608 | - | - | - | - | - | -| DarkNet53 | 864x480 | 63.2 | 57.7 | 1966 | 10070 | 55081 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_864x480.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/jde/jde_darknet53_30e_864x480.yml) | -| DarkNet53 | 576x320 | 59.1 | 56.4 | 1911 | 10923 | 61789 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_576x320.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/jde/jde_darknet53_30e_576x320.yml) | +| DarkNet53 | 864x480 | 63.2 | 57.7 | 1966 | 10070 | 55081 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_864x480.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mot/jde/jde_darknet53_30e_864x480.yml) | +| DarkNet53 | 576x320 | 59.1 | 56.4 | 1911 | 10923 | 61789 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_576x320.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mot/jde/jde_darknet53_30e_576x320.yml) | **注意:** - JDE使用8个GPU进行训练，每个GPU上batch size为4，训练了30个epoch。 diff --git a/configs/mot/mcfairmot/README.md b/configs/mot/mcfairmot/README.md index 4e595f3900fa89e0789bf98474a2ea40c1f2c633..0a39c37760d2d494e5e0fd6c578f8ee07b0c50b2 100644 --- a/configs/mot/mcfairmot/README.md +++ b/configs/mot/mcfairmot/README.md @@ -48,7 +48,7 @@ PP-tracking provides an AI studio public project tutorial. Please refer to this | Model | Compression Strategy | Prediction Delay（T4） |Prediction Delay（V100）| Model Configuration File |Compression Algorithm Configuration File | | :--------------| :------- | :------: | :----: | :----: | :----: | | DLA-34 | baseline | 41.3 | 21.9 |[Configuration File](./mcfairmot_dla34_30e_1088x608_visdrone_vehicle_bytetracker.yml)| - | -| DLA-34 | off-line quantization | 37.8 | 21.2 |[Configuration File](./mcfairmot_dla34_30e_1088x608_visdrone_vehicle_bytetracker.yml)|[Configuration File](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/slim/post_quant/mcfairmot_ptq.yml)| +| DLA-34 | off-line quantization | 37.8 | 21.2 |[Configuration File](./mcfairmot_dla34_30e_1088x608_visdrone_vehicle_bytetracker.yml)|[Configuration File](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/configs/slim/post_quant/mcfairmot_ptq.yml)| ## Getting Start diff --git a/configs/mot/mcfairmot/README_cn.md b/configs/mot/mcfairmot/README_cn.md index d054a04314977f397e840a4d778770ba9b50d366..705568caa080a5514def2c4797e6c2cce9b8f9f5 100644 --- a/configs/mot/mcfairmot/README_cn.md +++ b/configs/mot/mcfairmot/README_cn.md @@ -47,7 +47,7 @@ PP-Tracking 提供了AI Studio公开项目案例，教程请参考[PP-Tracking | 骨干网络 | 压缩策略 | 预测时延（T4） |预测时延（V100）| 配置文件 |压缩算法配置文件 | | :--------------| :------- | :------: | :----: | :----: | :----: | | DLA-34 | baseline | 41.3 | 21.9 |[配置文件](./mcfairmot_dla34_30e_1088x608_visdrone_vehicle_bytetracker.yml)| - | -| DLA-34 | 离线量化 | 37.8 | 21.2 |[配置文件](./mcfairmot_dla34_30e_1088x608_visdrone_vehicle_bytetracker.yml)|[配置文件](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/slim/post_quant/mcfairmot_ptq.yml)| +| DLA-34 | 离线量化 | 37.8 | 21.2 |[配置文件](./mcfairmot_dla34_30e_1088x608_visdrone_vehicle_bytetracker.yml)|[配置文件](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/configs/slim/post_quant/mcfairmot_ptq.yml)| ## 快速开始 diff --git a/configs/pedestrian/README.md b/configs/pedestrian/README.md index f9ba42a1985cb3dcad00d6a3b621d24f37e338ac..d42b11fbd3bf6eea79fa88afaeef3c8a767884ab 100644 --- a/configs/pedestrian/README.md +++ b/configs/pedestrian/README.md @@ -5,7 +5,7 @@ We provide some models implemented by PaddlePaddle to detect objects in specific | Task | Algorithm | Box AP | Download | Configs | |:---------------------|:---------:|:------:| :-------------------------------------------------------------------------------------: |:------:| -| Pedestrian Detection | YOLOv3 | 51.8 | [model](https://paddledet.bj.bcebos.com/models/pedestrian_yolov3_darknet.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/pedestrian/pedestrian_yolov3_darknet.yml) | +| Pedestrian Detection | YOLOv3 | 51.8 | [model](https://paddledet.bj.bcebos.com/models/pedestrian_yolov3_darknet.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/pedestrian/pedestrian_yolov3_darknet.yml) | ## Pedestrian Detection @@ -17,7 +17,7 @@ The network for detecting vehicles is YOLOv3, the backbone of which is Dacknet53 ### 2. Configuration for training -PaddleDetection provides users with a configuration file [yolov3_darknet53_270e_coco.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/yolov3/yolov3_darknet53_270e_coco.yml) to train YOLOv3 on the COCO dataset, compared with this file, we modify some parameters as followed to conduct the training for pedestrian detection: +PaddleDetection provides users with a configuration file [yolov3_darknet53_270e_coco.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/configs/yolov3/yolov3_darknet53_270e_coco.yml) to train YOLOv3 on the COCO dataset, compared with this file, we modify some parameters as followed to conduct the training for pedestrian detection: * num_classes: 1 * dataset_dir: dataset/pedestrian diff --git a/configs/pedestrian/README_cn.md b/configs/pedestrian/README_cn.md index a1d8b86dbf941427ec4a56e2b99b6fb7cc6a2004..80f0ecd1ed3dcbf8061964b59231cd3084a8cf97 100644 --- a/configs/pedestrian/README_cn.md +++ b/configs/pedestrian/README_cn.md @@ -5,7 +5,7 @@ | 任务 | 算法 | 精度(Box AP) | 下载 | 配置文件 | |:---------------------|:---------:|:------:| :---------------------------------------------------------------------------------: | :------:| -| 行人检测 | YOLOv3 | 51.8 | [下载链接](https://paddledet.bj.bcebos.com/models/pedestrian_yolov3_darknet.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/pedestrian/pedestrian_yolov3_darknet.yml) | +| 行人检测 | YOLOv3 | 51.8 | [下载链接](https://paddledet.bj.bcebos.com/models/pedestrian_yolov3_darknet.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/pedestrian/pedestrian_yolov3_darknet.yml) | ## 行人检测（Pedestrian Detection） @@ -18,7 +18,7 @@ Backbone为Dacknet53的YOLOv3。 ### 2. 训练参数配置 -PaddleDetection提供了使用COCO数据集对YOLOv3进行训练的参数配置文件[yolov3_darknet53_270e_coco.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/yolov3/yolov3_darknet53_270e_coco.yml)，与之相比，在进行行人检测的模型训练时，我们对以下参数进行了修改： +PaddleDetection提供了使用COCO数据集对YOLOv3进行训练的参数配置文件[yolov3_darknet53_270e_coco.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/configs/yolov3/yolov3_darknet53_270e_coco.yml)，与之相比，在进行行人检测的模型训练时，我们对以下参数进行了修改： * num_classes: 1 * dataset_dir: dataset/pedestrian diff --git a/configs/picodet/FULL_QUANTIZATION.md b/configs/picodet/FULL_QUANTIZATION.md index ff177d5ce726b3819660aef37c0560c61dfd08fb..da9654a0d35dbfa4155f2caddb4da689709c057d 100644 --- a/configs/picodet/FULL_QUANTIZATION.md +++ b/configs/picodet/FULL_QUANTIZATION.md @@ -36,8 +36,8 @@ | 模型 | 策略 | mAP | FP32 | INT8 | 配置文件 | 模型 | |:------------- |:-------- |:----:|:----:|:----:|:---------------------------------------------------------------------------------------------------------------------------------:|:-----------------------------------------------------------------------------------:| -| PicoDet-S-NPU | Baseline | 30.1 | - | - | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet/picodet_s_416_coco_npu.yml) | [Model](https://bj.bcebos.com/v1/paddle-slim-models/act/picodet_s_416_coco_npu.tar) | -| PicoDet-S-NPU | 量化训练 | 29.7 | - | - | [config](https://github.com/PaddlePaddle/PaddleSlim/tree/develop/demo/full_quantization/detection/configs/picodet_s_qat_dis.yaml) | [Model](https://bj.bcebos.com/v1/paddle-slim-models/act/picodet_s_npu_quant.tar) | +| PicoDet-S-NPU | Baseline | 30.1 | - | - | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/picodet_s_416_coco_npu.yml) | [Model](https://bj.bcebos.com/v1/paddle-slim-models/act/picodet_s_416_coco_npu.tar) | +| PicoDet-S-NPU | 量化训练 | 29.7 | - | - | [config](https://github.com/PaddlePaddle/PaddleSlim/tree/release/2.5/demo/full_quantization/detection/configs/picodet_s_qat_dis.yaml) | [Model](https://bj.bcebos.com/v1/paddle-slim-models/act/picodet_s_npu_quant.tar) | - mAP的指标均在COCO val2017数据集中评测得到，IoU=0.5:0.95。 diff --git a/configs/picodet/README.md b/configs/picodet/README.md index 10edd3a928fca7cc24a30b924a475d7df91375a5..adced96f01fc9a1513fcb91710237e20808b952c 100644 --- a/configs/picodet/README.md +++ b/configs/picodet/README.md @@ -37,21 +37,21 @@ PP-PicoDet模型有如下特点： | 模型 | 输入尺寸 | mAPval
0.5:0.95 | mAPval
0.5 | 参数量
(M) | FLOPS
(G) | 预测时延[CPU](#latency)
(ms) | 预测时延[Lite](#latency)
(ms) | 权重下载 | 配置文件 | 导出模型 | | :-------- | :--------: | :---------------------: | :----------------: | :----------------: | :---------------: | :-----------------------------: | :-----------------------------: | :----------------------------------------: | :--------------------------------------- | :--------------------------------------- | -| PicoDet-XS | 320*320 | 23.5 | 36.1 | 0.70 | 0.67 | 3.9ms | 7.81ms | [model](https://paddledet.bj.bcebos.com/models/picodet_xs_320_coco_lcnet.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_xs_320_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet/picodet_xs_320_coco_lcnet.yml) | [w/ 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_xs_320_coco_lcnet.tar) | [w/o 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_xs_320_coco_lcnet_non_postprocess.tar) | -| PicoDet-XS | 416*416 | 26.2 | 39.3 | 0.70 | 1.13 | 6.1ms | 12.38ms | [model](https://paddledet.bj.bcebos.com/models/picodet_xs_416_coco_lcnet.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_xs_416_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet/picodet_xs_416_coco_lcnet.yml) | [w/ 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_xs_416_coco_lcnet.tar) | [w/o 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_xs_416_coco_lcnet_non_postprocess.tar) | -| PicoDet-S | 320*320 | 29.1 | 43.4 | 1.18 | 0.97 | 4.8ms | 9.56ms | [model](https://paddledet.bj.bcebos.com/models/picodet_s_320_coco_lcnet.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_s_320_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet/picodet_s_320_coco_lcnet.yml) | [w/ 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_s_320_coco_lcnet.tar) | [w/o 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_s_320_coco_lcnet_non_postprocess.tar) | -| PicoDet-S | 416*416 | 32.5 | 47.6 | 1.18 | 1.65 | 6.6ms | 15.20ms | [model](https://paddledet.bj.bcebos.com/models/picodet_s_416_coco_lcnet.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_s_416_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet/picodet_s_416_coco_lcnet.yml) | [w/ 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_s_416_coco_lcnet.tar) | [w/o 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_s_416_coco_lcnet_non_postprocess.tar) | -| PicoDet-M | 320*320 | 34.4 | 50.0 | 3.46 | 2.57 | 8.2ms | 17.68ms | [model](https://paddledet.bj.bcebos.com/models/picodet_m_320_coco_lcnet.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_m_320_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet/picodet_m_320_coco_lcnet.yml) | [w/ 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_m_320_coco_lcnet.tar) | [w/o 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_m_320_coco_lcnet_non_postprocess.tar) | -| PicoDet-M | 416*416 | 37.5 | 53.4 | 3.46 | 4.34 | 12.7ms | 28.39ms | [model](https://paddledet.bj.bcebos.com/models/picodet_m_416_coco_lcnet.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_m_416_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet/picodet_m_416_coco_lcnet.yml) | [w/ 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_m_416_coco_lcnet.tar) | [w/o 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_m_416_coco_lcnet_non_postprocess.tar) | -| PicoDet-L | 320*320 | 36.1 | 52.0 | 5.80 | 4.20 | 11.5ms | 25.21ms | [model](https://paddledet.bj.bcebos.com/models/picodet_l_320_coco_lcnet.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_l_320_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet/picodet_l_320_coco_lcnet.yml) | [w/ 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_l_320_coco_lcnet.tar) | [w/o 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_l_320_coco_lcnet_non_postprocess.tar) | -| PicoDet-L | 416*416 | 39.4 | 55.7 | 5.80 | 7.10 | 20.7ms | 42.23ms | [model](https://paddledet.bj.bcebos.com/models/picodet_l_416_coco_lcnet.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_l_416_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet/picodet_l_416_coco_lcnet.yml) | [w/ 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_l_416_coco_lcnet.tar) | [w/o 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_l_416_coco_lcnet_non_postprocess.tar) | -| PicoDet-L | 640*640 | 42.6 | 59.2 | 5.80 | 16.81 | 62.5ms | 108.1ms | [model](https://paddledet.bj.bcebos.com/models/picodet_l_640_coco_lcnet.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_l_640_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet/picodet_l_640_coco_lcnet.yml) | [w/ 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_l_640_coco_lcnet.tar) | [w/o 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_l_640_coco_lcnet_non_postprocess.tar) | +| PicoDet-XS | 320*320 | 23.5 | 36.1 | 0.70 | 0.67 | 3.9ms | 7.81ms | [model](https://paddledet.bj.bcebos.com/models/picodet_xs_320_coco_lcnet.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_xs_320_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/picodet_xs_320_coco_lcnet.yml) | [w/ 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_xs_320_coco_lcnet.tar) | [w/o 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_xs_320_coco_lcnet_non_postprocess.tar) | +| PicoDet-XS | 416*416 | 26.2 | 39.3 | 0.70 | 1.13 | 6.1ms | 12.38ms | [model](https://paddledet.bj.bcebos.com/models/picodet_xs_416_coco_lcnet.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_xs_416_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/picodet_xs_416_coco_lcnet.yml) | [w/ 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_xs_416_coco_lcnet.tar) | [w/o 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_xs_416_coco_lcnet_non_postprocess.tar) | +| PicoDet-S | 320*320 | 29.1 | 43.4 | 1.18 | 0.97 | 4.8ms | 9.56ms | [model](https://paddledet.bj.bcebos.com/models/picodet_s_320_coco_lcnet.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_s_320_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/picodet_s_320_coco_lcnet.yml) | [w/ 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_s_320_coco_lcnet.tar) | [w/o 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_s_320_coco_lcnet_non_postprocess.tar) | +| PicoDet-S | 416*416 | 32.5 | 47.6 | 1.18 | 1.65 | 6.6ms | 15.20ms | [model](https://paddledet.bj.bcebos.com/models/picodet_s_416_coco_lcnet.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_s_416_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/picodet_s_416_coco_lcnet.yml) | [w/ 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_s_416_coco_lcnet.tar) | [w/o 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_s_416_coco_lcnet_non_postprocess.tar) | +| PicoDet-M | 320*320 | 34.4 | 50.0 | 3.46 | 2.57 | 8.2ms | 17.68ms | [model](https://paddledet.bj.bcebos.com/models/picodet_m_320_coco_lcnet.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_m_320_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/picodet_m_320_coco_lcnet.yml) | [w/ 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_m_320_coco_lcnet.tar) | [w/o 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_m_320_coco_lcnet_non_postprocess.tar) | +| PicoDet-M | 416*416 | 37.5 | 53.4 | 3.46 | 4.34 | 12.7ms | 28.39ms | [model](https://paddledet.bj.bcebos.com/models/picodet_m_416_coco_lcnet.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_m_416_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/picodet_m_416_coco_lcnet.yml) | [w/ 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_m_416_coco_lcnet.tar) | [w/o 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_m_416_coco_lcnet_non_postprocess.tar) | +| PicoDet-L | 320*320 | 36.1 | 52.0 | 5.80 | 4.20 | 11.5ms | 25.21ms | [model](https://paddledet.bj.bcebos.com/models/picodet_l_320_coco_lcnet.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_l_320_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/picodet_l_320_coco_lcnet.yml) | [w/ 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_l_320_coco_lcnet.tar) | [w/o 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_l_320_coco_lcnet_non_postprocess.tar) | +| PicoDet-L | 416*416 | 39.4 | 55.7 | 5.80 | 7.10 | 20.7ms | 42.23ms | [model](https://paddledet.bj.bcebos.com/models/picodet_l_416_coco_lcnet.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_l_416_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/picodet_l_416_coco_lcnet.yml) | [w/ 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_l_416_coco_lcnet.tar) | [w/o 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_l_416_coco_lcnet_non_postprocess.tar) | +| PicoDet-L | 640*640 | 42.6 | 59.2 | 5.80 | 16.81 | 62.5ms | 108.1ms | [model](https://paddledet.bj.bcebos.com/models/picodet_l_640_coco_lcnet.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_l_640_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/picodet_l_640_coco_lcnet.yml) | [w/ 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_l_640_coco_lcnet.tar) | [w/o 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_l_640_coco_lcnet_non_postprocess.tar) | - 特色模型 | 模型 | 输入尺寸 | mAPval
0.5:0.95 | mAPval
0.5 | 参数量
(M) | FLOPS
(G) | 预测时延[CPU](#latency)
(ms) | 预测时延[Lite](#latency)
(ms) | 权重下载 | 配置文件 | | :-------- | :--------: | :---------------------: | :----------------: | :----------------: | :---------------: | :-----------------------------: | :-----------------------------: | :----------------------------------------: | :--------------------------------------- | -| PicoDet-S-NPU | 416*416 | 30.1 | 44.2 | - | - | - | - | [model](https://paddledet.bj.bcebos.com/models/picodet_s_416_coco_npu.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_s_416_coco_npu.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet/picodet_s_416_coco_npu.yml) | +| PicoDet-S-NPU | 416*416 | 30.1 | 44.2 | - | - | - | - | [model](https://paddledet.bj.bcebos.com/models/picodet_s_416_coco_npu.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_s_416_coco_npu.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/picodet_s_416_coco_npu.yml) |
@@ -59,7 +59,7 @@ PP-PicoDet模型有如下特点： - 时延测试： 我们所有的模型都在`英特尔酷睿i7 10750H`的CPU 和`骁龙865(4xA77+4xA55)`的ARM CPU上测试(4线程，FP16预测)。上面表格中标有`CPU`的是使用OpenVINO测试，标有`Lite`的是使用[Paddle Lite](https://github.com/PaddlePaddle/Paddle-Lite)进行测试。 - PicoDet在COCO train2017上训练，并且在COCO val2017上进行验证。使用4卡GPU训练，并且上表所有的预训练模型都是通过发布的默认配置训练得到。 -- Benchmark测试：测试速度benchmark性能时，导出模型后处理不包含在网络中，需要设置`-o export.benchmark=True` 或手动修改[runtime.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/runtime.yml#L12)。 +- Benchmark测试：测试速度benchmark性能时，导出模型后处理不包含在网络中，需要设置`-o export.benchmark=True` 或手动修改[runtime.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/configs/runtime.yml#L12)。
@@ -93,8 +93,8 @@ PP-PicoDet模型有如下特点：
安装 -- [安装指导文档](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/docs/tutorials/INSTALL.md) -- [准备数据文档](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/docs/tutorials/PrepareDataSet_en.md) +- [安装指导文档](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/docs/tutorials/INSTALL.md) +- [准备数据文档](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/docs/tutorials/PrepareDataSet_en.md)
@@ -136,7 +136,7 @@ python tools/infer.py -c configs/picodet/picodet_s_320_coco_lcnet.yml \ -o weights=https://paddledet.bj.bcebos.com/models/picodet_s_320_coco_lcnet.pdparams ``` -详情请参考[快速开始文档](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/docs/tutorials/GETTING_STARTED.md). +详情请参考[快速开始文档](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/docs/tutorials/GETTING_STARTED.md). @@ -155,8 +155,8 @@ python tools/export_model.py -c configs/picodet/picodet_s_320_coco_lcnet.yml \ --output_dir=output_inference ``` -- 如无需导出后处理，请指定：`-o export.benchmark=True`（如果-o已出现过，此处删掉-o）或者手动修改[runtime.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/runtime.yml) 中相应字段。 -- 如无需导出NMS，请指定：`-o export.nms=False`或者手动修改[runtime.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/runtime.yml) 中相应字段。 许多导出至ONNX场景只支持单输入及固定shape输出，所以如果导出至ONNX，推荐不导出NMS。 +- 如无需导出后处理，请指定：`-o export.benchmark=True`（如果-o已出现过，此处删掉-o）或者手动修改[runtime.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/configs/runtime.yml) 中相应字段。 +- 如无需导出NMS，请指定：`-o export.nms=False`或者手动修改[runtime.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/configs/runtime.yml) 中相应字段。 许多导出至ONNX场景只支持单输入及固定shape输出，所以如果导出至ONNX，推荐不导出NMS。 @@ -273,7 +273,7 @@ python tools/train.py -c configs/picodet/picodet_s_416_coco_lcnet.yml \ --slim_config configs/slim/quant/picodet_s_416_lcnet_quant.yml --eval ``` -- 更多细节请参考[slim文档](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim) +- 更多细节请参考[slim文档](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/slim) @@ -288,13 +288,13 @@ python tools/train.py -c configs/picodet/picodet_s_416_coco_lcnet.yml \
教程: -训练及部署细节请参考[非结构化剪枝文档](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet/legacy_model/pruner/README.md)。 +训练及部署细节请参考[非结构化剪枝文档](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/legacy_model/pruner/README.md)。
## 应用 -- **行人检测：** `PicoDet-S-Pedestrian`行人检测模型请参考[PP-TinyPose](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/keypoint/tiny_pose#%E8%A1%8C%E4%BA%BA%E6%A3%80%E6%B5%8B%E6%A8%A1%E5%9E%8B) +- **行人检测：** `PicoDet-S-Pedestrian`行人检测模型请参考[PP-TinyPose](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/keypoint/tiny_pose#%E8%A1%8C%E4%BA%BA%E6%A3%80%E6%B5%8B%E6%A8%A1%E5%9E%8B) - **主体检测：** `PicoDet-L-Mainbody`主体检测模型请参考[主体检测文档](./legacy_model/application/mainbody_detection/README.md) @@ -328,7 +328,7 @@ pretrain_weights: https://paddledet.bj.bcebos.com/models/picodet_l_640_coco_lcne
如何计算模型参数量。 -可以将以下代码插入：[trainer.py](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/ppdet/engine/trainer.py#L141) 来计算参数量。 +可以将以下代码插入：[trainer.py](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/ppdet/engine/trainer.py#L141) 来计算参数量。 ```python params = sum([ diff --git a/configs/picodet/README_en.md b/configs/picodet/README_en.md index d7d51c7b3b774ce0f68822a7d5084ea8639ada53..80b8a86729c9a1c0aeacdae1988b563a81d8d2da 100644 --- a/configs/picodet/README_en.md +++ b/configs/picodet/README_en.md @@ -33,22 +33,22 @@ We developed a series of lightweight models, named `PP-PicoDet`. Because of the | Model | Input size | mAPval
0.5:0.95 | mAPval
0.5 | Params
(M) | FLOPS
(G) | Latency[CPU](#latency)
(ms) | Latency[Lite](#latency)
(ms) | Weight | Config | Inference Model | | :-------- | :--------: | :---------------------: | :----------------: | :----------------: | :---------------: | :-----------------------------: | :-----------------------------: | :----------------------------------------: | :--------------------------------------- | :--------------------------------------- | -| PicoDet-XS | 320*320 | 23.5 | 36.1 | 0.70 | 0.67 | 3.9ms | 7.81ms | [model](https://paddledet.bj.bcebos.com/models/picodet_xs_320_coco_lcnet.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_xs_320_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet/picodet_xs_320_coco_lcnet.yml) | [w/ postprocess](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_xs_320_coco_lcnet.tar) | [w/o postprocess](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_xs_320_coco_lcnet_non_postprocess.tar) | -| PicoDet-XS | 416*416 | 26.2 | 39.3 | 0.70 | 1.13 | 6.1ms | 12.38ms | [model](https://paddledet.bj.bcebos.com/models/picodet_xs_416_coco_lcnet.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_xs_416_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet/picodet_xs_416_coco_lcnet.yml) | [w/ postprocess](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_xs_416_coco_lcnet.tar) | [w/o postprocess](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_xs_416_coco_lcnet_non_postprocess.tar) | -| PicoDet-S | 320*320 | 29.1 | 43.4 | 1.18 | 0.97 | 4.8ms | 9.56ms | [model](https://paddledet.bj.bcebos.com/models/picodet_s_320_coco_lcnet.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_s_320_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet/picodet_s_320_coco_lcnet.yml) | [w/ postprocess](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_s_320_coco_lcnet.tar) | [w/o postprocess](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_s_320_coco_lcnet_non_postprocess.tar) | -| PicoDet-S | 416*416 | 32.5 | 47.6 | 1.18 | 1.65 | 6.6ms | 15.20ms | [model](https://paddledet.bj.bcebos.com/models/picodet_s_416_coco_lcnet.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_s_416_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet/picodet_s_416_coco_lcnet.yml) | [w/ postprocess](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_s_416_coco_lcnet.tar) | [w/o postprocess](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_s_416_coco_lcnet_non_postprocess.tar) | -| PicoDet-M | 320*320 | 34.4 | 50.0 | 3.46 | 2.57 | 8.2ms | 17.68ms | [model](https://paddledet.bj.bcebos.com/models/picodet_m_320_coco_lcnet.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_m_320_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet/picodet_m_320_coco_lcnet.yml) | [w/ postprocess](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_m_320_coco_lcnet.tar) | [w/o postprocess](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_m_320_coco_lcnet_non_postprocess.tar) | -| PicoDet-M | 416*416 | 37.5 | 53.4 | 3.46 | 4.34 | 12.7ms | 28.39ms | [model](https://paddledet.bj.bcebos.com/models/picodet_m_416_coco_lcnet.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_m_416_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet/picodet_m_416_coco_lcnet.yml) | [w/ postprocess](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_m_416_coco_lcnet.tar) | [w/o postprocess](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_m_416_coco_lcnet_non_postprocess.tar) | -| PicoDet-L | 320*320 | 36.1 | 52.0 | 5.80 | 4.20 | 11.5ms | 25.21ms | [model](https://paddledet.bj.bcebos.com/models/picodet_l_320_coco_lcnet.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_l_320_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet/picodet_l_320_coco_lcnet.yml) | [w/ postprocess](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_l_320_coco_lcnet.tar) | [w/o postprocess](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_l_320_coco_lcnet_non_postprocess.tar) | -| PicoDet-L | 416*416 | 39.4 | 55.7 | 5.80 | 7.10 | 20.7ms | 42.23ms | [model](https://paddledet.bj.bcebos.com/models/picodet_l_416_coco_lcnet.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_l_416_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet/picodet_l_416_coco_lcnet.yml) | [w/ postprocess](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_l_416_coco_lcnet.tar) | [w/o postprocess](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_l_416_coco_lcnet_non_postprocess.tar) | -| PicoDet-L | 640*640 | 42.6 | 59.2 | 5.80 | 16.81 | 62.5ms | 108.1ms | [model](https://paddledet.bj.bcebos.com/models/picodet_l_640_coco_lcnet.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_l_640_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet/picodet_l_640_coco_lcnet.yml) | [w/ postprocess](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_l_640_coco_lcnet.tar) | [w/o postprocess](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_l_640_coco_lcnet_non_postprocess.tar) | +| PicoDet-XS | 320*320 | 23.5 | 36.1 | 0.70 | 0.67 | 3.9ms | 7.81ms | [model](https://paddledet.bj.bcebos.com/models/picodet_xs_320_coco_lcnet.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_xs_320_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/picodet_xs_320_coco_lcnet.yml) | [w/ postprocess](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_xs_320_coco_lcnet.tar) | [w/o postprocess](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_xs_320_coco_lcnet_non_postprocess.tar) | +| PicoDet-XS | 416*416 | 26.2 | 39.3 | 0.70 | 1.13 | 6.1ms | 12.38ms | [model](https://paddledet.bj.bcebos.com/models/picodet_xs_416_coco_lcnet.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_xs_416_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/picodet_xs_416_coco_lcnet.yml) | [w/ postprocess](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_xs_416_coco_lcnet.tar) | [w/o postprocess](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_xs_416_coco_lcnet_non_postprocess.tar) | +| PicoDet-S | 320*320 | 29.1 | 43.4 | 1.18 | 0.97 | 4.8ms | 9.56ms | [model](https://paddledet.bj.bcebos.com/models/picodet_s_320_coco_lcnet.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_s_320_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/picodet_s_320_coco_lcnet.yml) | [w/ postprocess](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_s_320_coco_lcnet.tar) | [w/o postprocess](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_s_320_coco_lcnet_non_postprocess.tar) | +| PicoDet-S | 416*416 | 32.5 | 47.6 | 1.18 | 1.65 | 6.6ms | 15.20ms | [model](https://paddledet.bj.bcebos.com/models/picodet_s_416_coco_lcnet.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_s_416_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/picodet_s_416_coco_lcnet.yml) | [w/ postprocess](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_s_416_coco_lcnet.tar) | [w/o postprocess](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_s_416_coco_lcnet_non_postprocess.tar) | +| PicoDet-M | 320*320 | 34.4 | 50.0 | 3.46 | 2.57 | 8.2ms | 17.68ms | [model](https://paddledet.bj.bcebos.com/models/picodet_m_320_coco_lcnet.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_m_320_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/picodet_m_320_coco_lcnet.yml) | [w/ postprocess](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_m_320_coco_lcnet.tar) | [w/o postprocess](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_m_320_coco_lcnet_non_postprocess.tar) | +| PicoDet-M | 416*416 | 37.5 | 53.4 | 3.46 | 4.34 | 12.7ms | 28.39ms | [model](https://paddledet.bj.bcebos.com/models/picodet_m_416_coco_lcnet.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_m_416_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/picodet_m_416_coco_lcnet.yml) | [w/ postprocess](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_m_416_coco_lcnet.tar) | [w/o postprocess](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_m_416_coco_lcnet_non_postprocess.tar) | +| PicoDet-L | 320*320 | 36.1 | 52.0 | 5.80 | 4.20 | 11.5ms | 25.21ms | [model](https://paddledet.bj.bcebos.com/models/picodet_l_320_coco_lcnet.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_l_320_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/picodet_l_320_coco_lcnet.yml) | [w/ postprocess](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_l_320_coco_lcnet.tar) | [w/o postprocess](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_l_320_coco_lcnet_non_postprocess.tar) | +| PicoDet-L | 416*416 | 39.4 | 55.7 | 5.80 | 7.10 | 20.7ms | 42.23ms | [model](https://paddledet.bj.bcebos.com/models/picodet_l_416_coco_lcnet.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_l_416_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/picodet_l_416_coco_lcnet.yml) | [w/ postprocess](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_l_416_coco_lcnet.tar) | [w/o postprocess](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_l_416_coco_lcnet_non_postprocess.tar) | +| PicoDet-L | 640*640 | 42.6 | 59.2 | 5.80 | 16.81 | 62.5ms | 108.1ms | [model](https://paddledet.bj.bcebos.com/models/picodet_l_640_coco_lcnet.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_l_640_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/picodet_l_640_coco_lcnet.yml) | [w/ postprocess](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_l_640_coco_lcnet.tar) | [w/o postprocess](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_l_640_coco_lcnet_non_postprocess.tar) |
Table Notes: - Latency: All our models test on `Intel core i7 10750H` CPU with MKLDNN by 12 threads and `Qualcomm Snapdragon 865(4xA77+4xA55)` with 4 threads by arm8 and with FP16. In the above table, test CPU latency on Paddle-Inference and testing Mobile latency with `Lite`->[Paddle-Lite](https://github.com/PaddlePaddle/Paddle-Lite). - PicoDet is trained on COCO train2017 dataset and evaluated on COCO val2017. And PicoDet used 4 GPUs for training and all checkpoints are trained with default settings and hyperparameters. -- Benchmark test: When testing the speed benchmark, the post-processing is not included in the exported model, you need to set `-o export.benchmark=True` or manually modify [runtime.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/runtime.yml#L12). +- Benchmark test: When testing the speed benchmark, the post-processing is not included in the exported model, you need to set `-o export.benchmark=True` or manually modify [runtime.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/configs/runtime.yml#L12).
@@ -82,8 +82,8 @@ We developed a series of lightweight models, named `PP-PicoDet`. Because of the
Installation -- [Installation guide](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/docs/tutorials/INSTALL.md) -- [Prepare dataset](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/docs/tutorials/PrepareDataSet_en.md) +- [Installation guide](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/docs/tutorials/INSTALL.md) +- [Prepare dataset](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/docs/tutorials/PrepareDataSet_en.md)
@@ -122,7 +122,7 @@ python tools/infer.py -c configs/picodet/picodet_s_320_coco_lcnet.yml \ -o weights=https://paddledet.bj.bcebos.com/models/picodet_s_320_coco_lcnet.pdparams ``` -Detail also can refer to [Quick start guide](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/docs/tutorials/GETTING_STARTED.md). +Detail also can refer to [Quick start guide](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/docs/tutorials/GETTING_STARTED.md).
@@ -141,8 +141,8 @@ python tools/export_model.py -c configs/picodet/picodet_s_320_coco_lcnet.yml \ --output_dir=output_inference ``` -- If no post processing is required, please specify: `-o export.benchmark=True` (if -o has already appeared, delete -o here) or manually modify corresponding fields in [runtime.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/runtime.yml). -- If no NMS is required, please specify: `-o export.nms=True` or manually modify corresponding fields in [runtime.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/runtime.yml). Many scenes exported to ONNX only support single input and fixed shape output, so if exporting to ONNX, it is recommended not to export NMS. +- If no post processing is required, please specify: `-o export.benchmark=True` (if -o has already appeared, delete -o here) or manually modify corresponding fields in [runtime.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/configs/runtime.yml). +- If no NMS is required, please specify: `-o export.nms=True` or manually modify corresponding fields in [runtime.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/configs/runtime.yml). Many scenes exported to ONNX only support single input and fixed shape output, so if exporting to ONNX, it is recommended not to export NMS. @@ -260,7 +260,7 @@ python tools/train.py -c configs/picodet/picodet_s_416_coco_lcnet.yml \ --slim_config configs/slim/quant/picodet_s_416_lcnet_quant.yml --eval ``` -- More detail can refer to [slim document](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim) +- More detail can refer to [slim document](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/slim) @@ -275,13 +275,13 @@ python tools/train.py -c configs/picodet/picodet_s_416_coco_lcnet.yml \
Tutorial: -Please refer this [documentation](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet/legacy_model/pruner/README.md) for details such as requirements, training and deployment. +Please refer this [documentation](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/legacy_model/pruner/README.md) for details such as requirements, training and deployment.
## Application -- **Pedestrian detection:** model zoo of `PicoDet-S-Pedestrian` please refer to [PP-TinyPose](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/keypoint/tiny_pose#%E8%A1%8C%E4%BA%BA%E6%A3%80%E6%B5%8B%E6%A8%A1%E5%9E%8B) +- **Pedestrian detection:** model zoo of `PicoDet-S-Pedestrian` please refer to [PP-TinyPose](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/keypoint/tiny_pose#%E8%A1%8C%E4%BA%BA%E6%A3%80%E6%B5%8B%E6%A8%A1%E5%9E%8B) - **Mainbody detection:** model zoo of `PicoDet-L-Mainbody` please refer to [mainbody detection](./legacy_model/application/mainbody_detection/README.md) @@ -315,7 +315,7 @@ Please use `PicoDet-LCNet` model, which has fewer `transpose` operators.
How to count model parameters. -You can insert below code at [here](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/ppdet/engine/trainer.py#L141) to count learnable parameters. +You can insert below code at [here](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/ppdet/engine/trainer.py#L141) to count learnable parameters. ```python params = sum([ diff --git a/configs/picodet/legacy_model/README.md b/configs/picodet/legacy_model/README.md index 7821c88be602bfa57cfd4ab36bcaa1040ce8a85c..3fd1654f2754502301b2598590d575030dc8bcbd 100644 --- a/configs/picodet/legacy_model/README.md +++ b/configs/picodet/legacy_model/README.md @@ -2,23 +2,23 @@ | Model | Input size | mAPval
0.5:0.95 | mAPval
0.5 | Params
(M) | FLOPS
(G) | Latency[NCNN](#latency)
(ms) | Latency[Lite](#latency)
(ms) | Download | Config | | :-------- | :--------: | :---------------------: | :----------------: | :----------------: | :---------------: | :-----------------------------: | :-----------------------------: | :----------------------------------------: | :--------------------------------------- | -| PicoDet-S | 320*320 | 27.1 | 41.4 | 0.99 | 0.73 | 8.13 | **6.65** | [model](https://paddledet.bj.bcebos.com/models/picodet_s_320_coco.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_s_320_coco.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet/picodet_s_320_coco.yml) | -| PicoDet-S | 416*416 | 30.7 | 45.8 | 0.99 | 1.24 | 12.37 | **9.82** | [model](https://paddledet.bj.bcebos.com/models/picodet_s_416_coco.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_s_416_coco.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet/picodet_s_416_coco.yml) | -| PicoDet-M | 320*320 | 30.9 | 45.7 | 2.15 | 1.48 | 11.27 | **9.61** | [model](https://paddledet.bj.bcebos.com/models/picodet_m_320_coco.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_m_320_coco.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet/picodet_m_320_coco.yml) | -| PicoDet-M | 416*416 | 34.8 | 50.5 | 2.15 | 2.50 | 17.39 | **15.88** | [model](https://paddledet.bj.bcebos.com/models/picodet_m_416_coco.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_m_416_coco.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet/picodet_m_416_coco.yml) | -| PicoDet-L | 320*320 | 32.9 | 48.2 | 3.30 | 2.23 | 15.26 | **13.42** | [model](https://paddledet.bj.bcebos.com/models/picodet_l_320_coco.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_l_320_coco.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet/picodet_l_320_coco.yml) | -| PicoDet-L | 416*416 | 36.6 | 52.5 | 3.30 | 3.76 | 23.36 | **21.85** | [model](https://paddledet.bj.bcebos.com/models/picodet_l_416_coco.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_l_416_coco.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet/picodet_l_416_coco.yml) | -| PicoDet-L | 640*640 | 40.9 | 57.6 | 3.30 | 8.91 | 54.11 | **50.55** | [model](https://paddledet.bj.bcebos.com/models/picodet_l_640_coco.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_l_640_coco.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet/picodet_l_640_coco.yml) | +| PicoDet-S | 320*320 | 27.1 | 41.4 | 0.99 | 0.73 | 8.13 | **6.65** | [model](https://paddledet.bj.bcebos.com/models/picodet_s_320_coco.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_s_320_coco.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/picodet_s_320_coco.yml) | +| PicoDet-S | 416*416 | 30.7 | 45.8 | 0.99 | 1.24 | 12.37 | **9.82** | [model](https://paddledet.bj.bcebos.com/models/picodet_s_416_coco.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_s_416_coco.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/picodet_s_416_coco.yml) | +| PicoDet-M | 320*320 | 30.9 | 45.7 | 2.15 | 1.48 | 11.27 | **9.61** | [model](https://paddledet.bj.bcebos.com/models/picodet_m_320_coco.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_m_320_coco.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/picodet_m_320_coco.yml) | +| PicoDet-M | 416*416 | 34.8 | 50.5 | 2.15 | 2.50 | 17.39 | **15.88** | [model](https://paddledet.bj.bcebos.com/models/picodet_m_416_coco.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_m_416_coco.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/picodet_m_416_coco.yml) | +| PicoDet-L | 320*320 | 32.9 | 48.2 | 3.30 | 2.23 | 15.26 | **13.42** | [model](https://paddledet.bj.bcebos.com/models/picodet_l_320_coco.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_l_320_coco.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/picodet_l_320_coco.yml) | +| PicoDet-L | 416*416 | 36.6 | 52.5 | 3.30 | 3.76 | 23.36 | **21.85** | [model](https://paddledet.bj.bcebos.com/models/picodet_l_416_coco.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_l_416_coco.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/picodet_l_416_coco.yml) | +| PicoDet-L | 640*640 | 40.9 | 57.6 | 3.30 | 8.91 | 54.11 | **50.55** | [model](https://paddledet.bj.bcebos.com/models/picodet_l_640_coco.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_l_640_coco.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/picodet_l_640_coco.yml) | #### More Configs | Model | Input size | mAPval
0.5:0.95 | mAPval
0.5 | Params
(M) | FLOPS
(G) | Latency[NCNN](#latency)
(ms) | Latency[Lite](#latency)
(ms) | Download | Config | | :--------------------------- | :--------: | :---------------------: | :----------------: | :----------------: | :---------------: | :-----------------------------: | :-----------------------------: | :----------------------------------------: | :--------------------------------------- | -| PicoDet-Shufflenetv2 1x | 416*416 | 30.0 | 44.6 | 1.17 | 1.53 | 15.06 | **10.63** | [model](https://paddledet.bj.bcebos.com/models/picodet_shufflenetv2_1x_416_coco.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_shufflenetv2_1x_416_coco.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet/more_config/picodet_shufflenetv2_1x_416_coco.yml) | -| PicoDet-MobileNetv3-large 1x | 416*416 | 35.6 | 52.0 | 3.55 | 2.80 | 20.71 | **17.88** | [model](https://paddledet.bj.bcebos.com/models/picodet_mobilenetv3_large_1x_416_coco.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_mobilenetv3_large_1x_416_coco.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet/more_config/picodet_mobilenetv3_large_1x_416_coco.yml) | -| PicoDet-LCNet 1.5x | 416*416 | 36.3 | 52.2 | 3.10 | 3.85 | 21.29 | **20.8** | [model](https://paddledet.bj.bcebos.com/models/picodet_lcnet_1_5x_416_coco.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_lcnet_1_5x_416_coco.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet/more_config/picodet_lcnet_1_5x_416_coco.yml) | -| PicoDet-LCNet 1.5x | 640*640 | 40.6 | 57.4 | 3.10 | - | - | - | [model](https://paddledet.bj.bcebos.com/models/picodet_lcnet_1_5x_640_coco.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_lcnet_1_5x_640_coco.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet/more_config/picodet_lcnet_1_5x_640_coco.yml) | -| PicoDet-R18 | 640*640 | 40.7 | 57.2 | 11.10 | - | - | - | [model](https://paddledet.bj.bcebos.com/models/picodet_r18_640_coco.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_r18_640_coco.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet/more_config/picodet_r18_640_coco.yml) | +| PicoDet-Shufflenetv2 1x | 416*416 | 30.0 | 44.6 | 1.17 | 1.53 | 15.06 | **10.63** | [model](https://paddledet.bj.bcebos.com/models/picodet_shufflenetv2_1x_416_coco.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_shufflenetv2_1x_416_coco.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/more_config/picodet_shufflenetv2_1x_416_coco.yml) | +| PicoDet-MobileNetv3-large 1x | 416*416 | 35.6 | 52.0 | 3.55 | 2.80 | 20.71 | **17.88** | [model](https://paddledet.bj.bcebos.com/models/picodet_mobilenetv3_large_1x_416_coco.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_mobilenetv3_large_1x_416_coco.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/more_config/picodet_mobilenetv3_large_1x_416_coco.yml) | +| PicoDet-LCNet 1.5x | 416*416 | 36.3 | 52.2 | 3.10 | 3.85 | 21.29 | **20.8** | [model](https://paddledet.bj.bcebos.com/models/picodet_lcnet_1_5x_416_coco.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_lcnet_1_5x_416_coco.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/more_config/picodet_lcnet_1_5x_416_coco.yml) | +| PicoDet-LCNet 1.5x | 640*640 | 40.6 | 57.4 | 3.10 | - | - | - | [model](https://paddledet.bj.bcebos.com/models/picodet_lcnet_1_5x_640_coco.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_lcnet_1_5x_640_coco.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/more_config/picodet_lcnet_1_5x_640_coco.yml) | +| PicoDet-R18 | 640*640 | 40.7 | 57.2 | 11.10 | - | - | - | [model](https://paddledet.bj.bcebos.com/models/picodet_r18_640_coco.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_r18_640_coco.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/more_config/picodet_r18_640_coco.yml) |
Table Notes: diff --git a/configs/picodet/legacy_model/application/layout_analysis/README.md b/configs/picodet/legacy_model/application/layout_analysis/README.md index 8bc43178b75292079457a059b865594f08a6666a..d0e70c10d1a27683ccb4bf85ec2ed744e1afa70f 100644 --- a/configs/picodet/legacy_model/application/layout_analysis/README.md +++ b/configs/picodet/legacy_model/application/layout_analysis/README.md @@ -22,7 +22,7 @@ | PicoDet-LCNet_x1_0 | 800*608 | 93.5% | [trained model](https://paddleocr.bj.bcebos.com/ppstructure/models/layout/picodet_lcnet_x1_0_layout.pdparams) | [inference model](https://paddleocr.bj.bcebos.com/ppstructure/models/layout/picodet_lcnet_x1_0_layout_infer.tar) | [config](./picodet_lcnet_x1_0_layout.yml) | | PicoDet-LCNet_x1_0 + FGD | 800*608 | 94.0% | [trained model](https://paddleocr.bj.bcebos.com/ppstructure/models/layout/picodet_lcnet_x1_0_fgd_layout.pdparams) | [inference model](https://paddleocr.bj.bcebos.com/ppstructure/models/layout/picodet_lcnet_x1_0_fgd_layout_infer.tar) | [teacher config](./picodet_lcnet_x2_5_layout.yml)|[student config](./picodet_lcnet_x1_0_layout.yml) | - [FGD蒸馏介绍](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/slim/distill/README.md) + [FGD蒸馏介绍](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/configs/slim/distill/README.md) ### 1.3 模型推理 diff --git a/configs/picodet/legacy_model/pruner/README.md b/configs/picodet/legacy_model/pruner/README.md index e62ed100d190110dbb17ba08bd6753c4585f3183..8f21306e2e6396f28b26eb02fad30662b3cc7df0 100644 --- a/configs/picodet/legacy_model/pruner/README.md +++ b/configs/picodet/legacy_model/pruner/README.md @@ -113,9 +113,9 @@ paddle_lite_opt --model_dir=inference_model/picodet_m_320_coco --valid_targets=a | Model | Input size | Sparsity | mAPval
0.5:0.95 | Size
(MB) | Latency single-thread[Lite](#latency)
(ms) | speed-up single-thread | Latency 4-thread[Lite](#latency)
(ms) | speed-up 4-thread | Download | SlimConfig | | :-------- | :--------: |:--------: | :---------------------: | :----------------: | :----------------: |:----------------: | :---------------: | :-----------------------------: | :-----------------------------: | :----------------------------------------: | | PicoDet-m-1.0 | 320*320 | 0 | 30.9 | 8.9 | 127 | 0 | 43 | 0 | [model](https://paddledet.bj.bcebos.com/models/picodet_m_320_coco.pdparams)| [log](https://paddledet.bj.bcebos.com/logs/train_picodet_m_320_coco.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.3/configs/picodet/picodet_m_320_coco.yml)| -| PicoDet-m-1.0 | 320*320 | 75% | 29.4 | 5.6 | **80** | 58% | **32** | 34% | [model](https://paddledet.bj.bcebos.com/models/slim/picodet_m_320__coco_sparse_75.pdparams)| [log](https://paddledet.bj.bcebos.com/logs/train_picodet_m_320__coco_sparse_75.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/slim/prune/picodet_m_unstructured_prune_75.yml)| +| PicoDet-m-1.0 | 320*320 | 75% | 29.4 | 5.6 | **80** | 58% | **32** | 34% | [model](https://paddledet.bj.bcebos.com/models/slim/picodet_m_320__coco_sparse_75.pdparams)| [log](https://paddledet.bj.bcebos.com/logs/train_picodet_m_320__coco_sparse_75.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/configs/slim/prune/picodet_m_unstructured_prune_75.yml)| | PicoDet-s-1.0 | 320*320 | 0 | 27.1 | 4.6 | 68 | 0 | 26 | 0 | [model](https://paddledet.bj.bcebos.com/models/picodet_s_320_coco.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_s_320_coco.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.3/configs/picodet/picodet_s_320_coco.yml)| -| PicoDet-m-1.0 | 320*320 | 85% | 27.6 | 4.1 | **65** | 96% | **27** | 59% | [model](https://paddledet.bj.bcebos.com/models/slim/picodet_m_320__coco_sparse_85.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_m_320__coco_sparse_85.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/slim/prune/picodet_m_unstructured_prune_85.yml)| +| PicoDet-m-1.0 | 320*320 | 85% | 27.6 | 4.1 | **65** | 96% | **27** | 59% | [model](https://paddledet.bj.bcebos.com/models/slim/picodet_m_320__coco_sparse_85.pdparams) | [log](https://paddledet.bj.bcebos.com/logs/train_picodet_m_320__coco_sparse_85.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/configs/slim/prune/picodet_m_unstructured_prune_85.yml)| **注意：** - 上述模型体积是**部署模型体积**，即 PaddleLite 转换得到的 *.nb 文件的体积。 diff --git a/configs/ppyolo/README.md b/configs/ppyolo/README.md index 754fdd434a6722b640e441e6b565b8593bf86004..a9566d61a92728a35675e2d861628f722556c5a6 100644 --- a/configs/ppyolo/README.md +++ b/configs/ppyolo/README.md @@ -41,25 +41,25 @@ PP-YOLO and PP-YOLOv2 improved performance and speed of YOLOv3 with following me | Model | GPU number | images/GPU | backbone | input shape | Box APval | Box APtest | V100 FP32(FPS) | V100 TensorRT FP16(FPS) | download | config | |:------------------------:|:-------:|:-------------:|:----------:| :-------:| :------------------: | :-------------------: | :------------: | :---------------------: | :------: | :------: | -| PP-YOLO | 8 | 24 | ResNet50vd | 608 | 44.8 | 45.2 | 72.9 | 155.6 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | -| PP-YOLO | 8 | 24 | ResNet50vd | 512 | 43.9 | 44.4 | 89.9 | 188.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | -| PP-YOLO | 8 | 24 | ResNet50vd | 416 | 42.1 | 42.5 | 109.1 | 215.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | -| PP-YOLO | 8 | 24 | ResNet50vd | 320 | 38.9 | 39.3 | 132.2 | 242.2 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | -| PP-YOLO_2x | 8 | 24 | ResNet50vd | 608 | 45.3 | 45.9 | 72.9 | 155.6 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_2x_coco.yml) | -| PP-YOLO_2x | 8 | 24 | ResNet50vd | 512 | 44.4 | 45.0 | 89.9 | 188.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_2x_coco.yml) | -| PP-YOLO_2x | 8 | 24 | ResNet50vd | 416 | 42.7 | 43.2 | 109.1 | 215.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_2x_coco.yml) | -| PP-YOLO_2x | 8 | 24 | ResNet50vd | 320 | 39.5 | 40.1 | 132.2 | 242.2 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_2x_coco.yml) | -| PP-YOLO | 4 | 32 | ResNet18vd | 512 | 29.2 | 29.5 | 357.1 | 657.9 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r18vd_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r18vd_coco.yml) | -| PP-YOLO | 4 | 32 | ResNet18vd | 416 | 28.6 | 28.9 | 409.8 | 719.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r18vd_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r18vd_coco.yml) | -| PP-YOLO | 4 | 32 | ResNet18vd | 320 | 26.2 | 26.4 | 480.7 | 763.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r18vd_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r18vd_coco.yml) | -| PP-YOLOv2 | 8 | 12 | ResNet50vd | 640 | 49.1 | 49.5 | 68.9 | 106.5 | [model](https://paddledet.bj.bcebos.com/models/ppyolov2_r50vd_dcn_365e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolov2_r50vd_dcn_365e_coco.yml) | -| PP-YOLOv2 | 8 | 12 | ResNet101vd | 640 | 49.7 | 50.3 | 49.5 | 87.0 | [model](https://paddledet.bj.bcebos.com/models/ppyolov2_r101vd_dcn_365e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolov2_r101vd_dcn_365e_coco.yml) | +| PP-YOLO | 8 | 24 | ResNet50vd | 608 | 44.8 | 45.2 | 72.9 | 155.6 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | +| PP-YOLO | 8 | 24 | ResNet50vd | 512 | 43.9 | 44.4 | 89.9 | 188.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | +| PP-YOLO | 8 | 24 | ResNet50vd | 416 | 42.1 | 42.5 | 109.1 | 215.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | +| PP-YOLO | 8 | 24 | ResNet50vd | 320 | 38.9 | 39.3 | 132.2 | 242.2 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | +| PP-YOLO_2x | 8 | 24 | ResNet50vd | 608 | 45.3 | 45.9 | 72.9 | 155.6 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_r50vd_dcn_2x_coco.yml) | +| PP-YOLO_2x | 8 | 24 | ResNet50vd | 512 | 44.4 | 45.0 | 89.9 | 188.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_r50vd_dcn_2x_coco.yml) | +| PP-YOLO_2x | 8 | 24 | ResNet50vd | 416 | 42.7 | 43.2 | 109.1 | 215.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_r50vd_dcn_2x_coco.yml) | +| PP-YOLO_2x | 8 | 24 | ResNet50vd | 320 | 39.5 | 40.1 | 132.2 | 242.2 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_r50vd_dcn_2x_coco.yml) | +| PP-YOLO | 4 | 32 | ResNet18vd | 512 | 29.2 | 29.5 | 357.1 | 657.9 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r18vd_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_r18vd_coco.yml) | +| PP-YOLO | 4 | 32 | ResNet18vd | 416 | 28.6 | 28.9 | 409.8 | 719.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r18vd_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_r18vd_coco.yml) | +| PP-YOLO | 4 | 32 | ResNet18vd | 320 | 26.2 | 26.4 | 480.7 | 763.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r18vd_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_r18vd_coco.yml) | +| PP-YOLOv2 | 8 | 12 | ResNet50vd | 640 | 49.1 | 49.5 | 68.9 | 106.5 | [model](https://paddledet.bj.bcebos.com/models/ppyolov2_r50vd_dcn_365e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolov2_r50vd_dcn_365e_coco.yml) | +| PP-YOLOv2 | 8 | 12 | ResNet101vd | 640 | 49.7 | 50.3 | 49.5 | 87.0 | [model](https://paddledet.bj.bcebos.com/models/ppyolov2_r101vd_dcn_365e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolov2_r101vd_dcn_365e_coco.yml) | **Notes:** - PP-YOLO is trained on COCO train2017 dataset and evaluated on val2017 & test-dev2017 dataset，Box APtest is evaluation results of `mAP(IoU=0.5:0.95)`. -- PP-YOLO used 8 GPUs for training and mini-batch size as 24 on each GPU, if GPU number and mini-batch size is changed, learning rate and iteration times should be adjusted according [FAQ](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/docs/tutorials/FAQ). +- PP-YOLO used 8 GPUs for training and mini-batch size as 24 on each GPU, if GPU number and mini-batch size is changed, learning rate and iteration times should be adjusted according [FAQ](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/docs/tutorials/FAQ). - PP-YOLO inference speed is tesed on single Tesla V100 with batch size as 1, CUDA 10.2, CUDNN 7.5.1, TensorRT 5.1.2.2 in TensorRT mode. - PP-YOLO FP32 inference speed testing uses inference model exported by `tools/export_model.py` and benchmarked by running `depoly/python/infer.py` with `--run_benchmark`. All testing results do not contains the time cost of data reading and post-processing(NMS), which is same as [YOLOv4(AlexyAB)](https://github.com/AlexeyAB/darknet) in testing method. - TensorRT FP16 inference speed testing exclude the time cost of bounding-box decoding(`yolo_box`) part comparing with FP32 testing above, which means that data reading, bounding-box decoding and post-processing(NMS) is excluded(test method same as [YOLOv4(AlexyAB)](https://github.com/AlexeyAB/darknet) too) @@ -69,26 +69,26 @@ PP-YOLO and PP-YOLOv2 improved performance and speed of YOLOv3 with following me | Model | GPU number | images/GPU | Model Size | input shape | Box APval | Box AP50val | Kirin 990 1xCore(FPS) | download | config | |:----------------------------:|:-------:|:-------------:|:----------:| :-------:| :------------------: | :--------------------: | :--------------------: | :------: | :------: | -| PP-YOLO_MobileNetV3_large | 4 | 32 | 28MB | 320 | 23.2 | 42.6 | 14.1 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_large_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_mbv3_large_coco.yml) | -| PP-YOLO_MobileNetV3_small | 4 | 32 | 16MB | 320 | 17.2 | 33.8 | 21.5 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_small_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_mbv3_small_coco.yml) | +| PP-YOLO_MobileNetV3_large | 4 | 32 | 28MB | 320 | 23.2 | 42.6 | 14.1 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_large_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_mbv3_large_coco.yml) | +| PP-YOLO_MobileNetV3_small | 4 | 32 | 16MB | 320 | 17.2 | 33.8 | 21.5 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_small_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_mbv3_small_coco.yml) | **Notes:** - PP-YOLO_MobileNetV3 is trained on COCO train2017 datast and evaluated on val2017 dataset，Box APval is evaluation results of `mAP(IoU=0.5:0.95)`, Box APval is evaluation results of `mAP(IoU=0.5)`. -- PP-YOLO_MobileNetV3 used 4 GPUs for training and mini-batch size as 32 on each GPU, if GPU number and mini-batch size is changed, learning rate and iteration times should be adjusted according [FAQ](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/docs/tutorials/FAQ). +- PP-YOLO_MobileNetV3 used 4 GPUs for training and mini-batch size as 32 on each GPU, if GPU number and mini-batch size is changed, learning rate and iteration times should be adjusted according [FAQ](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/docs/tutorials/FAQ). - PP-YOLO_MobileNetV3 inference speed is tested on Kirin 990 with 1 thread. ### PP-YOLO tiny | Model | GPU number | images/GPU | Model Size | Post Quant Model Size | input shape | Box APval | Kirin 990 4xCore(FPS) | download | config | post quant model | |:----------------------------:|:-------:|:-------------:|:----------:| :-------------------: | :---------: | :------------------: | :-------------------: | :------: | :----: | :--------------: | -| PP-YOLO tiny | 8 | 32 | 4.2MB | **1.3M** | 320 | 20.6 | 92.3 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_tiny_650e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_tiny_650e_coco.yml) | [inference model](https://paddledet.bj.bcebos.com/models/ppyolo_tiny_quant.tar) | -| PP-YOLO tiny | 8 | 32 | 4.2MB | **1.3M** | 416 | 22.7 | 65.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_tiny_650e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_tiny_650e_coco.yml) | [inference model](https://paddledet.bj.bcebos.com/models/ppyolo_tiny_quant.tar) | +| PP-YOLO tiny | 8 | 32 | 4.2MB | **1.3M** | 320 | 20.6 | 92.3 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_tiny_650e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_tiny_650e_coco.yml) | [inference model](https://paddledet.bj.bcebos.com/models/ppyolo_tiny_quant.tar) | +| PP-YOLO tiny | 8 | 32 | 4.2MB | **1.3M** | 416 | 22.7 | 65.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_tiny_650e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_tiny_650e_coco.yml) | [inference model](https://paddledet.bj.bcebos.com/models/ppyolo_tiny_quant.tar) | **Notes:** - PP-YOLO-tiny is trained on COCO train2017 datast and evaluated on val2017 dataset，Box APval is evaluation results of `mAP(IoU=0.5:0.95)`, Box APval is evaluation results of `mAP(IoU=0.5)`. -- PP-YOLO-tiny used 8 GPUs for training and mini-batch size as 32 on each GPU, if GPU number and mini-batch size is changed, learning rate and iteration times should be adjusted according [FAQ](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/docs/tutorials/FAQ/README.md). +- PP-YOLO-tiny used 8 GPUs for training and mini-batch size as 32 on each GPU, if GPU number and mini-batch size is changed, learning rate and iteration times should be adjusted according [FAQ](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/docs/tutorials/FAQ/README.md). - PP-YOLO-tiny inference speed is tested on Kirin 990 with 4 threads by arm8 - we alse provide PP-YOLO-tiny post quant inference model, which can compress model to **1.3MB** with nearly no inference on inference speed and performance @@ -98,9 +98,9 @@ PP-YOLO trained on Pascal VOC dataset as follows: | Model | GPU number | images/GPU | backbone | input shape | Box AP50val | download | config | |:------------------:|:----------:|:----------:|:----------:| :----------:| :--------------------: | :------: | :-----: | -| PP-YOLO | 8 | 12 | ResNet50vd | 608 | 84.9 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_voc.yml) | -| PP-YOLO | 8 | 12 | ResNet50vd | 416 | 84.3 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_voc.yml) | -| PP-YOLO | 8 | 12 | ResNet50vd | 320 | 82.2 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_voc.yml) | +| PP-YOLO | 8 | 12 | ResNet50vd | 608 | 84.9 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_r50vd_dcn_voc.yml) | +| PP-YOLO | 8 | 12 | ResNet50vd | 416 | 84.3 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_r50vd_dcn_voc.yml) | +| PP-YOLO | 8 | 12 | ResNet50vd | 320 | 82.2 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_r50vd_dcn_voc.yml) | ## Getting Start @@ -212,7 +212,7 @@ Optimizing method and ablation experiments of PP-YOLO compared with YOLOv3. - Performance and inference spedd are measure with input shape as 608 - All models are trained on COCO train2017 datast and evaluated on val2017 & test-dev2017 dataset，`Box AP` is evaluation results as `mAP(IoU=0.5:0.95)`. - Inference speed is tested on single Tesla V100 with batch size as 1 following test method and environment configuration in benchmark above. -- [YOLOv3-DarkNet53](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_darknet53_270e_coco.yml) with mAP as 39.0 is optimized YOLOv3 model in PaddleDetection，see [YOLOv3](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/yolov3/README.md) for details. +- [YOLOv3-DarkNet53](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_darknet53_270e_coco.yml) with mAP as 39.0 is optimized YOLOv3 model in PaddleDetection，see [YOLOv3](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/configs/yolov3/README.md) for details. ## Citation diff --git a/configs/ppyolo/README_cn.md b/configs/ppyolo/README_cn.md index f4b4c19af515977a365f07203cc5fbea83b49692..b5be59ee92ddb1792494b219f7839ed766ef5d35 100644 --- a/configs/ppyolo/README_cn.md +++ b/configs/ppyolo/README_cn.md @@ -41,24 +41,24 @@ PP-YOLO和PP-YOLOv2从如下方面优化和提升YOLOv3模型的精度和速度 | 模型 | GPU个数 | 每GPU图片个数 | 骨干网络 | 输入尺寸 | Box APval | Box APtest | V100 FP32(FPS) | V100 TensorRT FP16(FPS) | 模型下载 | 配置文件 | |:------------------------:|:-------:|:-------------:|:----------:| :-------:| :------------------: | :-------------------: | :------------: | :---------------------: | :------: | :------: | -| PP-YOLO | 8 | 24 | ResNet50vd | 608 | 44.8 | 45.2 | 72.9 | 155.6 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | -| PP-YOLO | 8 | 24 | ResNet50vd | 512 | 43.9 | 44.4 | 89.9 | 188.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | -| PP-YOLO | 8 | 24 | ResNet50vd | 416 | 42.1 | 42.5 | 109.1 | 215.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | -| PP-YOLO | 8 | 24 | ResNet50vd | 320 | 38.9 | 39.3 | 132.2 | 242.2 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | -| PP-YOLO_2x | 8 | 24 | ResNet50vd | 608 | 45.3 | 45.9 | 72.9 | 155.6 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_2x_coco.yml) | -| PP-YOLO_2x | 8 | 24 | ResNet50vd | 512 | 44.4 | 45.0 | 89.9 | 188.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_2x_coco.yml) | -| PP-YOLO_2x | 8 | 24 | ResNet50vd | 416 | 42.7 | 43.2 | 109.1 | 215.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_2x_coco.yml) | -| PP-YOLO_2x | 8 | 24 | ResNet50vd | 320 | 39.5 | 40.1 | 132.2 | 242.2 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_2x_coco.yml) | -| PP-YOLO | 4 | 32 | ResNet18vd | 512 | 29.2 | 29.5 | 357.1 | 657.9 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r18vd_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r18vd_coco.yml) | -| PP-YOLO | 4 | 32 | ResNet18vd | 416 | 28.6 | 28.9 | 409.8 | 719.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r18vd_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r18vd_coco.yml) | -| PP-YOLO | 4 | 32 | ResNet18vd | 320 | 26.2 | 26.4 | 480.7 | 763.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r18vd_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r18vd_coco.yml) | -| PP-YOLOv2 | 8 | 12 | ResNet50vd | 640 | 49.1 | 49.5 | 68.9 | 106.5 | [model](https://paddledet.bj.bcebos.com/models/ppyolov2_r50vd_dcn_365e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolov2_r50vd_dcn_365e_coco.yml) | -| PP-YOLOv2 | 8 | 12 | ResNet101vd | 640 | 49.7 | 50.3 | 49.5 | 87.0 | [model](https://paddledet.bj.bcebos.com/models/ppyolov2_r101vd_dcn_365e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolov2_r101vd_dcn_365e_coco.yml) | +| PP-YOLO | 8 | 24 | ResNet50vd | 608 | 44.8 | 45.2 | 72.9 | 155.6 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | +| PP-YOLO | 8 | 24 | ResNet50vd | 512 | 43.9 | 44.4 | 89.9 | 188.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | +| PP-YOLO | 8 | 24 | ResNet50vd | 416 | 42.1 | 42.5 | 109.1 | 215.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | +| PP-YOLO | 8 | 24 | ResNet50vd | 320 | 38.9 | 39.3 | 132.2 | 242.2 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | +| PP-YOLO_2x | 8 | 24 | ResNet50vd | 608 | 45.3 | 45.9 | 72.9 | 155.6 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_r50vd_dcn_2x_coco.yml) | +| PP-YOLO_2x | 8 | 24 | ResNet50vd | 512 | 44.4 | 45.0 | 89.9 | 188.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_r50vd_dcn_2x_coco.yml) | +| PP-YOLO_2x | 8 | 24 | ResNet50vd | 416 | 42.7 | 43.2 | 109.1 | 215.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_r50vd_dcn_2x_coco.yml) | +| PP-YOLO_2x | 8 | 24 | ResNet50vd | 320 | 39.5 | 40.1 | 132.2 | 242.2 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_r50vd_dcn_2x_coco.yml) | +| PP-YOLO | 4 | 32 | ResNet18vd | 512 | 29.2 | 29.5 | 357.1 | 657.9 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r18vd_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_r18vd_coco.yml) | +| PP-YOLO | 4 | 32 | ResNet18vd | 416 | 28.6 | 28.9 | 409.8 | 719.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r18vd_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_r18vd_coco.yml) | +| PP-YOLO | 4 | 32 | ResNet18vd | 320 | 26.2 | 26.4 | 480.7 | 763.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r18vd_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_r18vd_coco.yml) | +| PP-YOLOv2 | 8 | 12 | ResNet50vd | 640 | 49.1 | 49.5 | 68.9 | 106.5 | [model](https://paddledet.bj.bcebos.com/models/ppyolov2_r50vd_dcn_365e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolov2_r50vd_dcn_365e_coco.yml) | +| PP-YOLOv2 | 8 | 12 | ResNet101vd | 640 | 49.7 | 50.3 | 49.5 | 87.0 | [model](https://paddledet.bj.bcebos.com/models/ppyolov2_r101vd_dcn_365e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolov2_r101vd_dcn_365e_coco.yml) | **注意:** - PP-YOLO模型使用COCO数据集中train2017作为训练集，使用val2017和test-dev2017作为测试集，Box APtest为`mAP(IoU=0.5:0.95)`评估结果。 -- PP-YOLO模型训练过程中使用8 GPUs，每GPU batch size为24进行训练，如训练GPU数和batch size不使用上述配置，须参考[FAQ](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/docs/tutorials/FAQ)调整学习率和迭代次数。 +- PP-YOLO模型训练过程中使用8 GPUs，每GPU batch size为24进行训练，如训练GPU数和batch size不使用上述配置，须参考[FAQ](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/docs/tutorials/FAQ)调整学习率和迭代次数。 - PP-YOLO模型推理速度测试采用单卡V100，batch size=1进行测试，使用CUDA 10.2, CUDNN 7.5.1，TensorRT推理速度测试使用TensorRT 5.1.2.2。 - PP-YOLO模型FP32的推理速度测试数据为使用`tools/export_model.py`脚本导出模型后，使用`deploy/python/infer.py`脚本中的`--run_benchnark`参数使用Paddle预测库进行推理速度benchmark测试结果, 且测试的均为不包含数据预处理和模型输出后处理(NMS)的数据(与[YOLOv4(AlexyAB)](https://github.com/AlexeyAB/darknet)测试方法一致)。 - TensorRT FP16的速度测试相比于FP32去除了`yolo_box`(bbox解码)部分耗时，即不包含数据预处理，bbox解码和NMS(与[YOLOv4(AlexyAB)](https://github.com/AlexeyAB/darknet)测试方法一致)。 @@ -67,22 +67,22 @@ PP-YOLO和PP-YOLOv2从如下方面优化和提升YOLOv3模型的精度和速度 | 模型 | GPU个数 | 每GPU图片个数 | 模型体积 | 输入尺寸 | Box APval | Box AP50val | Kirin 990 1xCore (FPS) | 模型下载 | 配置文件 | |:----------------------------:|:-------:|:-------------:|:----------:| :-------:| :------------------: | :--------------------: | :--------------------: | :------: | :------: | -| PP-YOLO_MobileNetV3_large | 4 | 32 | 28MB | 320 | 23.2 | 42.6 | 14.1 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_large_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_mbv3_large_coco.yml) | -| PP-YOLO_MobileNetV3_small | 4 | 32 | 16MB | 320 | 17.2 | 33.8 | 21.5 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_small_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_mbv3_small_coco.yml) | +| PP-YOLO_MobileNetV3_large | 4 | 32 | 28MB | 320 | 23.2 | 42.6 | 14.1 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_large_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_mbv3_large_coco.yml) | +| PP-YOLO_MobileNetV3_small | 4 | 32 | 16MB | 320 | 17.2 | 33.8 | 21.5 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_small_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_mbv3_small_coco.yml) | - PP-YOLO_MobileNetV3 模型使用COCO数据集中train2017作为训练集，使用val2017作为测试集，Box APval为`mAP(IoU=0.5:0.95)`评估结果, Box AP50val为`mAP(IoU=0.5)`评估结果。 -- PP-YOLO_MobileNetV3 模型训练过程中使用4GPU，每GPU batch size为32进行训练，如训练GPU数和batch size不使用上述配置，须参考[FAQ](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/docs/tutorials/FAQ)调整学习率和迭代次数。 +- PP-YOLO_MobileNetV3 模型训练过程中使用4GPU，每GPU batch size为32进行训练，如训练GPU数和batch size不使用上述配置，须参考[FAQ](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/docs/tutorials/FAQ)调整学习率和迭代次数。 - PP-YOLO_MobileNetV3 模型推理速度测试环境配置为麒麟990芯片单线程。 ### PP-YOLO tiny模型 | 模型 | GPU 个数 | 每GPU图片个数 | 模型体积 | 后量化模型体积 | 输入尺寸 | Box APval | Kirin 990 1xCore (FPS) | 模型下载 | 配置文件 | 量化后模型 | |:----------------------------:|:----------:|:-------------:| :--------: | :------------: | :----------:| :------------------: | :--------------------: | :------: | :------: | :--------: | -| PP-YOLO tiny | 8 | 32 | 4.2MB | **1.3M** | 320 | 20.6 | 92.3 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_tiny_650e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_tiny_650e_coco.yml) | [预测模型](https://paddledet.bj.bcebos.com/models/ppyolo_tiny_quant.tar) | -| PP-YOLO tiny | 8 | 32 | 4.2MB | **1.3M** | 416 | 22.7 | 65.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_tiny_650e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_tiny_650e_coco.yml) | [预测模型](https://paddledet.bj.bcebos.com/models/ppyolo_tiny_quant.tar) | +| PP-YOLO tiny | 8 | 32 | 4.2MB | **1.3M** | 320 | 20.6 | 92.3 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_tiny_650e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_tiny_650e_coco.yml) | [预测模型](https://paddledet.bj.bcebos.com/models/ppyolo_tiny_quant.tar) | +| PP-YOLO tiny | 8 | 32 | 4.2MB | **1.3M** | 416 | 22.7 | 65.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_tiny_650e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_tiny_650e_coco.yml) | [预测模型](https://paddledet.bj.bcebos.com/models/ppyolo_tiny_quant.tar) | - PP-YOLO-tiny 模型使用COCO数据集中train2017作为训练集，使用val2017作为测试集，Box APval为`mAP(IoU=0.5:0.95)`评估结果, Box AP50val为`mAP(IoU=0.5)`评估结果。 -- PP-YOLO-tiny 模型训练过程中使用8GPU，每GPU batch size为32进行训练，如训练GPU数和batch size不使用上述配置，须参考[FAQ](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/docs/tutorials/FAQ/README.md)调整学习率和迭代次数。 +- PP-YOLO-tiny 模型训练过程中使用8GPU，每GPU batch size为32进行训练，如训练GPU数和batch size不使用上述配置，须参考[FAQ](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/docs/tutorials/FAQ/README.md)调整学习率和迭代次数。 - PP-YOLO-tiny 模型推理速度测试环境配置为麒麟990芯片4线程，arm8架构。 - 我们也提供的PP-YOLO-tiny的后量化压缩模型，将模型体积压缩到**1.3M**，对精度和预测速度基本无影响 @@ -92,9 +92,9 @@ PP-YOLO在Pascal VOC数据集上训练模型如下: | 模型 | GPU个数 | 每GPU图片个数 | 骨干网络 | 输入尺寸 | Box AP50val | 模型下载 | 配置文件 | |:------------------:|:-------:|:-------------:|:----------:| :----------:| :--------------------: | :------: | :-----: | -| PP-YOLO | 8 | 12 | ResNet50vd | 608 | 84.9 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_voc.yml) | -| PP-YOLO | 8 | 12 | ResNet50vd | 416 | 84.3 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_voc.yml) | -| PP-YOLO | 8 | 12 | ResNet50vd | 320 | 82.2 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_voc.yml) | +| PP-YOLO | 8 | 12 | ResNet50vd | 608 | 84.9 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_r50vd_dcn_voc.yml) | +| PP-YOLO | 8 | 12 | ResNet50vd | 416 | 84.3 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_r50vd_dcn_voc.yml) | +| PP-YOLO | 8 | 12 | ResNet50vd | 320 | 82.2 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_r50vd_dcn_voc.yml) | ## 使用说明 @@ -205,7 +205,7 @@ PP-YOLO模型相对于YOLOv3模型优化项消融实验数据如下表所示。 - 精度与推理速度数据均为使用输入图像尺寸为608的测试结果 - Box AP为在COCO train2017数据集训练，val2017和test-dev2017数据集上评估`mAP(IoU=0.5:0.95)`数据 - 推理速度为单卡V100上，batch size=1, 使用上述benchmark测试方法的测试结果，测试环境配置为CUDA 10.2，CUDNN 7.5.1 -- [YOLOv3-DarkNet53](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_darknet53_270e_coco.yml)精度38.9为PaddleDetection优化后的YOLOv3模型，可参见[YOLOv3](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/yolov3/README.md) +- [YOLOv3-DarkNet53](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_darknet53_270e_coco.yml)精度38.9为PaddleDetection优化后的YOLOv3模型，可参见[YOLOv3](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/configs/yolov3/README.md) ## 引用 diff --git a/configs/rcnn_enhance/README.md b/configs/rcnn_enhance/README.md index 974935b379e5569abfc001e26d3b3b61cb1ecd3b..fc820c4266dccdcbb552d2fa75a2f9e145f421eb 100644 --- a/configs/rcnn_enhance/README.md +++ b/configs/rcnn_enhance/README.md @@ -9,4 +9,4 @@ | 骨架网络 | 网络类型 | 每张GPU图片个数 | 学习率策略 |推理时间(fps) | Box AP | Mask AP | 下载 | 配置文件 | | :---------------------- | :-------------: | :-------: | :-----: | :------------: | :----: | :-----: | :-------------: | :-----: | -| ResNet50-vd-FPN-Dcnv2 | Faster | 2 | 3x | 61.425 | 41.5 | - | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_enhance_3x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/rcnn_enhance/faster_rcnn_enhance_3x_coco.yml) | +| ResNet50-vd-FPN-Dcnv2 | Faster | 2 | 3x | 61.425 | 41.5 | - | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_enhance_3x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/rcnn_enhance/faster_rcnn_enhance_3x_coco.yml) | diff --git a/configs/rcnn_enhance/README_en.md b/configs/rcnn_enhance/README_en.md index 2f0bdc4c4be37a1cbc68a64370942b3b98296514..1d09cf6bd01bda9abe102ccd7282e4e411d7ae55 100644 --- a/configs/rcnn_enhance/README_en.md +++ b/configs/rcnn_enhance/README_en.md @@ -9,4 +9,4 @@ | Backbone | Network type | Number of images per GPU | Learning rate strategy | Inferring time(fps) | Box AP | Mask AP | Download | Configuration File | | :-------------------- | :----------: | :----------------------: | :--------------------: | :-----------------: | :----: | :-----: | :---------------------------------------------------------------------------------: | :-------------------------------------------------------------------------------------------------------------------------------------: | -| ResNet50-vd-FPN-Dcnv2 | Faster | 2 | 3x | 61.425 | 41.5 | - | [link](https://paddledet.bj.bcebos.com/models/faster_rcnn_enhance_3x_coco.pdparams) | [Configuration File](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/rcnn_enhance/faster_rcnn_enhance_3x_coco.yml) | +| ResNet50-vd-FPN-Dcnv2 | Faster | 2 | 3x | 61.425 | 41.5 | - | [link](https://paddledet.bj.bcebos.com/models/faster_rcnn_enhance_3x_coco.pdparams) | [Configuration File](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/rcnn_enhance/faster_rcnn_enhance_3x_coco.yml) | diff --git a/configs/res2net/README.md b/configs/res2net/README.md index 7f03c240fef60329057685b1923393cec17c694b..c44b7e75cb0b7df9a2cdb6d1455fe41d47f60b38 100644 --- a/configs/res2net/README.md +++ b/configs/res2net/README.md @@ -30,8 +30,8 @@ | Backbone | Type | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download | Configs | | :---------------------- | :------------- | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: | :-----: | -| Res2Net50-FPN | Faster | 2 | 1x | - | 40.6 | - | [model](https://paddledet.bj.bcebos.com/models/faster_rcnn_res2net50_vb_26w_4s_fpn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/res2net/faster_rcnn_res2net50_vb_26w_4s_fpn_1x_coco.yml) | -| Res2Net50-FPN | Mask | 2 | 2x | - | 42.4 | 38.1 | [model](https://paddledet.bj.bcebos.com/models/mask_rcnn_res2net50_vb_26w_4s_fpn_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/res2net/mask_rcnn_res2net50_vb_26w_4s_fpn_2x_coco.yml) | -| Res2Net50-vd-FPN | Mask | 2 | 2x | - | 42.6 | 38.1 | [model](https://paddledet.bj.bcebos.com/models/mask_rcnn_res2net50_vd_26w_4s_fpn_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/res2net/mask_rcnn_res2net50_vd_26w_4s_fpn_2x_coco.yml) | +| Res2Net50-FPN | Faster | 2 | 1x | - | 40.6 | - | [model](https://paddledet.bj.bcebos.com/models/faster_rcnn_res2net50_vb_26w_4s_fpn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/configs/res2net/faster_rcnn_res2net50_vb_26w_4s_fpn_1x_coco.yml) | +| Res2Net50-FPN | Mask | 2 | 2x | - | 42.4 | 38.1 | [model](https://paddledet.bj.bcebos.com/models/mask_rcnn_res2net50_vb_26w_4s_fpn_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/configs/res2net/mask_rcnn_res2net50_vb_26w_4s_fpn_2x_coco.yml) | +| Res2Net50-vd-FPN | Mask | 2 | 2x | - | 42.6 | 38.1 | [model](https://paddledet.bj.bcebos.com/models/mask_rcnn_res2net50_vd_26w_4s_fpn_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/configs/res2net/mask_rcnn_res2net50_vd_26w_4s_fpn_2x_coco.yml) | Note: all the above models are trained with 8 gpus. diff --git a/configs/rotate/README.md b/configs/rotate/README.md index 72d52014f066fd7456906b7345d22f87a3b882f4..0163208ed96caefbab92e9ea9c7bac418e480f93 100644 --- a/configs/rotate/README.md +++ b/configs/rotate/README.md @@ -15,7 +15,7 @@ | 模型 | mAP | 学习率策略 | 角度表示 | 数据增广 | GPU数目 | 每GPU图片数目 | 模型下载 | 配置文件 | |:---:|:----:|:---------:|:-----:|:--------:|:-----:|:------------:|:-------:|:------:| -| [S2ANet](./s2anet/README.md) | 74.0 | 2x | le135 | - | 4 | 2 | [model](https://paddledet.bj.bcebos.com/models/s2anet_alignconv_2x_dota.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/dota/s2anet_alignconv_2x_dota.yml) | +| [S2ANet](./s2anet/README.md) | 74.0 | 2x | le135 | - | 4 | 2 | [model](https://paddledet.bj.bcebos.com/models/s2anet_alignconv_2x_dota.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/dota/s2anet_alignconv_2x_dota.yml) | **注意:** diff --git a/configs/rotate/README_en.md b/configs/rotate/README_en.md index a91f66a9d61c576070b954b312676aea54a2d4ec..dfd0a980d37adad6a46cfd0785c51258630691bb 100644 --- a/configs/rotate/README_en.md +++ b/configs/rotate/README_en.md @@ -14,7 +14,7 @@ Rotated object detection is used to detect rectangular bounding boxes with angle ## Model Zoo | Model | mAP | Lr Scheduler | Angle | Aug | GPU Number | images/GPU | download | config | |:---:|:----:|:---------:|:-----:|:--------:|:-----:|:------------:|:-------:|:------:| -| [S2ANet](./s2anet/README.md) | 74.0 | 2x | le135 | - | 4 | 2 | [model](https://paddledet.bj.bcebos.com/models/s2anet_alignconv_2x_dota.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/dota/s2anet_alignconv_2x_dota.yml) | +| [S2ANet](./s2anet/README.md) | 74.0 | 2x | le135 | - | 4 | 2 | [model](https://paddledet.bj.bcebos.com/models/s2anet_alignconv_2x_dota.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/dota/s2anet_alignconv_2x_dota.yml) | **Notes:** diff --git a/configs/rotate/s2anet/README.md b/configs/rotate/s2anet/README.md index c76364d8e2b8158638bdca393f4f4a8864759c2b..37a5b947291045037650a5d655af2656575b3db7 100644 --- a/configs/rotate/s2anet/README.md +++ b/configs/rotate/s2anet/README.md @@ -63,8 +63,8 @@ zip -r submit.zip submit | 模型 | Conv类型 | mAP | 模型下载 | 配置文件 | |:-----------:|:----------:|:--------:| :----------:| :---------: | -| S2ANet | Conv | 71.42 | [model](https://paddledet.bj.bcebos.com/models/s2anet_conv_2x_dota.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/rotate/s2anet/s2anet_conv_2x_dota.yml) | -| S2ANet | AlignConv | 74.0 | [model](https://paddledet.bj.bcebos.com/models/s2anet_alignconv_2x_dota.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/rotate/s2anet/s2anet_alignconv_2x_dota.yml) | +| S2ANet | Conv | 71.42 | [model](https://paddledet.bj.bcebos.com/models/s2anet_conv_2x_dota.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/rotate/s2anet/s2anet_conv_2x_dota.yml) | +| S2ANet | AlignConv | 74.0 | [model](https://paddledet.bj.bcebos.com/models/s2anet_alignconv_2x_dota.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/rotate/s2anet/s2anet_alignconv_2x_dota.yml) | **注意：** 这里使用`multiclass_nms`，与原作者使用nms略有不同。 diff --git a/configs/rotate/s2anet/README_en.md b/configs/rotate/s2anet/README_en.md index 70da7660b8b4aca16cdce5f9f8acc1ab4bc1f17b..09d2997e3ab5fd0c017f22d8a95c619ba5e009b9 100644 --- a/configs/rotate/s2anet/README_en.md +++ b/configs/rotate/s2anet/README_en.md @@ -72,8 +72,8 @@ zip -r submit.zip submit | Model | Conv Type | mAP | Model Download | Configuration File | |:-----------:|:----------:|:--------:| :----------:| :---------: | -| S2ANet | Conv | 71.42 | [model](https://paddledet.bj.bcebos.com/models/s2anet_conv_2x_dota.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/rotate/s2anet/s2anet_conv_2x_dota.yml) | -| S2ANet | AlignConv | 74.0 | [model](https://paddledet.bj.bcebos.com/models/s2anet_alignconv_2x_dota.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/rotate/s2anet/s2anet_alignconv_2x_dota.yml) | +| S2ANet | Conv | 71.42 | [model](https://paddledet.bj.bcebos.com/models/s2anet_conv_2x_dota.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/rotate/s2anet/s2anet_conv_2x_dota.yml) | +| S2ANet | AlignConv | 74.0 | [model](https://paddledet.bj.bcebos.com/models/s2anet_alignconv_2x_dota.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/rotate/s2anet/s2anet_alignconv_2x_dota.yml) | **Attention:** `multiclass_nms` is used here, which is slightly different from the original author's use of NMS. diff --git a/configs/slim/README.md b/configs/slim/README.md index 4eabd73b570dd3d971d0625c3e138895778719b5..8a9ba38f60f06fc0bc1853aece1925f50cb413b3 100755 --- a/configs/slim/README.md +++ b/configs/slim/README.md @@ -103,18 +103,18 @@ python tools/export_model.py -c configs/{MODEL.yml} --slim_config configs/slim/{ | 模型 | 压缩策略 | GFLOPs | 模型体积(MB) | 输入尺寸 | 预测时延(SD855) | Box AP | 下载 | 模型配置文件 | 压缩算法配置文件 | | :---------: | :-------: | :------------: |:-------------: | :------: | :-------------: | :------: | :-----------------------------------------------------: |:-------------: | :------: | -| YOLOv3-MobileNetV1 | baseline | 24.13 | 93 | 608 | 332.0ms | 75.1 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_voc.yml) | - | -| YOLOv3-MobileNetV1 | 剪裁-l1_norm(sensity) | 15.78(-34.49%) | 66(-29%) | 608 | - | 78.4(+3.3) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_voc_prune_l1_norm.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_voc.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/prune/yolov3_prune_l1_norm.yml) | +| YOLOv3-MobileNetV1 | baseline | 24.13 | 93 | 608 | 332.0ms | 75.1 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v1_270e_voc.yml) | - | +| YOLOv3-MobileNetV1 | 剪裁-l1_norm(sensity) | 15.78(-34.49%) | 66(-29%) | 608 | - | 78.4(+3.3) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_voc_prune_l1_norm.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v1_270e_voc.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/slim/prune/yolov3_prune_l1_norm.yml) | #### COCO上benchmark | 模型 | 压缩策略 | GFLOPs | 模型体积(MB) | 输入尺寸 | 预测时延(SD855) | Box AP | 下载 | 模型配置文件 | 压缩算法配置文件 | | :---------: | :-------: | :------------: |:-------------: | :------: | :-------------: | :------: | :-----------------------------------------------------: |:-------------: | :------: | -| PP-YOLO-MobileNetV3_large | baseline | -- | 18.5 | 608 | 25.1ms | 23.2 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_large_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_mbv3_large_coco.yml) | - | -| PP-YOLO-MobileNetV3_large | 剪裁-FPGM | -37% | 12.6 | 608 | - | 22.3 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolo_mbv3_large_prune_fpgm.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_mbv3_large_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/prune/ppyolo_mbv3_large_prune_fpgm.yml) | -| YOLOv3-DarkNet53 | baseline | -- | 238.2 | 608 | - | 39.0 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_large_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_darknet53_270e_coco.yml) | - | -| YOLOv3-DarkNet53 | 剪裁-FPGM | -24% | - | 608 | - | 37.6 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_darknet_prune_fpgm.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_darknet53_270e_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/prune/yolov3_darknet_prune_fpgm.yml) | -| PP-YOLO_R50vd | baseline | -- | 183.3 | 608 | - | 44.8 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | - | -| PP-YOLO_R50vd | 剪裁-FPGM | -35% | - | 608 | - | 42.1 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolo_r50vd_prune_fpgm.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/prune/ppyolo_r50vd_prune_fpgm.yml) | +| PP-YOLO-MobileNetV3_large | baseline | -- | 18.5 | 608 | 25.1ms | 23.2 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_large_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_mbv3_large_coco.yml) | - | +| PP-YOLO-MobileNetV3_large | 剪裁-FPGM | -37% | 12.6 | 608 | - | 22.3 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolo_mbv3_large_prune_fpgm.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_mbv3_large_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/slim/prune/ppyolo_mbv3_large_prune_fpgm.yml) | +| YOLOv3-DarkNet53 | baseline | -- | 238.2 | 608 | - | 39.0 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_large_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_darknet53_270e_coco.yml) | - | +| YOLOv3-DarkNet53 | 剪裁-FPGM | -24% | - | 608 | - | 37.6 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_darknet_prune_fpgm.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_darknet53_270e_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/slim/prune/yolov3_darknet_prune_fpgm.yml) | +| PP-YOLO_R50vd | baseline | -- | 183.3 | 608 | - | 44.8 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | - | +| PP-YOLO_R50vd | 剪裁-FPGM | -35% | - | 608 | - | 42.1 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolo_r50vd_prune_fpgm.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/slim/prune/ppyolo_r50vd_prune_fpgm.yml) | 说明： - 目前剪裁除RCNN系列模型外，其余模型均已支持。 @@ -126,24 +126,24 @@ python tools/export_model.py -c configs/{MODEL.yml} --slim_config configs/slim/{ | 模型 | 压缩策略 | 输入尺寸 | 模型体积(MB) | 预测时延(V100) | 预测时延(SD855) | Box AP | 下载 | Inference模型下载 | 模型配置文件 | 压缩算法配置文件 | | ------------------ | ------------ | -------- | :---------: | :---------: |:---------: | :---------: | :----------------------------------------------: | :----------------------------------------------: |:------------------------------------------: | :------------------------------------: | -| PP-YOLOE-l | baseline | 640 | - | 11.2ms(trt_fp32) | 7.7ms(trt_fp16) | -- | 50.9 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyoloe_crn_l_300e_coco.pdparams) | - | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyoloe/ppyoloe_crn_l_300e_coco.yml) | - | -| PP-YOLOE-l | 普通在线量化 | 640 | - | 6.7ms(trt_int8) | -- | 48.8 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyoloe_l_coco_qat.pdparams) | - | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyoloe/ppyoloe_crn_l_300e_coco.yml) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/quant/ppyoloe_l_qat.yml) | -| PP-YOLOv2_R50vd | baseline | 640 | 208.6 | 19.1ms | -- | 49.1 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyolov2_r50vd_dcn_365e_coco.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolov2_r50vd_dcn_365e_coco.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | - | -| PP-YOLOv2_R50vd | PACT在线量化 | 640 | -- | 17.3ms | -- | 48.1 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolov2_r50vd_dcn_qat.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolov2_r50vd_dcn_qat.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/quant/ppyolov2_r50vd_dcn_qat.yml) | -| PP-YOLO_R50vd | baseline | 608 | 183.3 | 17.4ms | -- | 44.8 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolo_r50vd_dcn_1x_coco.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | - | -| PP-YOLO_R50vd | PACT在线量化 | 608 | 67.3 | 13.8ms | -- | 44.3 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolo_r50vd_qat_pact.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolo_r50vd_qat_pact.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/quant/ppyolo_r50vd_qat_pact.yml) | -| PP-YOLO-MobileNetV3_large | baseline | 320 | 18.5 | 2.7ms | 27.9ms | 23.2 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_large_coco.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolo_mbv3_large_coco.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_mbv3_large_coco.yml) | - | -| PP-YOLO-MobileNetV3_large | 普通在线量化 | 320 | 5.6 | -- | 25.1ms | 24.3 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolo_mbv3_large_qat.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolo_mbv3_large_qat.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_mbv3_large_coco.yml) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/quant/ppyolo_mbv3_large_qat.yml) | -| YOLOv3-MobileNetV1 | baseline | 608 | 94.2 | 8.9ms | 332ms | 29.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_270e_coco.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | - | -| YOLOv3-MobileNetV1 | 普通在线量化 | 608 | 25.4 | 6.6ms | 248ms | 30.5 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_coco_qat.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_coco_qat.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/quant/yolov3_mobilenet_v1_qat.yml) | -| YOLOv3-MobileNetV3 | baseline | 608 | 90.3 | 9.4ms | 367.2ms | 31.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_coco.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v3_large_270e_coco.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_270e_coco.yml) | - | -| YOLOv3-MobileNetV3 | PACT在线量化 | 608 | 24.4 | 8.0ms | 280.0ms | 31.1 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v3_coco_qat.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v3_coco_qat.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_270e_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/quant/yolov3_mobilenet_v3_qat.yml) | -| YOLOv3-DarkNet53 | baseline | 608 | 238.2 | 16.0ms | -- | 39.0 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_darknet53_270e_coco.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_darknet53_270e_coco.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_darknet53_270e_coco.yml) | - | -| YOLOv3-DarkNet53 | 普通在线量化 | 608 | 78.8 | 12.4ms | -- | 38.8 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_darknet_coco_qat.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_darknet_coco_qat.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_darknet53_270e_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/quant/yolov3_darknet_qat.yml) | -| SSD-MobileNet_v1 | baseline | 300 | 22.5 | 4.4ms | 26.6ms | 73.8 | [下载链接](https://paddledet.bj.bcebos.com/models/ssd_mobilenet_v1_300_120e_voc.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ssd_mobilenet_v1_300_120e_voc.tar) |[配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ssd/ssd_mobilenet_v1_300_120e_voc.yml) | - | -| SSD-MobileNet_v1 | 普通在线量化 | 300 | 7.1 | -- | 21.5ms | 72.9 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ssd_mobilenet_v1_300_voc_qat.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ssd_mobilenet_v1_300_voc_qat.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ssd/ssd_mobilenet_v1_300_120e_voc.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/quant/ssd_mobilenet_v1_qat.yml) | -| Mask-ResNet50-FPN | baseline | (800, 1333) | 174.1 | 359.5ms | -- | 39.2/35.6 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_fpn_1x_coco.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/mask_rcnn_r50_fpn_1x_coco.tar) |[配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_r50_fpn_1x_coco.yml) | - | -| Mask-ResNet50-FPN | 普通在线量化 | (800, 1333) | -- | -- | -- | 39.7(+0.5)/35.9(+0.3) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/mask_rcnn_r50_fpn_1x_qat.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/mask_rcnn_r50_fpn_1x_qat.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_r50_fpn_1x_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/quant/mask_rcnn_r50_fpn_1x_qat.yml) | +| PP-YOLOE-l | baseline | 640 | - | 11.2ms(trt_fp32) | 7.7ms(trt_fp16) | -- | 50.9 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyoloe_crn_l_300e_coco.pdparams) | - | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyoloe/ppyoloe_crn_l_300e_coco.yml) | - | +| PP-YOLOE-l | 普通在线量化 | 640 | - | 6.7ms(trt_int8) | -- | 48.8 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyoloe_l_coco_qat.pdparams) | - | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyoloe/ppyoloe_crn_l_300e_coco.yml) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/slim/quant/ppyoloe_l_qat.yml) | +| PP-YOLOv2_R50vd | baseline | 640 | 208.6 | 19.1ms | -- | 49.1 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyolov2_r50vd_dcn_365e_coco.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolov2_r50vd_dcn_365e_coco.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | - | +| PP-YOLOv2_R50vd | PACT在线量化 | 640 | -- | 17.3ms | -- | 48.1 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolov2_r50vd_dcn_qat.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolov2_r50vd_dcn_qat.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/slim/quant/ppyolov2_r50vd_dcn_qat.yml) | +| PP-YOLO_R50vd | baseline | 608 | 183.3 | 17.4ms | -- | 44.8 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolo_r50vd_dcn_1x_coco.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | - | +| PP-YOLO_R50vd | PACT在线量化 | 608 | 67.3 | 13.8ms | -- | 44.3 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolo_r50vd_qat_pact.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolo_r50vd_qat_pact.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/slim/quant/ppyolo_r50vd_qat_pact.yml) | +| PP-YOLO-MobileNetV3_large | baseline | 320 | 18.5 | 2.7ms | 27.9ms | 23.2 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_large_coco.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolo_mbv3_large_coco.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_mbv3_large_coco.yml) | - | +| PP-YOLO-MobileNetV3_large | 普通在线量化 | 320 | 5.6 | -- | 25.1ms | 24.3 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolo_mbv3_large_qat.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolo_mbv3_large_qat.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_mbv3_large_coco.yml) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/slim/quant/ppyolo_mbv3_large_qat.yml) | +| YOLOv3-MobileNetV1 | baseline | 608 | 94.2 | 8.9ms | 332ms | 29.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_270e_coco.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | - | +| YOLOv3-MobileNetV1 | 普通在线量化 | 608 | 25.4 | 6.6ms | 248ms | 30.5 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_coco_qat.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_coco_qat.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/slim/quant/yolov3_mobilenet_v1_qat.yml) | +| YOLOv3-MobileNetV3 | baseline | 608 | 90.3 | 9.4ms | 367.2ms | 31.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_coco.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v3_large_270e_coco.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v3_large_270e_coco.yml) | - | +| YOLOv3-MobileNetV3 | PACT在线量化 | 608 | 24.4 | 8.0ms | 280.0ms | 31.1 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v3_coco_qat.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v3_coco_qat.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v3_large_270e_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/slim/quant/yolov3_mobilenet_v3_qat.yml) | +| YOLOv3-DarkNet53 | baseline | 608 | 238.2 | 16.0ms | -- | 39.0 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_darknet53_270e_coco.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_darknet53_270e_coco.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_darknet53_270e_coco.yml) | - | +| YOLOv3-DarkNet53 | 普通在线量化 | 608 | 78.8 | 12.4ms | -- | 38.8 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_darknet_coco_qat.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_darknet_coco_qat.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_darknet53_270e_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/slim/quant/yolov3_darknet_qat.yml) | +| SSD-MobileNet_v1 | baseline | 300 | 22.5 | 4.4ms | 26.6ms | 73.8 | [下载链接](https://paddledet.bj.bcebos.com/models/ssd_mobilenet_v1_300_120e_voc.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ssd_mobilenet_v1_300_120e_voc.tar) |[配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ssd/ssd_mobilenet_v1_300_120e_voc.yml) | - | +| SSD-MobileNet_v1 | 普通在线量化 | 300 | 7.1 | -- | 21.5ms | 72.9 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ssd_mobilenet_v1_300_voc_qat.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ssd_mobilenet_v1_300_voc_qat.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ssd/ssd_mobilenet_v1_300_120e_voc.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/slim/quant/ssd_mobilenet_v1_qat.yml) | +| Mask-ResNet50-FPN | baseline | (800, 1333) | 174.1 | 359.5ms | -- | 39.2/35.6 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_fpn_1x_coco.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/mask_rcnn_r50_fpn_1x_coco.tar) |[配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mask_rcnn/mask_rcnn_r50_fpn_1x_coco.yml) | - | +| Mask-ResNet50-FPN | 普通在线量化 | (800, 1333) | -- | -- | -- | 39.7(+0.5)/35.9(+0.3) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/mask_rcnn_r50_fpn_1x_qat.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/mask_rcnn_r50_fpn_1x_qat.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mask_rcnn/mask_rcnn_r50_fpn_1x_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/slim/quant/mask_rcnn_r50_fpn_1x_qat.yml) | 说明： - 上述V100预测时延非量化模型均是使用TensorRT-FP32测试，量化模型均使用TensorRT-INT8测试，并且都包含NMS耗时。 @@ -166,8 +166,8 @@ python3.7 tools/post_quant.py -c configs/ppyolo/ppyolo_mbv3_large_coco.yml --sli | 模型 | 压缩策略 | 输入尺寸 | Box AP | 下载 | 模型配置文件 | 压缩算法配置文件 | | ------------------ | ------------ | -------- | :---------: | :----------------------------------------------------------: | :----------------------------------------------------------: | :----------------------------------------------------------: | -| YOLOv3-MobileNetV1 | baseline | 608 | 29.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | - | -| YOLOv3-MobileNetV1 | 蒸馏 | 608 | 31.0(+1.6) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_coco_distill.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/distill/yolov3_mobilenet_v1_coco_distill.yml) | +| YOLOv3-MobileNetV1 | baseline | 608 | 29.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | - | +| YOLOv3-MobileNetV1 | 蒸馏 | 608 | 31.0(+1.6) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_coco_distill.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/slim/distill/yolov3_mobilenet_v1_coco_distill.yml) | - 具体蒸馏方法请参考[蒸馏策略文档](distill/README.md) @@ -177,6 +177,6 @@ python3.7 tools/post_quant.py -c configs/ppyolo/ppyolo_mbv3_large_coco.yml --sli | 模型 | 压缩策略 | 输入尺寸 | GFLOPs | 模型体积(MB) | 预测时延(SD855) | Box AP | 下载 | 模型配置文件 | 压缩算法配置文件 | | ------------------ | ------------ | -------- | :---------: |:---------: |:---------: | :---------: |:----------------------------------------------------------: | :----------------------------------------------------------: | :----------------------------------------------------------: | -| YOLOv3-MobileNetV1 | baseline | 608 | 24.65 | 94.2 | 332.0ms | 29.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | - | -| YOLOv3-MobileNetV1 | 蒸馏+剪裁 | 608 | 7.54(-69.4%) | 30.9(-67.2%) | 166.1ms | 28.4(-1.0) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_coco_distill_prune.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/extensions/yolov3_mobilenet_v1_coco_distill_prune.yml) | -| YOLOv3-MobileNetV1 | 剪裁+量化 | 608 | - | - | - | - | - | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_voc.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/extensions/yolov3_mobilenetv1_prune_qat.yml) | +| YOLOv3-MobileNetV1 | baseline | 608 | 24.65 | 94.2 | 332.0ms | 29.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | - | +| YOLOv3-MobileNetV1 | 蒸馏+剪裁 | 608 | 7.54(-69.4%) | 30.9(-67.2%) | 166.1ms | 28.4(-1.0) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_coco_distill_prune.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/slim/extensions/yolov3_mobilenet_v1_coco_distill_prune.yml) | +| YOLOv3-MobileNetV1 | 剪裁+量化 | 608 | - | - | - | - | - | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v1_270e_voc.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/slim/extensions/yolov3_mobilenetv1_prune_qat.yml) | diff --git a/configs/slim/README_en.md b/configs/slim/README_en.md index 924757e3fcdd465c7eb51c0cb7ce8b71c8e2fcb5..33f31021982ce0768cbfddc9dd57adb5a18cb473 100755 --- a/configs/slim/README_en.md +++ b/configs/slim/README_en.md @@ -101,18 +101,18 @@ python tools/export_model.py -c configs/{MODEL.yml} --slim_config configs/slim/{ | Model | Compression Strategy | GFLOPs | Model Volume(MB) | Input Size | Predict Delay(SD855) | Box AP | Download | Model Configuration File | Compression Algorithm Configuration File | | :----------------: | :-------------------: | :------------: | :--------------: | :--------: | :------------------: | :--------: | :------------------------------------------------------------------------------------------------: | :--------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------------------------------------------: | -| YOLOv3-MobileNetV1 | baseline | 24.13 | 93 | 608 | 332.0ms | 75.1 | [link](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_voc.pdparams) | [configuration file](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_voc.yml) | - | -| YOLOv3-MobileNetV1 | 剪裁-l1_norm(sensity) | 15.78(-34.49%) | 66(-29%) | 608 | - | 78.4(+3.3) | [link](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_voc_prune_l1_norm.pdparams) | [configuration file](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_voc.yml) | [slim configuration file](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/prune/yolov3_prune_l1_norm.yml) | +| YOLOv3-MobileNetV1 | baseline | 24.13 | 93 | 608 | 332.0ms | 75.1 | [link](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_voc.pdparams) | [configuration file](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v1_270e_voc.yml) | - | +| YOLOv3-MobileNetV1 | 剪裁-l1_norm(sensity) | 15.78(-34.49%) | 66(-29%) | 608 | - | 78.4(+3.3) | [link](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_voc_prune_l1_norm.pdparams) | [configuration file](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v1_270e_voc.yml) | [slim configuration file](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/slim/prune/yolov3_prune_l1_norm.yml) | #### COCO Benchmark | Mode | Compression Strategy | GFLOPs | Model Volume(MB) | Input Size | Predict Delay(SD855) | Box AP | Download | Model Configuration File | Compression Algorithm Configuration File | | :-----------------------: | :------------------: | :----: | :--------------: | :--------: | :------------------: | :----: | :---------------------------------------------------------------------------------------: | :------------------------------------------------------------------------------------------------------------------------------: | :-----------------------------------------------------------------------------------------------------------------------------------------: | -| PP-YOLO-MobileNetV3_large | baseline | -- | 18.5 | 608 | 25.1ms | 23.2 | [link](https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_large_coco.pdparams) | [configuration file](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_mbv3_large_coco.yml) | - | -| PP-YOLO-MobileNetV3_large | 剪裁-FPGM | -37% | 12.6 | 608 | - | 22.3 | [link](https://paddledet.bj.bcebos.com/models/slim/ppyolo_mbv3_large_prune_fpgm.pdparams) | [configuration file](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_mbv3_large_coco.yml) | [slim configuration file](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/prune/ppyolo_mbv3_large_prune_fpgm.yml) | -| YOLOv3-DarkNet53 | baseline | -- | 238.2 | 608 | - | 39.0 | [link](https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_large_coco.pdparams) | [configuration file](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_darknet53_270e_coco.yml) | - | -| YOLOv3-DarkNet53 | 剪裁-FPGM | -24% | - | 608 | - | 37.6 | [link](https://paddledet.bj.bcebos.com/models/slim/yolov3_darknet_prune_fpgm.pdparams) | [configuration file](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_darknet53_270e_coco.yml) | [slim configuration file](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/prune/yolov3_darknet_prune_fpgm.yml) | -| PP-YOLO_R50vd | baseline | -- | 183.3 | 608 | - | 44.8 | [link](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [configuration file](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | - | -| PP-YOLO_R50vd | 剪裁-FPGM | -35% | - | 608 | - | 42.1 | [link](https://paddledet.bj.bcebos.com/models/slim/ppyolo_r50vd_prune_fpgm.pdparams) | [configuration file](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | [slim configuration file](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/prune/ppyolo_r50vd_prune_fpgm.yml) | +| PP-YOLO-MobileNetV3_large | baseline | -- | 18.5 | 608 | 25.1ms | 23.2 | [link](https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_large_coco.pdparams) | [configuration file](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_mbv3_large_coco.yml) | - | +| PP-YOLO-MobileNetV3_large | 剪裁-FPGM | -37% | 12.6 | 608 | - | 22.3 | [link](https://paddledet.bj.bcebos.com/models/slim/ppyolo_mbv3_large_prune_fpgm.pdparams) | [configuration file](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_mbv3_large_coco.yml) | [slim configuration file](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/slim/prune/ppyolo_mbv3_large_prune_fpgm.yml) | +| YOLOv3-DarkNet53 | baseline | -- | 238.2 | 608 | - | 39.0 | [link](https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_large_coco.pdparams) | [configuration file](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_darknet53_270e_coco.yml) | - | +| YOLOv3-DarkNet53 | 剪裁-FPGM | -24% | - | 608 | - | 37.6 | [link](https://paddledet.bj.bcebos.com/models/slim/yolov3_darknet_prune_fpgm.pdparams) | [configuration file](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_darknet53_270e_coco.yml) | [slim configuration file](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/slim/prune/yolov3_darknet_prune_fpgm.yml) | +| PP-YOLO_R50vd | baseline | -- | 183.3 | 608 | - | 44.8 | [link](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [configuration file](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | - | +| PP-YOLO_R50vd | 剪裁-FPGM | -35% | - | 608 | - | 42.1 | [link](https://paddledet.bj.bcebos.com/models/slim/ppyolo_r50vd_prune_fpgm.pdparams) | [configuration file](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | [slim configuration file](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/slim/prune/ppyolo_r50vd_prune_fpgm.yml) | Description: - Currently, all models except RCNN series models are supported. @@ -124,24 +124,24 @@ Description: | Model | Compression Strategy | Input Size | Model Volume(MB) | Prediction Delay(V100) | Prediction Delay(SD855) | Box AP | Download | Download of Inference Model | Model Configuration File | Compression Algorithm Configuration File | | ------------------------- | -------------------------- | ----------- | :--------------: | :--------------------: | :---------------------: | :-------------------: | :-----------------------------------------------------------------------------------------: | :-----------------------------------------------------------------------------------------: | :----------------------------------------------------------------------------------------------------------------------------------------: | :--------------------------------------------------------------------------------------------------------------------------------------: | -| PP-YOLOE-l | baseline | 640 | - | 11.2ms(trt_fp32) | 7.7ms(trt_fp16) | -- | 50.9 | [link](https://paddledet.bj.bcebos.com/models/ppyoloe_crn_l_300e_coco.pdparams) | - | [Configuration File](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyoloe/ppyoloe_crn_l_300e_coco.yml) | - | -| PP-YOLOE-l | Common Online quantitative | 640 | - | 6.7ms(trt_int8) | -- | 48.8 | [link](https://paddledet.bj.bcebos.com/models/slim/ppyoloe_l_coco_qat.pdparams) | - | [Configuration File](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyoloe/ppyoloe_crn_l_300e_coco.yml) | [Configuration File](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/quant/ppyoloe_l_qat.yml) | -| PP-YOLOv2_R50vd | baseline | 640 | 208.6 | 19.1ms | -- | 49.1 | [link](https://paddledet.bj.bcebos.com/models/ppyolov2_r50vd_dcn_365e_coco.pdparams) | [link](https://paddledet.bj.bcebos.com/models/slim/ppyolov2_r50vd_dcn_365e_coco.tar) | [Configuration File](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | - | -| PP-YOLOv2_R50vd | PACT Online quantitative | 640 | -- | 17.3ms | -- | 48.1 | [link](https://paddledet.bj.bcebos.com/models/slim/ppyolov2_r50vd_dcn_qat.pdparams) | [link](https://paddledet.bj.bcebos.com/models/slim/ppyolov2_r50vd_dcn_qat.tar) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/quant/ppyolov2_r50vd_dcn_qat.yml) | -| PP-YOLO_R50vd | baseline | 608 | 183.3 | 17.4ms | -- | 44.8 | [link](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [link](https://paddledet.bj.bcebos.com/models/slim/ppyolo_r50vd_dcn_1x_coco.tar) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | - | -| PP-YOLO_R50vd | PACT Online quantitative | 608 | 67.3 | 13.8ms | -- | 44.3 | [link](https://paddledet.bj.bcebos.com/models/slim/ppyolo_r50vd_qat_pact.pdparams) | [link](https://paddledet.bj.bcebos.com/models/slim/ppyolo_r50vd_qat_pact.tar) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/quant/ppyolo_r50vd_qat_pact.yml) | -| PP-YOLO-MobileNetV3_large | baseline | 320 | 18.5 | 2.7ms | 27.9ms | 23.2 | [link](https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_large_coco.pdparams) | [link](https://paddledet.bj.bcebos.com/models/slim/ppyolo_mbv3_large_coco.tar) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_mbv3_large_coco.yml) | - | -| PP-YOLO-MobileNetV3_large | Common Online quantitative | 320 | 5.6 | -- | 25.1ms | 24.3 | [link](https://paddledet.bj.bcebos.com/models/slim/ppyolo_mbv3_large_qat.pdparams) | [link](https://paddledet.bj.bcebos.com/models/slim/ppyolo_mbv3_large_qat.tar) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_mbv3_large_coco.yml) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/quant/ppyolo_mbv3_large_qat.yml) | -| YOLOv3-MobileNetV1 | baseline | 608 | 94.2 | 8.9ms | 332ms | 29.4 | [link](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams) | [link](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_270e_coco.tar) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | - | -| YOLOv3-MobileNetV1 | Common Online quantitative | 608 | 25.4 | 6.6ms | 248ms | 30.5 | [link](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_coco_qat.pdparams) | [link](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_coco_qat.tar) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | [slim Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/quant/yolov3_mobilenet_v1_qat.yml) | -| YOLOv3-MobileNetV3 | baseline | 608 | 90.3 | 9.4ms | 367.2ms | 31.4 | [link](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_coco.pdparams) | [link](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v3_large_270e_coco.tar) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_270e_coco.yml) | - | -| YOLOv3-MobileNetV3 | PACT Online quantitative | 608 | 24.4 | 8.0ms | 280.0ms | 31.1 | [link](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v3_coco_qat.pdparams) | [link](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v3_coco_qat.tar) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_270e_coco.yml) | [slim Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/quant/yolov3_mobilenet_v3_qat.yml) | -| YOLOv3-DarkNet53 | baseline | 608 | 238.2 | 16.0ms | -- | 39.0 | [link](https://paddledet.bj.bcebos.com/models/yolov3_darknet53_270e_coco.pdparams) | [link](https://paddledet.bj.bcebos.com/models/slim/yolov3_darknet53_270e_coco.tar) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_darknet53_270e_coco.yml) | - | -| YOLOv3-DarkNet53 | Common Online quantitative | 608 | 78.8 | 12.4ms | -- | 38.8 | [link](https://paddledet.bj.bcebos.com/models/slim/yolov3_darknet_coco_qat.pdparams) | [link](https://paddledet.bj.bcebos.com/models/slim/yolov3_darknet_coco_qat.tar) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_darknet53_270e_coco.yml) | [slim Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/quant/yolov3_darknet_qat.yml) | -| SSD-MobileNet_v1 | baseline | 300 | 22.5 | 4.4ms | 26.6ms | 73.8 | [link](https://paddledet.bj.bcebos.com/models/ssd_mobilenet_v1_300_120e_voc.pdparams) | [link](https://paddledet.bj.bcebos.com/models/slim/ssd_mobilenet_v1_300_120e_voc.tar) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ssd/ssd_mobilenet_v1_300_120e_voc.yml) | - | -| SSD-MobileNet_v1 | Common Online quantitative | 300 | 7.1 | -- | 21.5ms | 72.9 | [link](https://paddledet.bj.bcebos.com/models/slim/ssd_mobilenet_v1_300_voc_qat.pdparams) | [link](https://paddledet.bj.bcebos.com/models/slim/ssd_mobilenet_v1_300_voc_qat.tar) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ssd/ssd_mobilenet_v1_300_120e_voc.yml) | [slim Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/quant/ssd_mobilenet_v1_qat.yml) | -| Mask-ResNet50-FPN | baseline | (800, 1333) | 174.1 | 359.5ms | -- | 39.2/35.6 | [link](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_fpn_1x_coco.pdparams) | [link](https://paddledet.bj.bcebos.com/models/slim/mask_rcnn_r50_fpn_1x_coco.tar) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_r50_fpn_1x_coco.yml) | - | -| Mask-ResNet50-FPN | Common Online quantitative | (800, 1333) | -- | -- | -- | 39.7(+0.5)/35.9(+0.3) | [link](https://paddledet.bj.bcebos.com/models/slim/mask_rcnn_r50_fpn_1x_qat.pdparams) | [link](https://paddledet.bj.bcebos.com/models/slim/mask_rcnn_r50_fpn_1x_qat.tar) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_r50_fpn_1x_coco.yml) | [slim Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/quant/mask_rcnn_r50_fpn_1x_qat.yml) | +| PP-YOLOE-l | baseline | 640 | - | 11.2ms(trt_fp32) | 7.7ms(trt_fp16) | -- | 50.9 | [link](https://paddledet.bj.bcebos.com/models/ppyoloe_crn_l_300e_coco.pdparams) | - | [Configuration File](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyoloe/ppyoloe_crn_l_300e_coco.yml) | - | +| PP-YOLOE-l | Common Online quantitative | 640 | - | 6.7ms(trt_int8) | -- | 48.8 | [link](https://paddledet.bj.bcebos.com/models/slim/ppyoloe_l_coco_qat.pdparams) | - | [Configuration File](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyoloe/ppyoloe_crn_l_300e_coco.yml) | [Configuration File](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/slim/quant/ppyoloe_l_qat.yml) | +| PP-YOLOv2_R50vd | baseline | 640 | 208.6 | 19.1ms | -- | 49.1 | [link](https://paddledet.bj.bcebos.com/models/ppyolov2_r50vd_dcn_365e_coco.pdparams) | [link](https://paddledet.bj.bcebos.com/models/slim/ppyolov2_r50vd_dcn_365e_coco.tar) | [Configuration File](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | - | +| PP-YOLOv2_R50vd | PACT Online quantitative | 640 | -- | 17.3ms | -- | 48.1 | [link](https://paddledet.bj.bcebos.com/models/slim/ppyolov2_r50vd_dcn_qat.pdparams) | [link](https://paddledet.bj.bcebos.com/models/slim/ppyolov2_r50vd_dcn_qat.tar) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/slim/quant/ppyolov2_r50vd_dcn_qat.yml) | +| PP-YOLO_R50vd | baseline | 608 | 183.3 | 17.4ms | -- | 44.8 | [link](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [link](https://paddledet.bj.bcebos.com/models/slim/ppyolo_r50vd_dcn_1x_coco.tar) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | - | +| PP-YOLO_R50vd | PACT Online quantitative | 608 | 67.3 | 13.8ms | -- | 44.3 | [link](https://paddledet.bj.bcebos.com/models/slim/ppyolo_r50vd_qat_pact.pdparams) | [link](https://paddledet.bj.bcebos.com/models/slim/ppyolo_r50vd_qat_pact.tar) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/slim/quant/ppyolo_r50vd_qat_pact.yml) | +| PP-YOLO-MobileNetV3_large | baseline | 320 | 18.5 | 2.7ms | 27.9ms | 23.2 | [link](https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_large_coco.pdparams) | [link](https://paddledet.bj.bcebos.com/models/slim/ppyolo_mbv3_large_coco.tar) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_mbv3_large_coco.yml) | - | +| PP-YOLO-MobileNetV3_large | Common Online quantitative | 320 | 5.6 | -- | 25.1ms | 24.3 | [link](https://paddledet.bj.bcebos.com/models/slim/ppyolo_mbv3_large_qat.pdparams) | [link](https://paddledet.bj.bcebos.com/models/slim/ppyolo_mbv3_large_qat.tar) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/ppyolo_mbv3_large_coco.yml) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/slim/quant/ppyolo_mbv3_large_qat.yml) | +| YOLOv3-MobileNetV1 | baseline | 608 | 94.2 | 8.9ms | 332ms | 29.4 | [link](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams) | [link](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_270e_coco.tar) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | - | +| YOLOv3-MobileNetV1 | Common Online quantitative | 608 | 25.4 | 6.6ms | 248ms | 30.5 | [link](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_coco_qat.pdparams) | [link](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_coco_qat.tar) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | [slim Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/slim/quant/yolov3_mobilenet_v1_qat.yml) | +| YOLOv3-MobileNetV3 | baseline | 608 | 90.3 | 9.4ms | 367.2ms | 31.4 | [link](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_coco.pdparams) | [link](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v3_large_270e_coco.tar) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v3_large_270e_coco.yml) | - | +| YOLOv3-MobileNetV3 | PACT Online quantitative | 608 | 24.4 | 8.0ms | 280.0ms | 31.1 | [link](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v3_coco_qat.pdparams) | [link](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v3_coco_qat.tar) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v3_large_270e_coco.yml) | [slim Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/slim/quant/yolov3_mobilenet_v3_qat.yml) | +| YOLOv3-DarkNet53 | baseline | 608 | 238.2 | 16.0ms | -- | 39.0 | [link](https://paddledet.bj.bcebos.com/models/yolov3_darknet53_270e_coco.pdparams) | [link](https://paddledet.bj.bcebos.com/models/slim/yolov3_darknet53_270e_coco.tar) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_darknet53_270e_coco.yml) | - | +| YOLOv3-DarkNet53 | Common Online quantitative | 608 | 78.8 | 12.4ms | -- | 38.8 | [link](https://paddledet.bj.bcebos.com/models/slim/yolov3_darknet_coco_qat.pdparams) | [link](https://paddledet.bj.bcebos.com/models/slim/yolov3_darknet_coco_qat.tar) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_darknet53_270e_coco.yml) | [slim Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/slim/quant/yolov3_darknet_qat.yml) | +| SSD-MobileNet_v1 | baseline | 300 | 22.5 | 4.4ms | 26.6ms | 73.8 | [link](https://paddledet.bj.bcebos.com/models/ssd_mobilenet_v1_300_120e_voc.pdparams) | [link](https://paddledet.bj.bcebos.com/models/slim/ssd_mobilenet_v1_300_120e_voc.tar) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ssd/ssd_mobilenet_v1_300_120e_voc.yml) | - | +| SSD-MobileNet_v1 | Common Online quantitative | 300 | 7.1 | -- | 21.5ms | 72.9 | [link](https://paddledet.bj.bcebos.com/models/slim/ssd_mobilenet_v1_300_voc_qat.pdparams) | [link](https://paddledet.bj.bcebos.com/models/slim/ssd_mobilenet_v1_300_voc_qat.tar) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ssd/ssd_mobilenet_v1_300_120e_voc.yml) | [slim Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/slim/quant/ssd_mobilenet_v1_qat.yml) | +| Mask-ResNet50-FPN | baseline | (800, 1333) | 174.1 | 359.5ms | -- | 39.2/35.6 | [link](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_fpn_1x_coco.pdparams) | [link](https://paddledet.bj.bcebos.com/models/slim/mask_rcnn_r50_fpn_1x_coco.tar) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mask_rcnn/mask_rcnn_r50_fpn_1x_coco.yml) | - | +| Mask-ResNet50-FPN | Common Online quantitative | (800, 1333) | -- | -- | -- | 39.7(+0.5)/35.9(+0.3) | [link](https://paddledet.bj.bcebos.com/models/slim/mask_rcnn_r50_fpn_1x_qat.pdparams) | [link](https://paddledet.bj.bcebos.com/models/slim/mask_rcnn_r50_fpn_1x_qat.tar) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mask_rcnn/mask_rcnn_r50_fpn_1x_coco.yml) | [slim Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/slim/quant/mask_rcnn_r50_fpn_1x_qat.yml) | Description: - The above V100 prediction delay non-quantified model is tested by TensorRT FP32, and the quantified model is tested by TensorRT INT8, and both of them include NMS time. @@ -153,8 +153,8 @@ Description: | Model | Compression Strategy | Input Size | Box AP | Download | Model Configuration File | Compression Strategy Configuration File | | ------------------ | -------------------- | ---------- | :--------: | :-------------------------------------------------------------------------------------------: | :----------------------------------------------------------------------------------------------------------------------------------: | :-----------------------------------------------------------------------------------------------------------------------------------------------: | -| YOLOv3-MobileNetV1 | baseline | 608 | 29.4 | [link](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | - | -| YOLOv3-MobileNetV1 | Distillation | 608 | 31.0(+1.6) | [link](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_coco_distill.pdparams) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | [slimConfiguration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/distill/yolov3_mobilenet_v1_coco_distill.yml) | +| YOLOv3-MobileNetV1 | baseline | 608 | 29.4 | [link](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | - | +| YOLOv3-MobileNetV1 | Distillation | 608 | 31.0(+1.6) | [link](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_coco_distill.pdparams) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | [slimConfiguration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/slim/distill/yolov3_mobilenet_v1_coco_distill.yml) | - Please refer to the specific distillation method[Distillation Policy Document](distill/README.md) @@ -164,5 +164,5 @@ Description: | Model | Compression Strategy | Input Size | GFLOPs | Model Volume(MB) | Prediction Delay(SD855) | Box AP | Download | Model Configuration File | Compression Algorithm Configuration File | | ------------------ | ------------------------ | ---------- | :----------: | :--------------: | :---------------------: | :--------: | :-------------------------------------------------------------------------------------------------: | :----------------------------------------------------------------------------------------------------------------------------------: | :--------------------------------------------------------------------------------------------------------------------------------------------------------: | -| YOLOv3-MobileNetV1 | baseline | 608 | 24.65 | 94.2 | 332.0ms | 29.4 | [link](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | - | -| YOLOv3-MobileNetV1 | Distillation + Tailoring | 608 | 7.54(-69.4%) | 30.9(-67.2%) | 166.1ms | 28.4(-1.0) | [link](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_coco_distill_prune.pdparams) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | [slimConfiguration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/extensions/yolov3_mobilenet_v1_coco_distill_prune.yml) | +| YOLOv3-MobileNetV1 | baseline | 608 | 24.65 | 94.2 | 332.0ms | 29.4 | [link](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | - | +| YOLOv3-MobileNetV1 | Distillation + Tailoring | 608 | 7.54(-69.4%) | 30.9(-67.2%) | 166.1ms | 28.4(-1.0) | [link](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_coco_distill_prune.pdparams) | [Configuration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | [slimConfiguration File ](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/slim/extensions/yolov3_mobilenet_v1_coco_distill_prune.yml) | diff --git a/configs/slim/distill/README.md b/configs/slim/distill/README.md index a08bf35fc350cd7c4284bb00ffdf641d80de9798..9fb0016da903089e8d2ec01c99bf4995b7637f94 100644 --- a/configs/slim/distill/README.md +++ b/configs/slim/distill/README.md @@ -3,7 +3,7 @@ ## YOLOv3模型蒸馏 以YOLOv3-MobileNetV1为例，使用YOLOv3-ResNet34作为蒸馏训练的teacher网络, 对YOLOv3-MobileNetV1结构的student网络进行蒸馏。 COCO数据集作为目标检测任务的训练目标难度更大，意味着teacher网络会预测出更多的背景bbox，如果直接用teacher的预测输出作为student学习的`soft label`会有严重的类别不均衡问题。解决这个问题需要引入新的方法，详细背景请参考论文:[Object detection at 200 Frames Per Second](https://arxiv.org/abs/1805.06361)。 -为了确定蒸馏的对象，我们首先需要找到student和teacher网络得到的`x,y,w,h,cls,objness`等Tensor，用teacher得到的结果指导student训练。具体实现可参考[代码](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/ppdet/slim/distill.py) +为了确定蒸馏的对象，我们首先需要找到student和teacher网络得到的`x,y,w,h,cls,objness`等Tensor，用teacher得到的结果指导student训练。具体实现可参考[代码](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/ppdet/slim/distill.py) ## FGD模型蒸馏 diff --git a/configs/smrt/README.md b/configs/smrt/README.md index d5a59ae1799bc53096cdcf53ece2ab53758f1a48..4135efb0ce71d2cc87e194734fc72a2e86ac3888 100644 --- a/configs/smrt/README.md +++ b/configs/smrt/README.md @@ -190,7 +190,7 @@ python tools/export_model.py -c configs/smrt/ppyoloe/ppyoloe_crn_m_300e_battery_ 为了更方便大家部署，我们也提供了完备的可视化部署Demo，欢迎尝试使用 -* [Windows Demo下载地址](https://github.com/PaddlePaddle/PaddleX/tree/develop/deploy/cpp/docs/csharp_deploy) +* [Windows Demo下载地址](https://github.com/PaddlePaddle/PaddleX/tree/release/2.5/deploy/cpp/docs/csharp_deploy)
diff --git a/configs/solov2/README.md b/configs/solov2/README.md index 037b2f96ce9f04087eed386abe58390857d59c4d..37db599d8c8a746f52acca80f9b560ebe2f8c8e2 100644 --- a/configs/solov2/README.md +++ b/configs/solov2/README.md @@ -19,9 +19,9 @@ SOLOv2 (Segmenting Objects by Locations) is a fast instance segmentation framewo | BlendMask | R50-FPN | True | 3x | 37.8 | 13.5 | V100 | - | - | | SOLOv2 (Paper) | R50-FPN | False | 1x | 34.8 | 18.5 | V100 | - | - | | SOLOv2 (Paper) | X101-DCN-FPN | True | 3x | 42.4 | 5.9 | V100 | - | - | -| SOLOv2 | R50-FPN | False | 1x | 35.5 | 21.9 | V100 | [model](https://paddledet.bj.bcebos.com/models/solov2_r50_fpn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/solov2/solov2_r50_fpn_1x_coco.yml) | -| SOLOv2 | R50-FPN | True | 3x | 38.0 | 21.9 | V100 | [model](https://paddledet.bj.bcebos.com/models/solov2_r50_fpn_3x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/solov2/solov2_r50_fpn_3x_coco.yml) | -| SOLOv2 | R101vd-FPN | True | 3x | 42.7 | 12.1 | V100 | [model](https://paddledet.bj.bcebos.com/models/solov2_r101_vd_fpn_3x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/solov2/solov2_r101_vd_fpn_3x_coco.yml) | +| SOLOv2 | R50-FPN | False | 1x | 35.5 | 21.9 | V100 | [model](https://paddledet.bj.bcebos.com/models/solov2_r50_fpn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/solov2/solov2_r50_fpn_1x_coco.yml) | +| SOLOv2 | R50-FPN | True | 3x | 38.0 | 21.9 | V100 | [model](https://paddledet.bj.bcebos.com/models/solov2_r50_fpn_3x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/solov2/solov2_r50_fpn_3x_coco.yml) | +| SOLOv2 | R101vd-FPN | True | 3x | 42.7 | 12.1 | V100 | [model](https://paddledet.bj.bcebos.com/models/solov2_r101_vd_fpn_3x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/solov2/solov2_r101_vd_fpn_3x_coco.yml) | **Notes:** @@ -30,7 +30,7 @@ SOLOv2 (Segmenting Objects by Locations) is a fast instance segmentation framewo ## Enhanced model | Backbone | Input size | Lr schd | V100 FP32(FPS) | Mask APval | Download | Configs | | :---------------------: | :-------------------: | :-----: | :------------: | :-----: | :---------: | :------------------------: | -| Light-R50-VD-DCN-FPN | 512 | 3x | 38.6 | 39.0 | [model](https://paddledet.bj.bcebos.com/models/solov2_r50_enhance_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/solov2/solov2_r50_enhance_coco.yml) | +| Light-R50-VD-DCN-FPN | 512 | 3x | 38.6 | 39.0 | [model](https://paddledet.bj.bcebos.com/models/solov2_r50_enhance_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/solov2/solov2_r50_enhance_coco.yml) | **Optimizing method of enhanced model:** - Better backbone network: ResNet50vd-DCN diff --git a/configs/ssd/README.md b/configs/ssd/README.md index 1ebc458669cfbc60216440c412aa1df7ac62602c..f1dadcb57641b0421d427ce5ec6000a4e132560c 100644 --- a/configs/ssd/README.md +++ b/configs/ssd/README.md @@ -6,8 +6,8 @@ | 骨架网络 | 网络类型 | 每张GPU图片个数 | 学习率策略 |推理时间(fps) | Box AP | 下载 | 配置文件 | | :-------------- | :------------- | :-----: | :-----: | :------------: | :-----: | :-----------------------------------------------------: | :-----: | -| VGG | SSD | 8 | 240e | ---- | 77.8 | [下载链接](https://paddledet.bj.bcebos.com/models/ssd_vgg16_300_240e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ssd/ssd_vgg16_300_240e_voc.yml) | -| MobileNet v1 | SSD | 32 | 120e | ---- | 73.8 | [下载链接](https://paddledet.bj.bcebos.com/models/ssd_mobilenet_v1_300_120e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ssd/ssd_mobilenet_v1_300_120e_voc.yml) | +| VGG | SSD | 8 | 240e | ---- | 77.8 | [下载链接](https://paddledet.bj.bcebos.com/models/ssd_vgg16_300_240e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ssd/ssd_vgg16_300_240e_voc.yml) | +| MobileNet v1 | SSD | 32 | 120e | ---- | 73.8 | [下载链接](https://paddledet.bj.bcebos.com/models/ssd_mobilenet_v1_300_120e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ssd/ssd_mobilenet_v1_300_120e_voc.yml) | **注意：** SSD-VGG使用4GPU在总batch size为32下训练240个epoch。SSD-MobileNetv1使用2GPU在总batch size为64下训练120周期。 diff --git a/configs/tood/README.md b/configs/tood/README.md index 9eb87fdf92ba36901e8f50b0d5a8c6fdb0da4104..9b33617c2b6243ac699eb3865e6bb29dee664a40 100644 --- a/configs/tood/README.md +++ b/configs/tood/README.md @@ -11,7 +11,7 @@ TOOD is an object detection model. We reproduced the model of the paper. | Backbone | Model | Images/GPU | Inf time (fps) | Box AP | Config | Download | |:------:|:--------:|:--------:|:--------------:|:------:|:------:|:--------:| -| R-50 | TOOD | 4 | --- | 42.5 | [config](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/tood/tood_r50_fpn_1x_coco.yml) | [model](https://paddledet.bj.bcebos.com/models/tood_r50_fpn_1x_coco.pdparams) | +| R-50 | TOOD | 4 | --- | 42.5 | [config](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/configs/tood/tood_r50_fpn_1x_coco.yml) | [model](https://paddledet.bj.bcebos.com/models/tood_r50_fpn_1x_coco.pdparams) | **Notes:** diff --git a/configs/ttfnet/README.md b/configs/ttfnet/README.md index 6f5a73e0ce8e1ce8430160a1cbdd6ae41d7accdf..17418c161d97a79d1bc33607db73827ccbdad8d8 100644 --- a/configs/ttfnet/README.md +++ b/configs/ttfnet/README.md @@ -13,7 +13,7 @@ TTFNet是一种用于实时目标检测且对训练时间友好的网络，对Ce | 骨架网络 | 网络类型 | 每张GPU图片个数 | 学习率策略 |推理时间(fps) | Box AP | 下载 | 配置文件 | | :-------------- | :------------- | :-----: | :-----: | :------------: | :-----: | :-----------------------------------------------------: | :-----: | -| DarkNet53 | TTFNet | 12 | 1x | ---- | 33.5 | [下载链接](https://paddledet.bj.bcebos.com/models/ttfnet_darknet53_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ttfnet/ttfnet_darknet53_1x_coco.yml) | +| DarkNet53 | TTFNet | 12 | 1x | ---- | 33.5 | [下载链接](https://paddledet.bj.bcebos.com/models/ttfnet_darknet53_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ttfnet/ttfnet_darknet53_1x_coco.yml) | @@ -40,7 +40,7 @@ PAFNet系列模型从如下方面优化TTFNet模型： | 骨架网络 | 网络类型 | 每张GPU图片个数 | 学习率策略 |推理时间(fps) | Box AP | 下载 | 配置文件 | | :-------------- | :------------- | :-----: | :-----: | :------------: | :-----: | :-----------------------------------------------------: | :-----: | -| ResNet50vd | PAFNet | 18 | 10x | ---- | 39.8 | [下载链接](https://paddledet.bj.bcebos.com/models/pafnet_10x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ttfnet/pafnet_10x_coco.yml) | +| ResNet50vd | PAFNet | 18 | 10x | ---- | 39.8 | [下载链接](https://paddledet.bj.bcebos.com/models/pafnet_10x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ttfnet/pafnet_10x_coco.yml) | @@ -48,7 +48,7 @@ PAFNet系列模型从如下方面优化TTFNet模型： | 骨架网络 | 网络类型 | 每张GPU图片个数 | 学习率策略 | Box AP | 麒麟990延时（ms） | 体积（M） | 下载 | 配置文件 | | :-------------- | :------------- | :-----: | :-----: | :-----: | :------------: | :-----: | :-----------------------------------------------------: | :-----: | -| MobileNetv3 | PAFNet-Lite | 12 | 20x | 23.9 | 26.00 | 14 | [下载链接](https://paddledet.bj.bcebos.com/models/pafnet_lite_mobilenet_v3_20x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ttfnet/pafnet_lite_mobilenet_v3_20x_coco.yml) | +| MobileNetv3 | PAFNet-Lite | 12 | 20x | 23.9 | 26.00 | 14 | [下载链接](https://paddledet.bj.bcebos.com/models/pafnet_lite_mobilenet_v3_20x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ttfnet/pafnet_lite_mobilenet_v3_20x_coco.yml) | **注意：** 由于动态图框架整体升级，PAFNet的PaddleDetection发布的权重模型评估时需要添加--bias字段, 例如 diff --git a/configs/ttfnet/README_en.md b/configs/ttfnet/README_en.md index 77af509a819cfd28c878ff717d469a2c3ca1eb94..2c6ce7126ad7fb308a2d65633311c79ce2808cac 100644 --- a/configs/ttfnet/README_en.md +++ b/configs/ttfnet/README_en.md @@ -14,7 +14,7 @@ The training time is short. Based on DarkNet53 backbone network, V100 8 cards on | Backbone | Network type | Number of images per GPU | Learning rate strategy | Inferring time(fps) | Box AP | Download | Configuration File | | :-------- | :----------- | :----------------------: | :--------------------: | :-----------------: | :----: | :------------------------------------------------------------------------------: | :----------------------------------------------------------------------------------------------------------------------------: | -| DarkNet53 | TTFNet | 12 | 1x | ---- | 33.5 | [link](https://paddledet.bj.bcebos.com/models/ttfnet_darknet53_1x_coco.pdparams) | [Configuration File](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ttfnet/ttfnet_darknet53_1x_coco.yml) | +| DarkNet53 | TTFNet | 12 | 1x | ---- | 33.5 | [link](https://paddledet.bj.bcebos.com/models/ttfnet_darknet53_1x_coco.pdparams) | [Configuration File](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ttfnet/ttfnet_darknet53_1x_coco.yml) | @@ -41,7 +41,7 @@ PAFNet series models optimize TTFNet model from the following aspects: | Backbone | Net type | Number of images per GPU | Learning rate strategy | Inferring time(fps) | Box AP | Download | Configuration File | | :--------- | :------- | :----------------------: | :--------------------: | :-----------------: | :----: | :---------------------------------------------------------------------: | :-------------------------------------------------------------------------------------------------------------------: | -| ResNet50vd | PAFNet | 18 | 10x | ---- | 39.8 | [link](https://paddledet.bj.bcebos.com/models/pafnet_10x_coco.pdparams) | [Configuration File](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ttfnet/pafnet_10x_coco.yml) | +| ResNet50vd | PAFNet | 18 | 10x | ---- | 39.8 | [link](https://paddledet.bj.bcebos.com/models/pafnet_10x_coco.pdparams) | [Configuration File](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ttfnet/pafnet_10x_coco.yml) | @@ -49,7 +49,7 @@ PAFNet series models optimize TTFNet model from the following aspects: | Backbone | Net type | Number of images per GPU | Learning rate strategy | Box AP | kirin 990 delay（ms） | volume（M） | Download | Configuration File | | :---------- | :---------- | :----------------------: | :--------------------: | :----: | :-------------------: | :---------: | :---------------------------------------------------------------------------------------: | :-------------------------------------------------------------------------------------------------------------------------------------: | -| MobileNetv3 | PAFNet-Lite | 12 | 20x | 23.9 | 26.00 | 14 | [link](https://paddledet.bj.bcebos.com/models/pafnet_lite_mobilenet_v3_20x_coco.pdparams) | [Configuration File](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ttfnet/pafnet_lite_mobilenet_v3_20x_coco.yml) | +| MobileNetv3 | PAFNet-Lite | 12 | 20x | 23.9 | 26.00 | 14 | [link](https://paddledet.bj.bcebos.com/models/pafnet_lite_mobilenet_v3_20x_coco.pdparams) | [Configuration File](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ttfnet/pafnet_lite_mobilenet_v3_20x_coco.yml) | **Attention:** Due to the overall upgrade of the dynamic graph framework, the weighting model published by PaddleDetection of PAF Net needs to be evaluated with a --bias field, for example diff --git a/configs/vehicle/README.md b/configs/vehicle/README.md index 5e20c6ffa86dcbc6e7d9fa8fbf57a9ae98eccb74..23d16b0eab85efeee4516148578f519ec2cd2ec2 100644 --- a/configs/vehicle/README.md +++ b/configs/vehicle/README.md @@ -5,7 +5,7 @@ We provide some models implemented by PaddlePaddle to detect objects in specific | Task | Algorithm | Box AP | Download | Configs | |:---------------------|:---------:|:------:| :-------------------------------------------------------------------------------------: |:------:| -| Vehicle Detection | YOLOv3 | 54.5 | [model](https://paddledet.bj.bcebos.com/models/vehicle_yolov3_darknet.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/vehicle/vehicle_yolov3_darknet.yml) | +| Vehicle Detection | YOLOv3 | 54.5 | [model](https://paddledet.bj.bcebos.com/models/vehicle_yolov3_darknet.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/vehicle/vehicle_yolov3_darknet.yml) | ## Vehicle Detection @@ -17,7 +17,7 @@ The network for detecting vehicles is YOLOv3, the backbone of which is Dacknet53 ### 2. Configuration for training -PaddleDetection provides users with a configuration file [yolov3_darknet53_270e_coco.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/yolov3/yolov3_darknet53_270e_coco.yml) to train YOLOv3 on the COCO dataset, compared with this file, we modify some parameters as followed to conduct the training for vehicle detection: +PaddleDetection provides users with a configuration file [yolov3_darknet53_270e_coco.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/configs/yolov3/yolov3_darknet53_270e_coco.yml) to train YOLOv3 on the COCO dataset, compared with this file, we modify some parameters as followed to conduct the training for vehicle detection: * num_classes: 6 * anchors: [[8, 9], [10, 23], [19, 15], [23, 33], [40, 25], [54, 50], [101, 80], [139, 145], [253, 224]] diff --git a/configs/vehicle/README_cn.md b/configs/vehicle/README_cn.md index 2bd09bb10bb4ab6e56f15fb4411ecd012249b677..ccbf649f3ba822a93d98b74748a19ba414008fab 100644 --- a/configs/vehicle/README_cn.md +++ b/configs/vehicle/README_cn.md @@ -5,7 +5,7 @@ | 任务 | 算法 | 精度(Box AP) | 下载 | 配置文件 | |:---------------------|:---------:|:------:| :---------------------------------------------------------------------------------: | :------:| -| 车辆检测 | YOLOv3 | 54.5 | [下载链接](https://paddledet.bj.bcebos.com/models/vehicle_yolov3_darknet.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/vehicle/vehicle_yolov3_darknet.yml) | +| 车辆检测 | YOLOv3 | 54.5 | [下载链接](https://paddledet.bj.bcebos.com/models/vehicle_yolov3_darknet.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/vehicle/vehicle_yolov3_darknet.yml) | ## 车辆检测（Vehicle Detection） @@ -18,7 +18,7 @@ Backbone为Dacknet53的YOLOv3。 ### 2. 训练参数配置 -PaddleDetection提供了使用COCO数据集对YOLOv3进行训练的参数配置文件[yolov3_darknet53_270e_coco.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/yolov3/yolov3_darknet53_270e_coco.yml)，与之相比，在进行车辆检测的模型训练时，我们对以下参数进行了修改： +PaddleDetection提供了使用COCO数据集对YOLOv3进行训练的参数配置文件[yolov3_darknet53_270e_coco.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/configs/yolov3/yolov3_darknet53_270e_coco.yml)，与之相比，在进行车辆检测的模型训练时，我们对以下参数进行了修改： * num_classes: 6 * anchors: [[8, 9], [10, 23], [19, 15], [23, 33], [40, 25], [54, 50], [101, 80], [139, 145], [253, 224]] diff --git a/configs/yolov3/README.md b/configs/yolov3/README.md index 41cee48c916f4530e43efa49f961239f52e60cd1..cdd948a35d9c952d4c15fd1437f5be73f73293df 100644 --- a/configs/yolov3/README.md +++ b/configs/yolov3/README.md @@ -9,41 +9,41 @@ | DarkNet53(paper) | 608 | 8 | 270e | ---- | 33.0 | - | - | | DarkNet53(paper) | 416 | 8 | 270e | ---- | 31.0 | - | - | | DarkNet53(paper) | 320 | 8 | 270e | ---- | 28.2 | - | - | -| DarkNet53 | 608 | 8 | 270e | ---- | 39.1 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_darknet53_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_darknet53_270e_coco.yml) | -| DarkNet53 | 416 | 8 | 270e | ---- | 37.7 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_darknet53_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_darknet53_270e_coco.yml) | -| DarkNet53 | 320 | 8 | 270e | ---- | 34.8 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_darknet53_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_darknet53_270e_coco.yml) | -| ResNet50_vd | 608 | 8 | 270e | ---- | 40.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_r50vd_dcn_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_r50vd_dcn_270e_coco.yml) | -| ResNet50_vd | 416 | 8 | 270e | ---- | 38.2 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_r50vd_dcn_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_r50vd_dcn_270e_coco.yml) | -| ResNet50_vd | 320 | 8 | 270e | ---- | 35.1 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_r50vd_dcn_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_r50vd_dcn_270e_coco.yml) | -| ResNet34 | 608 | 8 | 270e | ---- | 36.2 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_r34_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_r34_270e_coco.yml) | -| ResNet34 | 416 | 8 | 270e | ---- | 34.3 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_r34_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_r34_270e_coco.yml) | -| ResNet34 | 320 | 8 | 270e | ---- | 31.2 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_r34_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_r34_270e_coco.yml) | -| MobileNet-V1 | 608 | 8 | 270e | ---- | 29.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | -| MobileNet-V1 | 416 | 8 | 270e | ---- | 29.3 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | -| MobileNet-V1 | 320 | 8 | 270e | ---- | 27.2 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | -| MobileNet-V3 | 608 | 8 | 270e | ---- | 31.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_270e_coco.yml) | -| MobileNet-V3 | 416 | 8 | 270e | ---- | 29.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_270e_coco.yml) | -| MobileNet-V3 | 320 | 8 | 270e | ---- | 27.1 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_270e_coco.yml) | -| MobileNet-V1-SSLD | 608 | 8 | 270e | ---- | 31.0 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_coco.yml) | -| MobileNet-V1-SSLD | 416 | 8 | 270e | ---- | 30.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_coco.yml) | -| MobileNet-V1-SSLD | 320 | 8 | 270e | ---- | 28.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_coco.yml) | +| DarkNet53 | 608 | 8 | 270e | ---- | 39.1 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_darknet53_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_darknet53_270e_coco.yml) | +| DarkNet53 | 416 | 8 | 270e | ---- | 37.7 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_darknet53_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_darknet53_270e_coco.yml) | +| DarkNet53 | 320 | 8 | 270e | ---- | 34.8 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_darknet53_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_darknet53_270e_coco.yml) | +| ResNet50_vd | 608 | 8 | 270e | ---- | 40.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_r50vd_dcn_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_r50vd_dcn_270e_coco.yml) | +| ResNet50_vd | 416 | 8 | 270e | ---- | 38.2 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_r50vd_dcn_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_r50vd_dcn_270e_coco.yml) | +| ResNet50_vd | 320 | 8 | 270e | ---- | 35.1 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_r50vd_dcn_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_r50vd_dcn_270e_coco.yml) | +| ResNet34 | 608 | 8 | 270e | ---- | 36.2 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_r34_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_r34_270e_coco.yml) | +| ResNet34 | 416 | 8 | 270e | ---- | 34.3 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_r34_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_r34_270e_coco.yml) | +| ResNet34 | 320 | 8 | 270e | ---- | 31.2 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_r34_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_r34_270e_coco.yml) | +| MobileNet-V1 | 608 | 8 | 270e | ---- | 29.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | +| MobileNet-V1 | 416 | 8 | 270e | ---- | 29.3 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | +| MobileNet-V1 | 320 | 8 | 270e | ---- | 27.2 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | +| MobileNet-V3 | 608 | 8 | 270e | ---- | 31.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v3_large_270e_coco.yml) | +| MobileNet-V3 | 416 | 8 | 270e | ---- | 29.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v3_large_270e_coco.yml) | +| MobileNet-V3 | 320 | 8 | 270e | ---- | 27.1 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v3_large_270e_coco.yml) | +| MobileNet-V1-SSLD | 608 | 8 | 270e | ---- | 31.0 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_coco.yml) | +| MobileNet-V1-SSLD | 416 | 8 | 270e | ---- | 30.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_coco.yml) | +| MobileNet-V1-SSLD | 320 | 8 | 270e | ---- | 28.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_coco.yml) | ### YOLOv3 on Pasacl VOC | 骨架网络 | 输入尺寸 | 每张GPU图片个数 | 学习率策略 |推理时间(fps)| Box AP | 下载 | 配置文件 | | :----------- | :--: | :-----: | :-----: |:------------: |:----: | :-------: | :----: | -| MobileNet-V1 | 608 | 8 | 270e | - | 75.2 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_voc.yml) | -| MobileNet-V1 | 416 | 8 | 270e | - | 76.2 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_voc.yml) | -| MobileNet-V1 | 320 | 8 | 270e | - | 74.3 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_voc.yml) | -| MobileNet-V3 | 608 | 8 | 270e | - | 79.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_270e_voc.yml) | -| MobileNet-V3 | 416 | 8 | 270e | - | 78.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_270e_voc.yml) | -| MobileNet-V3 | 320 | 8 | 270e | - | 76.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_270e_voc.yml) | -| MobileNet-V1-SSLD | 608 | 8 | 270e | - | 78.3 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_voc.yml) | -| MobileNet-V1-SSLD | 416 | 8 | 270e | - | 79.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_voc.yml) | -| MobileNet-V1-SSLD | 320 | 8 | 270e | - | 77.3 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_voc.yml) | -| MobileNet-V3-SSLD | 608 | 8 | 270e | - | 80.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_ssld_270e_voc.yml) | -| MobileNet-V3-SSLD | 416 | 8 | 270e | - | 79.2 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_ssld_270e_voc.yml) | -| MobileNet-V3-SSLD | 320 | 8 | 270e | - | 77.3 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_ssld_270e_voc.yml) | +| MobileNet-V1 | 608 | 8 | 270e | - | 75.2 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v1_270e_voc.yml) | +| MobileNet-V1 | 416 | 8 | 270e | - | 76.2 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v1_270e_voc.yml) | +| MobileNet-V1 | 320 | 8 | 270e | - | 74.3 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v1_270e_voc.yml) | +| MobileNet-V3 | 608 | 8 | 270e | - | 79.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v3_large_270e_voc.yml) | +| MobileNet-V3 | 416 | 8 | 270e | - | 78.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v3_large_270e_voc.yml) | +| MobileNet-V3 | 320 | 8 | 270e | - | 76.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v3_large_270e_voc.yml) | +| MobileNet-V1-SSLD | 608 | 8 | 270e | - | 78.3 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_voc.yml) | +| MobileNet-V1-SSLD | 416 | 8 | 270e | - | 79.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_voc.yml) | +| MobileNet-V1-SSLD | 320 | 8 | 270e | - | 77.3 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_voc.yml) | +| MobileNet-V3-SSLD | 608 | 8 | 270e | - | 80.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v3_large_ssld_270e_voc.yml) | +| MobileNet-V3-SSLD | 416 | 8 | 270e | - | 79.2 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v3_large_ssld_270e_voc.yml) | +| MobileNet-V3-SSLD | 320 | 8 | 270e | - | 77.3 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v3_large_ssld_270e_voc.yml) | ## Citations ``` diff --git a/configs/yolox/README.md b/configs/yolox/README.md index a689b2981e06d439bc212c4fbb2ba4efa6860a7c..e9cdf03da172815040eb0eef0cd15cb8bf04112f 100644 --- a/configs/yolox/README.md +++ b/configs/yolox/README.md @@ -168,7 +168,7 @@ python deploy/python/infer.py --model_dir=output_inference/yolox_s_300e_coco --i
如何计算模型参数量 -可以将以下代码插入：[trainer.py](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/ppdet/engine/trainer.py#L154) 来计算参数量。 +可以将以下代码插入：[trainer.py](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/ppdet/engine/trainer.py#L154) 来计算参数量。 ```python params = sum([ p.numel() for n, p in self.model.named_parameters() diff --git a/deploy/README.md b/deploy/README.md index ac1ba72f61c760d04376a510af55ed6bd4ac75b7..6e083c291409c6acde70e75cc145b0147fd2f36c 100644 --- a/deploy/README.md +++ b/deploy/README.md @@ -51,7 +51,7 @@ python tools/export_model.py -c configs/yolov3/yolov3_mobilenet_v1_roadsign.yml - 详细案例请参考[Paddle-Lite-Demo](https://github.com/PaddlePaddle/Paddle-Lite-Demo)部署。更多内容，请参考[Paddle-Lite](https://github.com/PaddlePaddle/Paddle-Lite) -## 4.第三方部署（MNN、NCNN、Openvino） +## 4.第三方部署（MNN、NCNN、Openvino） - 第三方部署提供PicoDet、TinyPose案例，其他模型请参考修改 - TinyPose部署推荐工具：Intel CPU端推荐使用Openvino，GPU端推荐使用PaddleInference，ARM/ANDROID端推荐使用PaddleLite或者MNN diff --git a/deploy/README_en.md b/deploy/README_en.md index f587b56b99e7a6b7c7ed31c5ae6307ade6e18126..dc2a0ac659672b47e89514ffead423124751a2be 100644 --- a/deploy/README_en.md +++ b/deploy/README_en.md @@ -42,7 +42,7 @@ The prediction model will be exported to the `output_inference/yolov3_darknet53_ For details on model export, please refer to the documentation [Tutorial on Paddle Detection MODEL EXPORT](./EXPORT_MODEL_en.md). ### 2.2 Predictions are made using Paddle Serving -* [Install PaddleServing](https://github.com/PaddlePaddle/Serving/blob/develop/README.md#installation) +* [Install PaddleServing](https://github.com/PaddlePaddle/Serving/blob/release/2.5/README.md#installation) * [Use PaddleServing](./serving/README.md) diff --git a/deploy/auto_compression/README.md b/deploy/auto_compression/README.md index d5ade01716f9544e7301dd1ae55415c2355789f3..0d35a8d282288abdaf36d65045f6219e7177f1fc 100644 --- a/deploy/auto_compression/README.md +++ b/deploy/auto_compression/README.md @@ -21,7 +21,7 @@ | 模型 | Base mAP | 离线量化mAP | ACT量化mAP | TRT-FP32 | TRT-FP16 | TRT-INT8 | 配置文件 | 量化模型 | | :-------- |:-------- |:--------: | :---------------------: | :----------------: | :----------------: | :---------------: | :----------------------: | :---------------------: | -| PP-YOLOE-l | 50.9 | - | 50.6 | 11.2ms | 7.7ms | **6.7ms** | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/deploy/auto_compression/configs/ppyoloe_l_qat_dis.yaml) | [Quant Model](https://bj.bcebos.com/v1/paddle-slim-models/act/ppyoloe_crn_l_300e_coco_quant.tar) | +| PP-YOLOE-l | 50.9 | - | 50.6 | 11.2ms | 7.7ms | **6.7ms** | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/deploy/auto_compression/configs/ppyoloe_l_qat_dis.yaml) | [Quant Model](https://bj.bcebos.com/v1/paddle-slim-models/act/ppyoloe_crn_l_300e_coco_quant.tar) | - mAP的指标均在COCO val2017数据集中评测得到，IoU=0.5:0.95。 - PP-YOLOE-l模型在Tesla V100的GPU环境下测试，并且开启TensorRT，batch_size=1，包含NMS，测试脚本是[benchmark demo](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.4/deploy/python)。 @@ -30,7 +30,7 @@ | 模型 | 策略 | mAP | FP32 | FP16 | INT8 | 配置文件 | 模型 | | :-------- |:-------- |:--------: | :----------------: | :----------------: | :---------------: | :----------------------: | :---------------------: | -| PicoDet-S-NPU | Baseline | 30.1 | - | - | - | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet/picodet_s_416_coco_npu.yml) | [Model](https://bj.bcebos.com/v1/paddle-slim-models/act/picodet_s_416_coco_npu.tar) | +| PicoDet-S-NPU | Baseline | 30.1 | - | - | - | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet/picodet_s_416_coco_npu.yml) | [Model](https://bj.bcebos.com/v1/paddle-slim-models/act/picodet_s_416_coco_npu.tar) | | PicoDet-S-NPU | 量化训练 | 29.7 | - | - | - | [config](https://github.com/PaddlePaddle/PaddleSlim/tree/develop/demo/full_quantization/detection/configs/picodet_s_qat_dis.yaml) | [Model](https://bj.bcebos.com/v1/paddle-slim-models/act/picodet_s_npu_quant.tar) | - mAP的指标均在COCO val2017数据集中评测得到，IoU=0.5:0.95。 @@ -87,7 +87,7 @@ pip install paddledet 预测模型的格式为：`model.pdmodel` 和 `model.pdiparams`两个，带`pdmodel`的是模型文件，带`pdiparams`后缀的是权重文件。 -根据[PaddleDetection文档](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/docs/tutorials/GETTING_STARTED_cn.md#8-%E6%A8%A1%E5%9E%8B%E5%AF%BC%E5%87%BA) 导出Inference模型，具体可参考下方PP-YOLOE模型的导出示例： +根据[PaddleDetection文档](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/docs/tutorials/GETTING_STARTED_cn.md#8-%E6%A8%A1%E5%9E%8B%E5%AF%BC%E5%87%BA) 导出Inference模型，具体可参考下方PP-YOLOE模型的导出示例： - 下载代码 ``` git clone https://github.com/PaddlePaddle/PaddleDetection.git diff --git a/deploy/cpp/docs/Jetson_build.md b/deploy/cpp/docs/Jetson_build.md index ea9699a438ed3977e118b155a01b533d83bb12f4..ec94679667f2959aebdca2443c56804f84ba936c 100644 --- a/deploy/cpp/docs/Jetson_build.md +++ b/deploy/cpp/docs/Jetson_build.md @@ -14,11 +14,11 @@ ``` cat /etc/nv_tegra_release ``` -* (2) 根据硬件，选择硬件可安装的`JetPack`版本，硬件和`JetPack`版本对应关系请参考[jetpack-archive](https://developer.nvidia.com/embedded/jetpack-archive). +* (2) 根据硬件，选择硬件可安装的`JetPack`版本，硬件和`JetPack`版本对应关系请参考[jetpack-archive](https://release/2.5er.nvidia.com/embedded/jetpack-archive). * (3) 下载`JetPack`，请参考[NVIDIA Jetson Linux Developer Guide](https://docs.nvidia.com/jetson/l4t/index.html) 中的`Preparing a Jetson Developer Kit for Use`章节内容进行刷写系统镜像。 -**注意**: 请在[jetpack-archive](https://developer.nvidia.com/embedded/jetpack-archive) 根据硬件选择适配的`JetPack`版本进行刷机。 +**注意**: 请在[jetpack-archive](https://release/2.5er.nvidia.com/embedded/jetpack-archive) 根据硬件选择适配的`JetPack`版本进行刷机。 ## 下载或编译`Paddle`预测库 本文档使用`Paddle`在`JetPack4.3`上预先编译好的预测库，请根据硬件在[安装与编译 Linux 预测库](https://www.paddlepaddle.org.cn/documentation/docs/zh/guides/05_inference_deployment/inference/build_and_install_lib_cn.html) 中选择对应版本的`Paddle`预测库。 diff --git a/deploy/lite/README.md b/deploy/lite/README.md index 30447460eb6c4ccdf5c1013d1ea2d631d9073fba..c0148b86ea0aa38ee963bcd337ecadafe03ba0a1 100644 --- a/deploy/lite/README.md +++ b/deploy/lite/README.md @@ -36,8 +36,8 @@ export NDK_ROOT=[YOUR_NDK_PATH]/android-ndk-r17c ```shell git clone https://github.com/PaddlePaddle/Paddle-Lite.git cd Paddle-Lite -# 如果使用编译方式，建议使用develop分支编译预测库 -git checkout develop +# 如果使用编译方式，建议使用release/2.5分支编译预测库 +git checkout release/2.5 # FP32 ./lite/tools/build_android.sh --arch=armv8 --toolchain=clang --with_cv=ON --with_extra=ON # FP16 @@ -96,7 +96,7 @@ Paddle-Lite 提供了多种策略来自动优化原始的模型，其中包括 # 如果准备环境时已经clone了Paddle-Lite，则不用重新clone Paddle-Lite git clone https://github.com/PaddlePaddle/Paddle-Lite.git cd Paddle-Lite - git checkout develop + git checkout release/2.5 # 启动编译 ./lite/tools/build.sh build_optimize_tool ``` @@ -169,7 +169,7 @@ python deploy/lite/convert_yml_to_json.py output_inference/picodet_s_320_coco/in ``` 2.3. Window安装ADB - win上安装需要去谷歌的安卓平台下载ADB软件包进行安装：[链接](https://developer.android.com/studio) + win上安装需要去谷歌的安卓平台下载ADB软件包进行安装：[链接](https://release/2.5er.android.com/studio) 3. 手机连接电脑后，开启手机`USB调试`选项，选择`文件传输`模式，在电脑终端中输入： diff --git a/deploy/pipeline/README_en.md b/deploy/pipeline/README_en.md index 227d08ec7b1467d48c365629373b09c196c32528..05e8b38fb7a7338d3bf6cbdb3ee99fa1d05635f5 100644 --- a/deploy/pipeline/README_en.md +++ b/deploy/pipeline/README_en.md @@ -14,7 +14,7 @@ PP-Human supports various inputs such as images, single-camera, and multi-camera ## 📣 Updates -- 🔥 **2022.7.13：PP-Human v2 launched with a full upgrade of four industrial features: behavior analysis, attributes recognition, visitor traffic statistics and ReID. It provides a strong core algorithm for pedestrian detection, tracking and attribute analysis with a simple and detailed development process and model optimization strategy.** +- 🔥 **2022.7.13：PP-Human v2 launched with a full upgrade of four industrial features: behavior analysis, attributes recognition, visitor traffic statistics and ReID. It provides a strong core algorithm for pedestrian detection, tracking and attribute analysis with a simple and detailed release/2.5ment process and model optimization strategy.** - 2022.4.18: Add PP-Human practical tutorials, including training, deployment, and action expansion. Details for AIStudio project please see [Link](https://aistudio.baidu.com/aistudio/projectdetail/3842982) - 2022.4.10: Add PP-Human examples; empower refined management of intelligent community management. A quick start for AIStudio [Link](https://aistudio.baidu.com/aistudio/projectdetail/3679564) @@ -79,7 +79,7 @@ Click to download the model, then unzip and save it in the `. /output_inference` ### Pedestrian attribute/feature recognition * [A quick start](docs/tutorials/pphuman_attribute.md) -* [Customized development tutorials](../../docs/advanced_tutorials/customization/pphuman_attribute.md) +* [Customized release/2.5ment tutorials](../../docs/advanced_tutorials/customization/pphuman_attribute.md) * Data Preparation * Model Optimization * New Attributes @@ -89,7 +89,7 @@ Click to download the model, then unzip and save it in the `. /output_inference` * [A quick start](docs/tutorials/pphuman_action.md) * Falling detection * Fighting detection -* [Customized development tutorials](../../docs/advanced_tutorials/customization/action_recognotion/README.md) +* [Customized release/2.5ment tutorials](../../docs/advanced_tutorials/customization/action_recognotion/README.md) * Solution Selection * Data Preparation * Model Optimization @@ -98,7 +98,7 @@ Click to download the model, then unzip and save it in the `. /output_inference` ### ReID * [A quick start](docs/tutorials/pphuman_mtmct.md) -* [Customized development tutorials](../../docs/advanced_tutorials/customization/pphuman_mtmct.md) +* [Customized release/2.5ment tutorials](../../docs/advanced_tutorials/customization/pphuman_mtmct.md) * Data Preparation * Model Optimization @@ -108,6 +108,6 @@ Click to download the model, then unzip and save it in the `. /output_inference` * Pedestrian tracking, * Visitor traffic statistics * Regional intrusion diagnosis and counting -* [Customized development tutorials](../../docs/advanced_tutorials/customization/pphuman_mot.md) +* [Customized release/2.5ment tutorials](../../docs/advanced_tutorials/customization/pphuman_mot.md) * Data Preparation * Model Optimization diff --git a/deploy/pipeline/docs/tutorials/PPVehicle_QUICK_STARTED.md b/deploy/pipeline/docs/tutorials/PPVehicle_QUICK_STARTED.md index 4921a4225316900b7394dcee8be69ab54c6d0d61..3f756c999e2f439a037dde52b0f79fb87a239322 100644 --- a/deploy/pipeline/docs/tutorials/PPVehicle_QUICK_STARTED.md +++ b/deploy/pipeline/docs/tutorials/PPVehicle_QUICK_STARTED.md @@ -17,7 +17,7 @@ ## 环境准备 -环境要求： PaddleDetection版本 >= release/2.4 或 develop版本 +环境要求： PaddleDetection版本 >= release/2.4 或 release/2.5版本 PaddlePaddle和PaddleDetection安装 diff --git a/deploy/pipeline/docs/tutorials/pphuman_action.md b/deploy/pipeline/docs/tutorials/pphuman_action.md index 67f09fdd0c243d7bc563ae4ff13158562d0123e7..210081a3d4562ec62b58488681fa60e4e475671d 100644 --- a/deploy/pipeline/docs/tutorials/pphuman_action.md +++ b/deploy/pipeline/docs/tutorials/pphuman_action.md @@ -81,7 +81,7 @@ SKELETON_ACTION: # 基于骨骼点的行为识别模型配置 0: 摔倒， 1: 其他 ``` -- 摔倒行为识别模型使用了[ST-GCN](https://arxiv.org/abs/1801.07455)，并基于[PaddleVideo](https://github.com/PaddlePaddle/PaddleVideo/blob/develop/docs/zh-CN/model_zoo/recognition/stgcn.md)套件完成模型训练。 +- 摔倒行为识别模型使用了[ST-GCN](https://arxiv.org/abs/1801.07455)，并基于[PaddleVideo](https://github.com/PaddlePaddle/PaddleVideo/blob/release/2.5/docs/zh-CN/model_zoo/recognition/stgcn.md)套件完成模型训练。 ## 基于图像分类的行为识别 @@ -132,12 +132,12 @@ python deploy/pipeline/pipeline.py --config deploy/pipeline/config/infer_cfg_pph ### 方案说明 1. 使用目标检测与多目标跟踪获取视频输入中的行人检测框及跟踪ID序号，模型方案为PP-YOLOE，详细文档参考[PP-YOLOE](../../../../configs/ppyoloe/README_cn.md)，跟踪方案为OC-SORT，详细文档参考[OC-SORT](../../../../configs/mot/ocsort)。 2. 通过行人检测框的坐标在输入视频的对应帧中截取每个行人。 -3. 通过在帧级别的行人图像通过图像分类的方式实现。当图片所属类别为对应行为时，即认为在一定时间段内该人物处于该行为状态中。该任务使用[PP-HGNet](https://github.com/PaddlePaddle/PaddleClas/blob/develop/docs/zh_CN/models/PP-HGNet.md)实现，当前版本模型支持打电话行为的识别，预测得到的`class id`对应关系为： +3. 通过在帧级别的行人图像通过图像分类的方式实现。当图片所属类别为对应行为时，即认为在一定时间段内该人物处于该行为状态中。该任务使用[PP-HGNet](https://github.com/PaddlePaddle/PaddleClas/blob/release/2.5/docs/zh_CN/models/PP-HGNet.md)实现，当前版本模型支持打电话行为的识别，预测得到的`class id`对应关系为： ``` 0: 打电话， 1: 其他 ``` -- 基于分类的行为识别基于[PaddleClas](https://github.com/PaddlePaddle/PaddleClas/blob/develop/docs/zh_CN/models/PP-HGNet.md#3.3)完成模型训练。 +- 基于分类的行为识别基于[PaddleClas](https://github.com/PaddlePaddle/PaddleClas/blob/release/2.5/docs/zh_CN/models/PP-HGNet.md#3.3)完成模型训练。 ## 基于检测的行为识别 @@ -258,7 +258,7 @@ python deploy/pipeline/pipeline.py --config deploy/pipeline/config/infer_cfg_pph ### 方案说明 -目前打架识别模型使用的是[PP-TSM](https://github.com/PaddlePaddle/PaddleVideo/blob/develop/docs/zh-CN/model_zoo/recognition/pp-tsm.md)，并在PP-TSM视频分类模型训练流程的基础上修改适配，完成模型训练。对于输入的视频或者视频流，进行等间隔抽帧，当视频帧累计到指定数目时，输入到视频分类模型中判断是否存在打架行为。 +目前打架识别模型使用的是[PP-TSM](https://github.com/PaddlePaddle/PaddleVideo/blob/release/2.5/docs/zh-CN/model_zoo/recognition/pp-tsm.md)，并在PP-TSM视频分类模型训练流程的基础上修改适配，完成模型训练。对于输入的视频或者视频流，进行等间隔抽帧，当视频帧累计到指定数目时，输入到视频分类模型中判断是否存在打架行为。 ## 参考文献 diff --git a/deploy/pipeline/docs/tutorials/pphuman_action_en.md b/deploy/pipeline/docs/tutorials/pphuman_action_en.md index c7eacf4d8e5878d251734787ed64cab73170194f..f57a714a37abc01711ca8ce219c79311ff913ddc 100644 --- a/deploy/pipeline/docs/tutorials/pphuman_action_en.md +++ b/deploy/pipeline/docs/tutorials/pphuman_action_en.md @@ -97,7 +97,7 @@ SKELETON_ACTION: # Config for skeleton-based action recognition model 1: Others ``` -- The falling action recognition model uses [ST-GCN](https://arxiv.org/abs/1801.07455), and employ the [PaddleVideo](https://github.com/PaddlePaddle/PaddleVideo/blob/develop/docs/zh-CN/model_zoo/recognition/stgcn.md) toolkit to complete model training. +- The falling action recognition model uses [ST-GCN](https://arxiv.org/abs/1801.07455), and employ the [PaddleVideo](https://github.com/PaddlePaddle/PaddleVideo/blob/release/2.5/docs/zh-CN/model_zoo/recognition/stgcn.md) toolkit to complete model training. ## Image-Classification-Based Action Recognition -- Calling Recognition @@ -138,7 +138,7 @@ ID_BASED_CLSACTION: # config for classfication-based action recognition model 1. Get the pedestrian detection box and the tracking ID number of the video input through object detection and multi-object tracking. The adopted model is PP-YOLOE, and for details, please refer to [PP-YOLOE](../../../configs/ppyoloe). 2. Capture every pedestrian in frames of the input video accordingly by using the coordinate of the detection box. -3. With image classification through pedestrian images at the frame level, when the category to which the image belongs is the corresponding behavior, it is considered that the character is in the behavior state for a certain period of time. This task is implemented with [PP-HGNet](https://github.com/PaddlePaddle/PaddleClas/blob/develop/docs/zh_CN/models/PP-HGNet.md). In current version, the behavior of calling is supported and the relationship between the action type and `class id` is: +3. With image classification through pedestrian images at the frame level, when the category to which the image belongs is the corresponding behavior, it is considered that the character is in the behavior state for a certain period of time. This task is implemented with [PP-HGNet](https://github.com/PaddlePaddle/PaddleClas/blob/release/2.5/docs/zh_CN/models/PP-HGNet.md). In current version, the behavior of calling is supported and the relationship between the action type and `class id` is: ``` 0: Calling @@ -247,7 +247,7 @@ The result is shown as follow: Data source and copyright owner: Surveillance Camera Fight Dataset. ### Introduction to the Solution -The current fight recognition model is using [PP-TSM](https://github.com/PaddlePaddle/PaddleVideo/blob/develop/docs/zh-CN/model_zoo/recognition/pp-tsm.md), and adaptated to complete the model training. For the input video or video stream, we extraction frame at a certain interval. When the video frame accumulates to the specified number, it is input into the video classification model to determine whether there is fighting. +The current fight recognition model is using [PP-TSM](https://github.com/PaddlePaddle/PaddleVideo/blob/release/2.5/docs/zh-CN/model_zoo/recognition/pp-tsm.md), and adaptated to complete the model training. For the input video or video stream, we extraction frame at a certain interval. When the video frame accumulates to the specified number, it is input into the video classification model to determine whether there is fighting. ## Custom Training diff --git a/deploy/pptracking/README_en.md b/deploy/pptracking/README_en.md index 3352342ad37aefcde90d408cc415738f25b39d75..ca68c61f4d5a54c11f2588476403ba17baa4407b 100644 --- a/deploy/pptracking/README_en.md +++ b/deploy/pptracking/README_en.md @@ -37,7 +37,7 @@ PP-Tracking supports GUI predict and deployment. Please refer to this [doc](http PP-Tracking supports two paradigms: single camera tracking (MOT) and multi-camera tracking (MTMCT). - Single camera tracking supports **FairMOT** and **DeepSORT** two MOT models, multi-camera tracking only support **DeepSORT**. - The applications of single camera tracking include pedestrian tracking, vehicle tracking, multi-class tracking, small object tracking and traffic statistics. The models are mainly optimized based on FairMOT to achieve the effect of real-time tracking. At the same time, PP-Tracking provides pre-training models based on different application scenarios. -- In DeepSORT (including DeepSORT used in multi-camera tracking), the selected detectors are PaddeDetection's self-developed high-performance detector [PP-YOLOv2](../../configs/ppyolo/) and lightweight detector [PP-PicoDet](../../configs/picodet/), and the selected ReID model is PaddleClas's self-developed ultra lightweight backbone [PP-LCNet](https://github.com/PaddlePaddle/PaddleClas/blob/release/2.3/docs/zh_CN/models/PP-LCNet.md) +- In DeepSORT (including DeepSORT used in multi-camera tracking), the selected detectors are PaddeDetection's self-release/2.5ed high-performance detector [PP-YOLOv2](../../configs/ppyolo/) and lightweight detector [PP-PicoDet](../../configs/picodet/), and the selected ReID model is PaddleClas's self-release/2.5ed ultra lightweight backbone [PP-LCNet](https://github.com/PaddlePaddle/PaddleClas/blob/release/2.3/docs/zh_CN/models/PP-LCNet.md) PP-Tracking provids multi-scenario pre-training models and the exported models for deployment: diff --git a/deploy/pptracking/python/README.md b/deploy/pptracking/python/README.md index e56a69e3fe96aba11ed3a50d1173b39c30fc83cf..9c5d97645f25eb4600d914feeba91b509f239695 100644 --- a/deploy/pptracking/python/README.md +++ b/deploy/pptracking/python/README.md @@ -6,7 +6,7 @@ - 导出预测模型 - 基于Python进行预测 -PaddleDetection在训练过程包括网络的前向和优化器相关参数，而在部署过程中，我们只需要前向参数，具体参考:[导出模型](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/deploy/EXPORT_MODEL.md) +PaddleDetection在训练过程包括网络的前向和优化器相关参数，而在部署过程中，我们只需要前向参数，具体参考:[导出模型](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/deploy/EXPORT_MODEL.md) 导出后目录下，包括`infer_cfg.yml`, `model.pdiparams`, `model.pdiparams.info`, `model.pdmodel`四个文件。 PP-Tracking也提供了AI Studio公开项目案例，教程请参考[PP-Tracking之手把手玩转多目标跟踪](https://aistudio.baidu.com/aistudio/projectdetail/3022582)。 diff --git a/deploy/serving/README.md b/deploy/serving/README.md index 5fb6a033f461ccfca88216508275e7eb006e5017..a32efefffcae2d035c5e3d0f296916dc587c8eea 100644 --- a/deploy/serving/README.md +++ b/deploy/serving/README.md @@ -13,7 +13,7 @@ python tools/infer.py -c configs/yolov3/yolov3_darknet53_270e_coco.yml --infer_i 请参考[PaddleServing](https://github.com/PaddlePaddle/Serving/tree/v0.7.0) 中安装教程安装（版本>=0.7.0）。 ## 3. 导出模型 -PaddleDetection在训练过程包括网络的前向和优化器相关参数，而在部署过程中，我们只需要前向参数，具体参考:[导出模型](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/deploy/EXPORT_MODEL.md) +PaddleDetection在训练过程包括网络的前向和优化器相关参数，而在部署过程中，我们只需要前向参数，具体参考:[导出模型](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/deploy/EXPORT_MODEL.md) ``` python tools/export_model.py -c configs/yolov3/yolov3_darknet53_270e_coco.yml -o weights=https://paddledet.bj.bcebos.com/models/yolov3_darknet53_270e_coco.pdparams --export_serving_model=True diff --git a/deploy/serving/cpp/build_server.sh b/deploy/serving/cpp/build_server.sh index 803dce07c1cdb9c6a77f063b7b01391f3109667c..c46bf210b58bc45a7ac9557cc33764732ee3a48f 100644 --- a/deploy/serving/cpp/build_server.sh +++ b/deploy/serving/cpp/build_server.sh @@ -30,7 +30,7 @@ wget https://paddle-qa.bj.bcebos.com/PaddleServing/opencv3.tar.gz && tar -xvf op export OPENCV_DIR=$PWD/opencv3 # clone Serving -git clone https://github.com/PaddlePaddle/Serving.git -b develop --depth=1 +git clone https://github.com/PaddlePaddle/Serving.git -b release/2.5 --depth=1 cd Serving export Serving_repo_path=$PWD git submodule update --init --recursive diff --git a/deploy/third_engine/demo_avh/README.md b/deploy/third_engine/demo_avh/README.md index 69250e5f90a0e48a21e5f360af21e9809f6750db..821749a0871a556e4b989016aebf8f654d44439c 100644 --- a/deploy/third_engine/demo_avh/README.md +++ b/deploy/third_engine/demo_avh/README.md @@ -26,9 +26,9 @@ software will already be installed. If the demo is not run in the ci_cpu Docker container, then you will need the following: - Software required to build and run the demo (These can all be installed by running tvm/docker/install/ubuntu_install_ethosu_driver_stack.sh.) - - [Fixed Virtual Platform (FVP) based on Arm(R) Corstone(TM)-300 software](https://developer.arm.com/tools-and-software/open-source-software/arm-platforms-software/arm-ecosystem-fvps) + - [Fixed Virtual Platform (FVP) based on Arm(R) Corstone(TM)-300 software](https://release/2.5er.arm.com/tools-and-software/open-source-software/arm-platforms-software/arm-ecosystem-fvps) - [cmake 3.19.5](https://github.com/Kitware/CMake/releases/) - - [GCC toolchain from Arm(R)](https://developer.arm.com/-/media/Files/downloads/gnu-rm/10-2020q4/gcc-arm-none-eabi-10-2020-q4-major-x86_64-linux.tar.bz2) + - [GCC toolchain from Arm(R)](https://release/2.5er.arm.com/-/media/Files/downloads/gnu-rm/10-2020q4/gcc-arm-none-eabi-10-2020-q4-major-x86_64-linux.tar.bz2) - [Arm(R) Ethos(TM)-U NPU driver stack](https://review.mlplatform.org) - [CMSIS](https://github.com/ARM-software/CMSIS_5) - The python libraries listed in the requirements.txt of this directory diff --git a/deploy/third_engine/demo_onnxruntime/README.md b/deploy/third_engine/demo_onnxruntime/README.md index bdf7a9432f3e35499c616524b031a27cb2e99fc4..d246ec73d2b2972c5f073d29aec5910c1a7305a9 100644 --- a/deploy/third_engine/demo_onnxruntime/README.md +++ b/deploy/third_engine/demo_onnxruntime/README.md @@ -13,7 +13,7 @@ pip install onnxruntime ## Inference images -- 准备测试模型：根据[PicoDet](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet)中【导出及转换模型】步骤，采用包含后处理的方式导出模型（`-o export.benchmark=False` ），并生成待测试模型简化后的onnx模型（可在下文链接中直接下载）。同时在本目录下新建```onnx_file```文件夹，将导出的onnx模型放在该目录下。 +- 准备测试模型：根据[PicoDet](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet)中【导出及转换模型】步骤，采用包含后处理的方式导出模型（`-o export.benchmark=False` ），并生成待测试模型简化后的onnx模型（可在下文链接中直接下载）。同时在本目录下新建```onnx_file```文件夹，将导出的onnx模型放在该目录下。 - 准备测试所用图片：将待测试图片放在```./imgs```文件夹下，本demo已提供了两张测试图片。 diff --git a/deploy/third_engine/demo_openvino/README.md b/deploy/third_engine/demo_openvino/README.md index 99a3e0f27c519308f915627e66118c965b600e6d..01e7b02c85bcc2828964bc2dd8cca56f1da49ad7 100644 --- a/deploy/third_engine/demo_openvino/README.md +++ b/deploy/third_engine/demo_openvino/README.md @@ -1,13 +1,13 @@ # PicoDet OpenVINO Demo This fold provides PicoDet inference code using -[Intel's OpenVINO Toolkit](https://software.intel.com/content/www/us/en/develop/tools/openvino-toolkit.html). Most of the implements in this fold are same as *demo_ncnn*. +[Intel's OpenVINO Toolkit](https://software.intel.com/content/www/us/en/release/2.5/tools/openvino-toolkit.html). Most of the implements in this fold are same as *demo_ncnn*. **Recommand** to use the xxx.tar.gz file to install instead of github method, [link](https://registrationcenter-download.intel.com/akdlm/irc_nas/18096/l_openvino_toolkit_p_2021.4.689.tgz). ## Install OpenVINO Toolkit -Go to [OpenVINO HomePage](https://software.intel.com/content/www/us/en/develop/tools/openvino-toolkit.html) +Go to [OpenVINO HomePage](https://software.intel.com/content/www/us/en/release/2.5/tools/openvino-toolkit.html) Download a suitable version and install. diff --git a/deploy/third_engine/demo_openvino/python/README.md b/deploy/third_engine/demo_openvino/python/README.md index 1862417db48882b02459dd3b2a425758473f09f2..bdbc99ddf3c00c41e053880fdb969ad3d84d9a6f 100644 --- a/deploy/third_engine/demo_openvino/python/README.md +++ b/deploy/third_engine/demo_openvino/python/README.md @@ -15,9 +15,9 @@ pip install openvino==2022.1.0 ## Benchmark测试 -- 准备测试模型：根据[PicoDet](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet)中【导出及转换模型】步骤，采用不包含后处理的方式导出模型（`-o export.benchmark=True` ），并生成待测试模型简化后的onnx模型（可在下文链接中直接下载）。同时在本目录下新建```out_onnxsim```文件夹，将导出的onnx模型放在该目录下。 +- 准备测试模型：根据[PicoDet](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet)中【导出及转换模型】步骤，采用不包含后处理的方式导出模型（`-o export.benchmark=True` ），并生成待测试模型简化后的onnx模型（可在下文链接中直接下载）。同时在本目录下新建```out_onnxsim```文件夹，将导出的onnx模型放在该目录下。 -- 准备测试所用图片：本demo默认利用PaddleDetection/demo/[000000014439.jpg](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/demo/000000014439.jpg) +- 准备测试所用图片：本demo默认利用PaddleDetection/demo/[000000014439.jpg](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/demo/000000014439.jpg) - 在本目录下直接运行： @@ -31,9 +31,9 @@ python openvino_benchmark.py --img_path ..\..\..\..\demo\000000014439.jpg --onnx ## 真实图片测试(网络包含后处理，但不包含NMS) -- 准备测试模型：根据[PicoDet](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet)中【导出及转换模型】步骤，采用**包含后处理**但**不包含NMS**的方式导出模型（`-o export.benchmark=False export.nms=False` ），并生成待测试模型简化后的onnx模型（可在下文链接中直接下载）。同时在本目录下新建```out_onnxsim_infer```文件夹，将导出的onnx模型放在该目录下。 +- 准备测试模型：根据[PicoDet](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet)中【导出及转换模型】步骤，采用**包含后处理**但**不包含NMS**的方式导出模型（`-o export.benchmark=False export.nms=False` ），并生成待测试模型简化后的onnx模型（可在下文链接中直接下载）。同时在本目录下新建```out_onnxsim_infer```文件夹，将导出的onnx模型放在该目录下。 -- 准备测试所用图片：默认利用../../demo_onnxruntime/imgs/[bus.jpg](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/deploy/third_engine/demo_onnxruntime/imgs/bus.jpg) +- 准备测试所用图片：默认利用../../demo_onnxruntime/imgs/[bus.jpg](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/deploy/third_engine/demo_onnxruntime/imgs/bus.jpg) ```shell # Linux diff --git a/deploy/third_engine/demo_openvino_kpts/README.md b/deploy/third_engine/demo_openvino_kpts/README.md index 9730c4b914359020f637208c4e0a99170bd9b253..218f01de2ade8fbcaf8b188f26354139214d1262 100644 --- a/deploy/third_engine/demo_openvino_kpts/README.md +++ b/deploy/third_engine/demo_openvino_kpts/README.md @@ -1,13 +1,13 @@ # TinyPose OpenVINO Demo This fold provides TinyPose inference code using -[Intel's OpenVINO Toolkit](https://software.intel.com/content/www/us/en/develop/tools/openvino-toolkit.html). Most of the implements in this fold are same as *demo_ncnn*. +[Intel's OpenVINO Toolkit](https://software.intel.com/content/www/us/en/release/2.5/tools/openvino-toolkit.html). Most of the implements in this fold are same as *demo_ncnn*. **Recommand** to use the xxx.tar.gz file to install instead of github method, [link](https://registrationcenter-download.intel.com/akdlm/irc_nas/18096/l_openvino_toolkit_p_2021.4.689.tgz). ## Install OpenVINO Toolkit -Go to [OpenVINO HomePage](https://software.intel.com/content/www/us/en/develop/tools/openvino-toolkit.html) +Go to [OpenVINO HomePage](https://software.intel.com/content/www/us/en/release/2.5/tools/openvino-toolkit.html) Download a suitable version and install. @@ -104,7 +104,7 @@ make Download PicoDet openvino model [PicoDet openvino model download link](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_m_416_openvino.zip). Download TinyPose openvino model [TinyPose openvino model download link](https://paddledet.bj.bcebos.com/deploy/third_engine/tinypose_256_openvino.zip). -move picodet and tinypose openvino model files to the demo's weight folder. +move picodet and tinypose openvino model files to the demo's weight folder. ### Edit file ``` @@ -165,4 +165,3 @@ Model: [Tinypose256_Openvino](https://paddledet.bj.bcebos.com/deploy/third_engin | param | Min | Max | Avg | | ------------- | ----- | ----- | ----- | | infer time(s) | 0.018 | 0.062 | 0.028 | - diff --git a/docs/MODEL_ZOO_cn.md b/docs/MODEL_ZOO_cn.md index b71d07d5c2ea652b16855967236fa9323e2af0ee..7e3fa492504e567f5c8b6d0f01cc52dace27daa6 100644 --- a/docs/MODEL_ZOO_cn.md +++ b/docs/MODEL_ZOO_cn.md @@ -29,109 +29,109 @@ Paddle提供基于ImageNet的骨架网络预训练模型。所有预训练模型 ### Faster R-CNN -请参考[Faster R-CNN](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/faster_rcnn/) +请参考[Faster R-CNN](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/faster_rcnn/) ### Mask R-CNN -请参考[Mask R-CNN](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/) +请参考[Mask R-CNN](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mask_rcnn/) ### Cascade R-CNN -请参考[Cascade R-CNN](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/cascade_rcnn) +请参考[Cascade R-CNN](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/cascade_rcnn) ### YOLOv3 -请参考[YOLOv3](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/) +请参考[YOLOv3](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/) ### SSD -请参考[SSD](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ssd/) +请参考[SSD](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ssd/) ### FCOS -请参考[FCOS](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/fcos/) +请参考[FCOS](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/fcos/) ### SOLOv2 -请参考[SOLOv2](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/solov2/) +请参考[SOLOv2](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/solov2/) ### PP-YOLO -请参考[PP-YOLO](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/) +请参考[PP-YOLO](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/) ### TTFNet -请参考[TTFNet](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ttfnet/) +请参考[TTFNet](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ttfnet/) ### Group Normalization -请参考[Group Normalization](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/gn/) +请参考[Group Normalization](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/gn/) ### Deformable ConvNets v2 -请参考[Deformable ConvNets v2](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/dcn/) +请参考[Deformable ConvNets v2](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/dcn/) ### HRNets -请参考[HRNets](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/hrnet/) +请参考[HRNets](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/hrnet/) ### Res2Net -请参考[Res2Net](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/res2net/) +请参考[Res2Net](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/res2net/) ### GFL -请参考[GFL](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/gfl) +请参考[GFL](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/gfl) ### PicoDet -请参考[PicoDet](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet) +请参考[PicoDet](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet) ### PP-YOLOE -请参考[PP-YOLOE](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyoloe) +请参考[PP-YOLOE](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyoloe) ### YOLOX -请参考[YOLOX](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolox) +请参考[YOLOX](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolox) ## 旋转框检测 ### S2ANet -请参考[S2ANet](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/dota/) +请参考[S2ANet](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/dota/) ## 关键点检测 ### PP-TinyPose -请参考[PP-TinyPose](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/keypoint/tiny_pose) +请参考[PP-TinyPose](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/keypoint/tiny_pose) ## HRNet -请参考[HRNet](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/keypoint/hrnet) +请参考[HRNet](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/keypoint/hrnet) ## HigherHRNet -请参考[HigherHRNet](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/keypoint/higherhrnet) +请参考[HigherHRNet](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/keypoint/higherhrnet) ## 多目标跟踪 ### DeepSORT -请参考[DeepSORT](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/deepsort) +请参考[DeepSORT](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mot/deepsort) ### JDE -请参考[JDE](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/jde) +请参考[JDE](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mot/jde) ### FairMOT -请参考[FairMOT](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/fairmot) +请参考[FairMOT](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mot/fairmot) ### ByteTrack -请参考[ByteTrack](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/bytetrack) +请参考[ByteTrack](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mot/bytetrack) diff --git a/docs/MODEL_ZOO_en.md b/docs/MODEL_ZOO_en.md index fd23b895324f9544e9d007e25f6f607e4340c7b1..31b3a64969b175a9d9ad557d22f29735ec665aa1 100644 --- a/docs/MODEL_ZOO_en.md +++ b/docs/MODEL_ZOO_en.md @@ -28,109 +28,109 @@ Paddle provides a skeleton network pretraining model based on ImageNet. All pre- ### Faster R-CNN -Please refer to[Faster R-CNN](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/faster_rcnn/) +Please refer to[Faster R-CNN](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/faster_rcnn/) ### Mask R-CNN -Please refer to[Mask R-CNN](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/) +Please refer to[Mask R-CNN](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mask_rcnn/) ### Cascade R-CNN -Please refer to[Cascade R-CNN](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/cascade_rcnn) +Please refer to[Cascade R-CNN](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/cascade_rcnn) ### YOLOv3 -Please refer to[YOLOv3](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/) +Please refer to[YOLOv3](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/) ### SSD -Please refer to[SSD](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ssd/) +Please refer to[SSD](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ssd/) ### FCOS -Please refer to[FCOS](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/fcos/) +Please refer to[FCOS](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/fcos/) ### SOLOv2 -Please refer to[SOLOv2](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/solov2/) +Please refer to[SOLOv2](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/solov2/) ### PP-YOLO -Please refer to[PP-YOLO](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/) +Please refer to[PP-YOLO](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyolo/) ### TTFNet -请参考[TTFNet](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ttfnet/) +请参考[TTFNet](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ttfnet/) ### Group Normalization -Please refer to[Group Normalization](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/gn/) +Please refer to[Group Normalization](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/gn/) ### Deformable ConvNets v2 -Please refer to[Deformable ConvNets v2](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/dcn/) +Please refer to[Deformable ConvNets v2](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/dcn/) ### HRNets -Please refer to[HRNets](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/hrnet/) +Please refer to[HRNets](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/hrnet/) ### Res2Net -Please refer to[Res2Net](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/res2net/) +Please refer to[Res2Net](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/res2net/) ### GFL -Please refer to[GFL](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/gfl) +Please refer to[GFL](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/gfl) ### PicoDet -Please refer to[PicoDet](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/picodet) +Please refer to[PicoDet](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet) ### PP-YOLOE -Please refer to[PP-YOLOE](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyoloe) +Please refer to[PP-YOLOE](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyoloe) ### YOLOX -Please refer to[YOLOX](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolox) +Please refer to[YOLOX](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolox) ## Rotating frame detection ### S2ANet -Please refer to[S2ANet](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/dota/) +Please refer to[S2ANet](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/dota/) ## KeyPoint Detection ### PP-TinyPose -Please refer to [PP-TinyPose](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/keypoint/tiny_pose) +Please refer to [PP-TinyPose](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/keypoint/tiny_pose) ## HRNet -Please refer to [HRNet](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/keypoint/hrnet) +Please refer to [HRNet](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/keypoint/hrnet) ## HigherHRNet -Please refer to [HigherHRNet](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/keypoint/higherhrnet) +Please refer to [HigherHRNet](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/keypoint/higherhrnet) ## Multi-Object Tracking ### DeepSORT -Please refer to [DeepSORT](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/deepsort) +Please refer to [DeepSORT](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mot/deepsort) ### JDE -Please refer to [JDE](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/jde) +Please refer to [JDE](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mot/jde) ### FairMOT -Please refer to [FairMOT](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/fairmot) +Please refer to [FairMOT](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mot/fairmot) ### ByteTrack -Please refer to [ByteTrack](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/bytetrack) +Please refer to [ByteTrack](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mot/bytetrack) diff --git a/docs/advanced_tutorials/customization/action_recognotion/README_en.md b/docs/advanced_tutorials/customization/action_recognotion/README_en.md index d04d426b7076abdd38a7317117f5daab6eeff0ad..e332875d3f08dda1bce152480fc2a5f3bc4aa6b8 100644 --- a/docs/advanced_tutorials/customization/action_recognotion/README_en.md +++ b/docs/advanced_tutorials/customization/action_recognotion/README_en.md @@ -2,7 +2,7 @@ # Secondary Development for Action Recognition Task -In the process of industrial implementation, the application of action recognition algorithms will inevitably lead to the need for customized types of action, or the optimization of existing action recognition models to improve the performance of the model in specific scenarios. In view of the diversity of behaviors, PP-Human supports the identification of five abnormal behavioras of smoking, making phone calls, falling, fighting, and people intrusion. At the same time, according to the different behaviors, PP-Human integrates five action recognition technology solutions based on video classification, detection-based, image-based classification, tracking-based and skeleton-based, which can cover 90%+ action type recognition and meet various development needs. In this document, we use a case to introduce how to select a action recognition solution according to the expected behavior, and use PaddleDetection to carry out the secondary development of the action recognition algorithm, including: solution selection, data preparation, model optimization and development process for adding new actions. +In the process of industrial implementation, the application of action recognition algorithms will inevitably lead to the need for customized types of action, or the optimization of existing action recognition models to improve the performance of the model in specific scenarios. In view of the diversity of behaviors, PP-Human supports the identification of five abnormal behavioras of smoking, making phone calls, falling, fighting, and people intrusion. At the same time, according to the different behaviors, PP-Human integrates five action recognition technology solutions based on video classification, detection-based, image-based classification, tracking-based and skeleton-based, which can cover 90%+ action type recognition and meet various release/2.5ment needs. In this document, we use a case to introduce how to select a action recognition solution according to the expected behavior, and use PaddleDetection to carry out the secondary release/2.5ment of the action recognition algorithm, including: solution selection, data preparation, model optimization and release/2.5ment process for adding new actions. ## Solution Selection diff --git a/docs/advanced_tutorials/customization/action_recognotion/idbased_clas.md b/docs/advanced_tutorials/customization/action_recognotion/idbased_clas.md index 51f281835ab0b842a0718d726ae73a533587e82a..c2e3cb9bc3fe85642aae56183799dc7177fb6b1c 100644 --- a/docs/advanced_tutorials/customization/action_recognotion/idbased_clas.md +++ b/docs/advanced_tutorials/customization/action_recognotion/idbased_clas.md @@ -182,7 +182,7 @@ wget https://bj.bcebos.com/v1/paddledet/models/pipeline/infer_configs/PPHGNet_ti 基于人体id的分类的行为识别方案中，将任务转化为对应人物的图像进行图片级别的分类。对应分类的类型最终即视为当前阶段的行为。因此在完成自定义模型的训练及部署的基础上，还需要将分类模型结果转化为最终的行为识别结果作为输出，并修改可视化的显示结果。 #### 转换为行为识别结果 -请对应修改[后处理函数](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/deploy/pipeline/pphuman/action_infer.py#L509)。 +请对应修改[后处理函数](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/deploy/pipeline/pphuman/action_infer.py#L509)。 核心代码为： ```python @@ -220,4 +220,4 @@ else: ``` #### 修改可视化输出 -目前基于ID的行为识别，是根据行为识别的结果及预定义的类别名称进行展示的。详细逻辑请见[此处](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/deploy/pipeline/pipeline.py#L1024-L1043)。如果自定义的行为需要修改为其他的展示名称，请对应修改此处，以正确输出对应结果。 +目前基于ID的行为识别，是根据行为识别的结果及预定义的类别名称进行展示的。详细逻辑请见[此处](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/deploy/pipeline/pipeline.py#L1024-L1043)。如果自定义的行为需要修改为其他的展示名称，请对应修改此处，以正确输出对应结果。 diff --git a/docs/advanced_tutorials/customization/action_recognotion/idbased_clas_en.md b/docs/advanced_tutorials/customization/action_recognotion/idbased_clas_en.md index fc28ccc7029c7ea7f1e63d0ee4f97962747e7ad3..70d24a1ae3e816e068b0ee602da27727bde64fc4 100644 --- a/docs/advanced_tutorials/customization/action_recognotion/idbased_clas_en.md +++ b/docs/advanced_tutorials/customization/action_recognotion/idbased_clas_en.md @@ -182,7 +182,7 @@ At this point, this model can be used in PP-Human. ### Custom Action Output In the model of action recognition based on classification with human id, the task is defined as a picture-level classification task of corresponding person. The type of the corresponding classification is finally regarded as the action type of the current stage. Therefore, on the basis of completing the training and deployment of the custom model, it is also necessary to convert the classification model results to the final action recognition results as output, and the displayed result of the visualization should be modified. -Please modify the [postprocessing function](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/deploy/pipeline/pphuman/action_infer.py#L509). +Please modify the [postprocessing function](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/deploy/pipeline/pphuman/action_infer.py#L509). The core code are: ```python @@ -221,4 +221,4 @@ else: ``` #### Modify Visual Output -At present, ID-based action recognition is displayed based on the results of action recognition and predefined category names. For the detail, please refer to [here](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/deploy/pipeline/pipeline.py#L1024-L1043). If the custom action needs to be modified to another display name, please modify it accordingly to output the corresponding result. +At present, ID-based action recognition is displayed based on the results of action recognition and predefined category names. For the detail, please refer to [here](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/deploy/pipeline/pipeline.py#L1024-L1043). If the custom action needs to be modified to another display name, please modify it accordingly to output the corresponding result. diff --git a/docs/advanced_tutorials/customization/action_recognotion/idbased_det.md b/docs/advanced_tutorials/customization/action_recognotion/idbased_det.md index 02c7d9940c625074f24b8c651c2bcc9f9c138828..5e0b99805bb8af2cf0993239ad26a6821a44e0e1 100644 --- a/docs/advanced_tutorials/customization/action_recognotion/idbased_det.md +++ b/docs/advanced_tutorials/customization/action_recognotion/idbased_det.md @@ -4,7 +4,7 @@ ## 环境准备 -基于人体id的检测方案是直接使用[PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection)的功能进行模型训练的。请按照[安装说明](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/docs/tutorials/INSTALL_cn.md)完成环境安装，以进行后续的模型训练及使用流程。 +基于人体id的检测方案是直接使用[PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection)的功能进行模型训练的。请按照[安装说明](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/docs/tutorials/INSTALL_cn.md)完成环境安装，以进行后续的模型训练及使用流程。 ## 数据准备 基于检测的行为识别方案中，数据准备的流程与一般的检测模型一致，详情可参考[目标检测数据准备](../../../tutorials/data/PrepareDetDataSet.md)。将图像和标注数据组织成PaddleDetection中支持的格式之一即可。 @@ -174,7 +174,7 @@ ppyoloe_crn_s_80e_smoking_visdrone/ 基于人体id的检测的行为识别方案中，将任务转化为在对应人物的图像中检测目标特征对象。当目标特征对象被检测到时，则视为行为正在发生。因此在完成自定义模型的训练及部署的基础上，还需要将检测模型结果转化为最终的行为识别结果作为输出，并修改可视化的显示结果。 #### 转换为行为识别结果 -请对应修改[后处理函数](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/deploy/pipeline/pphuman/action_infer.py#L338)。 +请对应修改[后处理函数](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/deploy/pipeline/pphuman/action_infer.py#L338)。 核心代码为： ```python # 解析检测模型输出，并筛选出置信度高于阈值的有效检测框。 @@ -199,4 +199,4 @@ else: ``` #### 修改可视化输出 -目前基于ID的行为识别，是根据行为识别的结果及预定义的类别名称进行展示的。详细逻辑请见[此处](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/deploy/pipeline/pipeline.py#L1024-L1043)。如果自定义的行为需要修改为其他的展示名称，请对应修改此处，以正确输出对应结果。 +目前基于ID的行为识别，是根据行为识别的结果及预定义的类别名称进行展示的。详细逻辑请见[此处](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/deploy/pipeline/pipeline.py#L1024-L1043)。如果自定义的行为需要修改为其他的展示名称，请对应修改此处，以正确输出对应结果。 diff --git a/docs/advanced_tutorials/customization/action_recognotion/idbased_det_en.md b/docs/advanced_tutorials/customization/action_recognotion/idbased_det_en.md index 49cac4343ae2296d9d97cff16f38002eedbb2dcf..9a2d2c61d178cfc0031ee09738a9793a88b986a1 100644 --- a/docs/advanced_tutorials/customization/action_recognotion/idbased_det_en.md +++ b/docs/advanced_tutorials/customization/action_recognotion/idbased_det_en.md @@ -170,7 +170,7 @@ At this point, this model can be used in PP-Human. In the model of action recognition based on detection with human id, the task is defined to detect target objects in images of corresponding person. When the target object is detected, the behavior type of the character in a certain period of time. The type of the corresponding classification is regarded as the action of the current period. Therefore, on the basis of completing the training and deployment of the custom model, it is also necessary to convert the detection model results to the final action recognition results as output, and the displayed result of the visualization should be modified. #### Convert to Action Recognition Result -Please modify the [postprocessing function](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/deploy/pipeline/pphuman/action_infer.py#L338). +Please modify the [postprocessing function](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/deploy/pipeline/pphuman/action_infer.py#L338). The core code are: ```python @@ -196,4 +196,4 @@ else: ``` #### Modify Visual Output -At present, ID-based action recognition is displayed based on the results of action recognition and predefined category names. For the detail, please refer to [here](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/deploy/pipeline/pipeline.py#L1024-L1043). If the custom action needs to be modified to another display name, please modify it accordingly to output the corresponding result. +At present, ID-based action recognition is displayed based on the results of action recognition and predefined category names. For the detail, please refer to [here](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/deploy/pipeline/pipeline.py#L1024-L1043). If the custom action needs to be modified to another display name, please modify it accordingly to output the corresponding result. diff --git a/docs/advanced_tutorials/customization/action_recognotion/skeletonbased_rec.md b/docs/advanced_tutorials/customization/action_recognotion/skeletonbased_rec.md index 21cca224ba8d794e00d25937e14b6f10aeaf324f..3b18d03e4d6e3ab9408c03640eede8bbd60b0794 100644 --- a/docs/advanced_tutorials/customization/action_recognotion/skeletonbased_rec.md +++ b/docs/advanced_tutorials/customization/action_recognotion/skeletonbased_rec.md @@ -202,4 +202,4 @@ INFERENCE: 基于人体骨骼点的行为识别方案中，模型输出的分类结果即代表了该人物在一定时间段内行为类型。对应分类的类型最终即视为当前阶段的行为。因此在完成自定义模型的训练及部署的基础上，使用模型输出作为最终结果，修改可视化的显示结果即可。 #### 修改可视化输出 -目前基于ID的行为识别，是根据行为识别的结果及预定义的类别名称进行展示的。详细逻辑请见[此处](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/deploy/pipeline/pipeline.py#L1024-L1043)。如果自定义的行为需要修改为其他的展示名称，请对应修改此处，以正确输出对应结果。 +目前基于ID的行为识别，是根据行为识别的结果及预定义的类别名称进行展示的。详细逻辑请见[此处](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/deploy/pipeline/pipeline.py#L1024-L1043)。如果自定义的行为需要修改为其他的展示名称，请对应修改此处，以正确输出对应结果。 diff --git a/docs/advanced_tutorials/customization/action_recognotion/skeletonbased_rec_en.md b/docs/advanced_tutorials/customization/action_recognotion/skeletonbased_rec_en.md index a1e8d1f3ca8096c03cab9bb735306ba0db742474..9daf5eb027175fb604ec6cd26644d4ef6e461d62 100644 --- a/docs/advanced_tutorials/customization/action_recognotion/skeletonbased_rec_en.md +++ b/docs/advanced_tutorials/customization/action_recognotion/skeletonbased_rec_en.md @@ -197,4 +197,4 @@ INFERENCE: In the skeleton-based action recognition, the classification result of the model represents the behavior type of the character in a certain period of time. The type of the corresponding classification is regarded as the action of the current period. Therefore, on the basis of completing the training and deployment of the custom model, the model output is directly used as the final result, and the displayed result of the visualization should be modified. #### Modify Visual Output -At present, ID-based action recognition is displayed based on the results of action recognition and predefined category names. For the detail, please refer to [here](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/deploy/pipeline/pipeline.py#L1024-L1043). If the custom action needs to be modified to another display name, please modify it accordingly to output the corresponding result. +At present, ID-based action recognition is displayed based on the results of action recognition and predefined category names. For the detail, please refer to [here](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/deploy/pipeline/pipeline.py#L1024-L1043). If the custom action needs to be modified to another display name, please modify it accordingly to output the corresponding result. diff --git a/docs/advanced_tutorials/customization/action_recognotion/videobased_rec.md b/docs/advanced_tutorials/customization/action_recognotion/videobased_rec.md index 522eebe3d135a789a7843676ca477ec5e4b23a2c..98df83984b3ffbf036662fb1e5671b8cbf83a545 100644 --- a/docs/advanced_tutorials/customization/action_recognotion/videobased_rec.md +++ b/docs/advanced_tutorials/customization/action_recognotion/videobased_rec.md @@ -138,7 +138,7 @@ python tools/export_model.py -c pptsm_fight_frames_dense.yaml \ 新增行为后，需要对现有的可视化代码进行修改，目前代码支持打架二分类可视化，新增类别后需要根据识别结果自适应可视化推理结果。 -具体修改PaddleDetection中develop/deploy/pipeline/pipeline.py路径下PipePredictor类中visualize_video成员函数。当结果中存在'video_action'数据时，会对行为进行可视化。目前的逻辑是如果推理的类别为1，则为打架行为，进行可视化；否则不进行显示，即"video_action_score"为None。用户新增行为后，可根据类别index和对应的行为设置"video_action_text"字段，目前index=1对应"Fight"。相关代码块如下： +具体修改PaddleDetection中deploy/pipeline/pipeline.py路径下PipePredictor类中visualize_video成员函数。当结果中存在'video_action'数据时，会对行为进行可视化。目前的逻辑是如果推理的类别为1，则为打架行为，进行可视化；否则不进行显示，即"video_action_score"为None。用户新增行为后，可根据类别index和对应的行为设置"video_action_text"字段，目前index=1对应"Fight"。相关代码块如下： ``` video_action_res = result.get('video_action') diff --git a/docs/advanced_tutorials/customization/detection_en.md b/docs/advanced_tutorials/customization/detection_en.md index 003ea152906b947473643b93cf1585b7f32d2155..06706d95522503aa2cb85ab2a74f90836897f31b 100644 --- a/docs/advanced_tutorials/customization/detection_en.md +++ b/docs/advanced_tutorials/customization/detection_en.md @@ -2,7 +2,7 @@ # Customize Object Detection task -In the practical application of object detection algorithms in a specific industry, additional training is often required for practical use. The project iteration will also need to modify categories. This document details how to use PaddleDetection for a customized object detection algorithm. The process includes data preparation, model optimization roadmap, and modifying the category development process. +In the practical application of object detection algorithms in a specific industry, additional training is often required for practical use. The project iteration will also need to modify categories. This document details how to use PaddleDetection for a customized object detection algorithm. The process includes data preparation, model optimization roadmap, and modifying the category release/2.5ment process. ## Data Preparation diff --git a/docs/advanced_tutorials/customization/keypoint_detection.md b/docs/advanced_tutorials/customization/keypoint_detection.md index c54ff231e07a5540d2d93ecda4507803fd81ac21..65e25ede7d3b5134f0f2d684a50d4d60f0282656 100644 --- a/docs/advanced_tutorials/customization/keypoint_detection.md +++ b/docs/advanced_tutorials/customization/keypoint_detection.md @@ -48,7 +48,7 @@ python tools/train.py -c configs/keypoint/hrnet/hrnet_w32_256x192.yml -o pretrai 在关键点模型训练中增加遮挡的数据增强，参考[PP-TinyPose](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.4/configs/keypoint/tiny_pose/tinypose_256x192.yml#L100)。有助于模型提升这类场景下的表现。 ### 对视频预测进行平滑处理 -关键点模型是在图片级别的基础上进行训练和预测的，对于视频类型的输入也是将视频拆分为帧进行预测。帧与帧之间虽然内容大多相似，但微小的差异仍然可能导致模型的输出发生较大的变化，表现为虽然预测的坐标大体正确，但视觉效果上有较大的抖动问题。通过添加滤波平滑处理，将每一帧预测的结果与历史结果综合考虑，得到最终的输出结果，可以有效提升视频上的表现。该部分内容可参考[滤波平滑处理](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/deploy/python/det_keypoint_unite_infer.py#L206)。 +关键点模型是在图片级别的基础上进行训练和预测的，对于视频类型的输入也是将视频拆分为帧进行预测。帧与帧之间虽然内容大多相似，但微小的差异仍然可能导致模型的输出发生较大的变化，表现为虽然预测的坐标大体正确，但视觉效果上有较大的抖动问题。通过添加滤波平滑处理，将每一帧预测的结果与历史结果综合考虑，得到最终的输出结果，可以有效提升视频上的表现。该部分内容可参考[滤波平滑处理](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/deploy/python/det_keypoint_unite_infer.py#L206)。 ## 新增或修改关键点点位定义 @@ -236,7 +236,7 @@ python3 tools/eval.py -c configs/keypoint/hrnet/hrnet_w32_256x192.yml 注意：由于测试依赖pycocotools工具，其默认为`COCO`数据集的17点，如果修改后的模型并非预测17点，直接使用评估命令会报错。 需要修改以下内容以获得正确的评估结果： -- [sigma列表](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/ppdet/modeling/keypoint_utils.py#L219)，表示每个关键点的范围方差，越大则容忍度越高。其长度与预测点数一致。根据实际关键点可信区域设置，区域精确的一般0.25-0.5，例如眼睛。区域范围大的一般0.5-1.0，例如肩膀。若不确定建议0.75。 +- [sigma列表](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/ppdet/modeling/keypoint_utils.py#L219)，表示每个关键点的范围方差，越大则容忍度越高。其长度与预测点数一致。根据实际关键点可信区域设置，区域精确的一般0.25-0.5，例如眼睛。区域范围大的一般0.5-1.0，例如肩膀。若不确定建议0.75。 - [pycocotools sigma列表](https://github.com/cocodataset/cocoapi/blob/master/PythonAPI/pycocotools/cocoeval.py#L523)，含义及内容同上，取值与sigma列表一致。 ### 模型导出及预测 diff --git a/docs/advanced_tutorials/customization/keypoint_detection_en.md b/docs/advanced_tutorials/customization/keypoint_detection_en.md index 5f96ddffe3726530108b9887256f1e1ea2360c60..befe360305b206da6b1839712bc7ecad4cdf625b 100644 --- a/docs/advanced_tutorials/customization/keypoint_detection_en.md +++ b/docs/advanced_tutorials/customization/keypoint_detection_en.md @@ -60,7 +60,7 @@ Augmentation of covered data in keypoint model training to improve model perform The keypoint model is trained and predicted on the basis of image, and video input is also predicted by splitting the video into frames. Although the content is mostly similar between frames, small differences may still lead to large changes in the output of the model. As a result of that, although the predicted coordinates are roughly correct, there may be jitters in the visual effect. -By adding a smoothing filter process, the performance of the video output can be effectively improved by combining the predicted results of each frame and the historical results. For this part, please see [Filter Smoothing](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/deploy/python/det_keypoint_unite_infer.py#L206). +By adding a smoothing filter process, the performance of the video output can be effectively improved by combining the predicted results of each frame and the historical results. For this part, please see [Filter Smoothing](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/deploy/python/det_keypoint_unite_infer.py#L206). ## Add or modify keypoint definition diff --git a/docs/advanced_tutorials/customization/pphuman_attribute.md b/docs/advanced_tutorials/customization/pphuman_attribute.md index 75cdd4aebc22ddaae052c8f9be64e527d9f62fea..1fca3028eb111b398283fdd3ff427ebd9c73c46b 100644 --- a/docs/advanced_tutorials/customization/pphuman_attribute.md +++ b/docs/advanced_tutorials/customization/pphuman_attribute.md @@ -86,7 +86,7 @@ train.txt文件内为所有训练图片名称（相对于根路径的文件路 git clone https://github.com/PaddlePaddle/PaddleClas ``` -需要在配置文件`PaddleClas/blob/develop/ppcls/configs/PULC/person_attribute/PPLCNet_x1_0.yaml`中，修改的配置项如下： +需要在配置文件`PaddleClas/blob/release/2.5/ppcls/configs/PULC/person_attribute/PPLCNet_x1_0.yaml`中，修改的配置项如下： ``` DataLoader: @@ -180,7 +180,7 @@ ATTR: 2)对应修改训练中train.txt所使用的属性数量和名称； -3)修改训练配置，例如``PaddleClas/blob/develop/ppcls/configs/PULC/person_attribute/PPLCNet_x1_0.yaml``文件中的属性数量,详细见上述`修改配置开始训练`部分。 +3)修改训练配置，例如``PaddleClas/blob/release/2.5/ppcls/configs/PULC/person_attribute/PPLCNet_x1_0.yaml``文件中的属性数量,详细见上述`修改配置开始训练`部分。 增加属性示例： diff --git a/docs/advanced_tutorials/customization/pphuman_attribute_en.md b/docs/advanced_tutorials/customization/pphuman_attribute_en.md index 1dd3813ec3ff4c5e9ce66a7952b773e49555e307..4b0f6ce3222a52d8645319906a7835d0c0d86740 100644 --- a/docs/advanced_tutorials/customization/pphuman_attribute_en.md +++ b/docs/advanced_tutorials/customization/pphuman_attribute_en.md @@ -90,7 +90,7 @@ First run the following command to download the training code (for more environm git clone https://github.com/PaddlePaddle/PaddleClas ``` -You need to modify the following configuration in the configuration file `PaddleClas/blob/develop/ppcls/configs/PULC/person_attribute/PPLCNet_x1_0.yaml` +You need to modify the following configuration in the configuration file `PaddleClas/blob/release/2.5/ppcls/configs/PULC/person_attribute/PPLCNet_x1_0.yaml` ``` DataLoader: @@ -196,7 +196,7 @@ If the attributes need to be added or deleted, you need to 2) Modify the number and name of attributes used in train.txt corresponding to the training. -3) Modify the training configuration, for example, the number of attributes in the ``PaddleClas/blob/develop/ppcls/configs/PULC/person_attribute/PPLCNet_x1_0.yaml`` file, for details, please see the ``Modify configuration to start training`` section above. +3) Modify the training configuration, for example, the number of attributes in the ``PaddleClas/blob/release/2.5/ppcls/configs/PULC/person_attribute/PPLCNet_x1_0.yaml`` file, for details, please see the ``Modify configuration to start training`` section above. Example of adding attributes. @@ -209,7 +209,7 @@ Example of adding attributes. 2) Modify the number and name of attributes used in train.txt corresponding to the training. - 3) Modify the training configuration, for example, the number of attributes in the ``PaddleClas/blob/develop/ppcls/configs/PULC/person_attribute/PPLCNet_x1_0.yaml`` file, for details, please see the ``Modify configuration to start training`` section above. + 3) Modify the training configuration, for example, the number of attributes in the ``PaddleClas/blob/release/2.5/ppcls/configs/PULC/person_attribute/PPLCNet_x1_0.yaml`` file, for details, please see the ``Modify configuration to start training`` section above. Example of adding attributes. diff --git a/docs/advanced_tutorials/customization/pphuman_mot_en.md b/docs/advanced_tutorials/customization/pphuman_mot_en.md index 0aaea495663666782a318ccbc945f11169598eff..249c3087b200ba9bb9484f3b30d225c9e7ea23df 100644 --- a/docs/advanced_tutorials/customization/pphuman_mot_en.md +++ b/docs/advanced_tutorials/customization/pphuman_mot_en.md @@ -2,7 +2,7 @@ # Customized multi-object tracking task -When applying multi-object tracking algorithms in industrial applications, there will be inevitable demands for customized types of multi-object tracking or optimization of existing multi-object tracking models to improve the effectiveness of the models in specific scenarios. In this document, we present examples of how to choose a multi-object tracking solution based on the expected identified behavior, and how to use PaddleDetection for further development of multi-object tracking algorithms, including data preparation, model optimization ideas, and the development process of tracking category modification. +When applying multi-object tracking algorithms in industrial applications, there will be inevitable demands for customized types of multi-object tracking or optimization of existing multi-object tracking models to improve the effectiveness of the models in specific scenarios. In this document, we present examples of how to choose a multi-object tracking solution based on the expected identified behavior, and how to use PaddleDetection for further release/2.5ment of multi-object tracking algorithms, including data preparation, model optimization ideas, and the release/2.5ment process of tracking category modification. ## Data Preparation diff --git a/docs/advanced_tutorials/customization/pphuman_mtmct.md b/docs/advanced_tutorials/customization/pphuman_mtmct.md index 0d784e243cb782c2a5152dff3bd3652138391344..212cc5c02c2326e9210b9222798c4fb1ae5a77bc 100644 --- a/docs/advanced_tutorials/customization/pphuman_mtmct.md +++ b/docs/advanced_tutorials/customization/pphuman_mtmct.md @@ -78,7 +78,7 @@ git clone https://github.com/PaddlePaddle/PaddleClas ``` -需要在配置文件[softmax_triplet_with_center.yaml](https://github.com/PaddlePaddle/PaddleClas/blob/develop/ppcls/configs/reid/strong_baseline/softmax_triplet_with_center.yaml)中，修改的配置项如下： +需要在配置文件[softmax_triplet_with_center.yaml](https://github.com/PaddlePaddle/PaddleClas/blob/release/2.5/ppcls/configs/reid/strong_baseline/softmax_triplet_with_center.yaml)中，修改的配置项如下： ``` Head: diff --git a/docs/advanced_tutorials/customization/pphuman_mtmct_en.md b/docs/advanced_tutorials/customization/pphuman_mtmct_en.md index e3638c2700a4cd20d5bcb6f85c6c6d2b610a56ee..5ade886c7def252db141079fd130ed5fe2f72b84 100644 --- a/docs/advanced_tutorials/customization/pphuman_mtmct_en.md +++ b/docs/advanced_tutorials/customization/pphuman_mtmct_en.md @@ -81,7 +81,7 @@ First, execute the following command to download the training code (for more env git clone https://github.com/PaddlePaddle/PaddleClas ``` -You need to change the following configuration items in the configuration file [softmax_triplet_with_center.yaml](https://github.com/PaddlePaddle/PaddleClas/blob/develop/ppcls/configs/reid/strong_ baseline/softmax_triplet_with_center.yaml): +You need to change the following configuration items in the configuration file [softmax_triplet_with_center.yaml](https://github.com/PaddlePaddle/PaddleClas/blob/release/2.5/ppcls/configs/reid/strong_ baseline/softmax_triplet_with_center.yaml): ``` Head: diff --git a/docs/advanced_tutorials/customization/ppvehicle_attribute.md b/docs/advanced_tutorials/customization/ppvehicle_attribute.md index c40c9cb3059ed9834fff89af7a5a3e78cb5a4bec..36e02570522253690effc8300690f00ba09d20ab 100644 --- a/docs/advanced_tutorials/customization/ppvehicle_attribute.md +++ b/docs/advanced_tutorials/customization/ppvehicle_attribute.md @@ -209,7 +209,7 @@ VEHICLE_ATTR: 修改了属性定义后，pipeline后处理部分也需要做相应修改，主要影响结果可视化时的显示结果。 -相应代码在[文件](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/deploy/pipeline/ppvehicle/vehicle_attr.py#L108)中`postprocess`函数。 +相应代码在[文件](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/deploy/pipeline/ppvehicle/vehicle_attr.py#L108)中`postprocess`函数。 其函数实现说明如下： diff --git a/docs/advanced_tutorials/customization/ppvehicle_attribute_en.md b/docs/advanced_tutorials/customization/ppvehicle_attribute_en.md index 69fbc18fbf55081311978008d2b82c50f6f2634a..25def0d650f8694b6294bb682b764570641d9d76 100644 --- a/docs/advanced_tutorials/customization/ppvehicle_attribute_en.md +++ b/docs/advanced_tutorials/customization/ppvehicle_attribute_en.md @@ -223,7 +223,7 @@ The same applies to the deletion of attributes. After modifying the attribute definition, the post-processing part of the pipeline also needs to be modified accordingly, which mainly affects the display results when the results are visualized. -The code is at [file](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/deploy/pipeline/ppvehicle/vehicle_attr.py#L108), that is, the `postprocess` function. +The code is at [file](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/deploy/pipeline/ppvehicle/vehicle_attr.py#L108), that is, the `postprocess` function. The function implementation is described as follows: diff --git a/docs/advanced_tutorials/openvino_inference/README.md b/docs/advanced_tutorials/openvino_inference/README.md index ac372eaa30d1f02a5016b42b928e9c56bfea547a..e6809e7cbbf10a8807d77227c59c9fa77438fcd3 100644 --- a/docs/advanced_tutorials/openvino_inference/README.md +++ b/docs/advanced_tutorials/openvino_inference/README.md @@ -1,11 +1,11 @@ # Using OpenVINO for Inference ## Introduction -PaddleDetection has been a vibrant open-source project and has a large amout of contributors and maintainers around it. It is an AI framework which enables developers to quickly integrate AI capacities into their own projects and applications. +PaddleDetection has been a vibrant open-source project and has a large amout of contributors and maintainers around it. It is an AI framework which enables release/2.5ers to quickly integrate AI capacities into their own projects and applications. Intel OpenVINO is a widely used free toolkit. It facilitates the optimization of a deep learning model from a framework and deployment using an inference engine onto Intel hardware. -Apparently, the upstream(Paddle) and the downstream(Intel OpenVINO) can work together to streamline and simplify the process of developing an AI model and deploying the model onto hardware, which, in turn, makes our lives easier. +Apparently, the upstream(Paddle) and the downstream(Intel OpenVINO) can work together to streamline and simplify the process of release/2.5ing an AI model and deploying the model onto hardware, which, in turn, makes our lives easier. This article will show you how to use a PaddleDetection model [FairMOT](../../../configs/mot/fairmot/README.md) from the Model Zoo in PaddleDetection and use it with OpenVINO to do the inference. diff --git a/docs/feature_models/SSLD_PRETRAINED_MODEL.md b/docs/feature_models/SSLD_PRETRAINED_MODEL.md index e27b69a664a5d19624e61caad5cc079d9de8f602..7b1b2217e2e0358bec05fb8f0e96ebb3ec14b56d 100644 --- a/docs/feature_models/SSLD_PRETRAINED_MODEL.md +++ b/docs/feature_models/SSLD_PRETRAINED_MODEL.md @@ -6,34 +6,34 @@ | 骨架网络 | 网络类型 | 每张GPU图片个数 | 学习率策略 |推理时间(fps) | Box AP | Mask AP | 下载 | 配置文件 | | :------------------- | :------------| :-----: | :-----: | :------------: | :-----: | :-----: | :-----------------------------------------------------: | :-----: | -| ResNet50-vd-SSLDv2-FPN | Faster | 1 | 1x | ---- | 41.4 | - | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/faster_rcnn/faster_rcnn_r50_vd_fpn_ssld_1x_coco.yml) | -| ResNet50-vd-SSLDv2-FPN | Faster | 1 | 2x | ---- | 42.3 | - | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/faster_rcnn/faster_rcnn_r50_vd_fpn_ssld_2x_coco.yml) | -| ResNet50-vd-SSLDv2-FPN | Mask | 1 | 1x | ---- | 42.0 | 38.2 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_r50_vd_fpn_ssld_1x_coco.yml) | -| ResNet50-vd-SSLDv2-FPN | Mask | 1 | 2x | ---- | 42.7 | 38.9 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_r50_vd_fpn_ssld_2x_coco.yml) | -| ResNet50-vd-SSLDv2-FPN | Cascade Faster | 1 | 1x | ---- | 44.4 | - | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/cascade_rcnn/cascade_rcnn_r50_vd_fpn_ssld_1x_coco.yml) | -| ResNet50-vd-SSLDv2-FPN | Cascade Faster | 1 | 2x | ---- | 45.0 | - | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/cascade_rcnn/cascade_rcnn_r50_vd_fpn_ssld_2x_coco.yml) | -| ResNet50-vd-SSLDv2-FPN | Cascade Mask | 1 | 1x | ---- | 44.9 | 39.1 | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_mask_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/cascade_rcnn/cascade_mask_rcnn_r50_vd_fpn_ssld_1x_coco.yml) | -| ResNet50-vd-SSLDv2-FPN | Cascade Mask | 1 | 2x | ---- | 45.7 | 39.7 | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_mask_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/cascade_rcnn/cascade_mask_rcnn_r50_vd_fpn_ssld_2x_coco.yml) | +| ResNet50-vd-SSLDv2-FPN | Faster | 1 | 1x | ---- | 41.4 | - | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/faster_rcnn/faster_rcnn_r50_vd_fpn_ssld_1x_coco.yml) | +| ResNet50-vd-SSLDv2-FPN | Faster | 1 | 2x | ---- | 42.3 | - | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/faster_rcnn/faster_rcnn_r50_vd_fpn_ssld_2x_coco.yml) | +| ResNet50-vd-SSLDv2-FPN | Mask | 1 | 1x | ---- | 42.0 | 38.2 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mask_rcnn/mask_rcnn_r50_vd_fpn_ssld_1x_coco.yml) | +| ResNet50-vd-SSLDv2-FPN | Mask | 1 | 2x | ---- | 42.7 | 38.9 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mask_rcnn/mask_rcnn_r50_vd_fpn_ssld_2x_coco.yml) | +| ResNet50-vd-SSLDv2-FPN | Cascade Faster | 1 | 1x | ---- | 44.4 | - | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/cascade_rcnn/cascade_rcnn_r50_vd_fpn_ssld_1x_coco.yml) | +| ResNet50-vd-SSLDv2-FPN | Cascade Faster | 1 | 2x | ---- | 45.0 | - | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/cascade_rcnn/cascade_rcnn_r50_vd_fpn_ssld_2x_coco.yml) | +| ResNet50-vd-SSLDv2-FPN | Cascade Mask | 1 | 1x | ---- | 44.9 | 39.1 | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_mask_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/cascade_rcnn/cascade_mask_rcnn_r50_vd_fpn_ssld_1x_coco.yml) | +| ResNet50-vd-SSLDv2-FPN | Cascade Mask | 1 | 2x | ---- | 45.7 | 39.7 | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_mask_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/cascade_rcnn/cascade_mask_rcnn_r50_vd_fpn_ssld_2x_coco.yml) | ### YOLOv3 on COCO | 骨架网络 | 输入尺寸 | 每张GPU图片个数 | 学习率策略 |推理时间(fps) | Box AP | 下载 | 配置文件 | | :----------------- | :-------- | :-----------: | :------: | :---------: | :----: | :----------------------------------------------------: | :-----: | -| MobileNet-V1-SSLD | 608 | 8 | 270e | ---- | 31.0 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_coco.yml) | -| MobileNet-V1-SSLD | 416 | 8 | 270e | ---- | 30.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_coco.yml) | -| MobileNet-V1-SSLD | 320 | 8 | 270e | ---- | 28.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_coco.yml) | +| MobileNet-V1-SSLD | 608 | 8 | 270e | ---- | 31.0 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_coco.yml) | +| MobileNet-V1-SSLD | 416 | 8 | 270e | ---- | 30.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_coco.yml) | +| MobileNet-V1-SSLD | 320 | 8 | 270e | ---- | 28.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_coco.yml) | ### YOLOv3 on Pasacl VOC | 骨架网络 | 输入尺寸 | 每张GPU图片个数 | 学习率策略 |推理时间(fps) | Box AP | 下载 | 配置文件 | | :----------------- | :-------- | :-----------: | :------: | :---------: | :----: | :----------------------------------------------------: | :-----: | -| MobileNet-V1-SSLD | 608 | 8 | 270e | - | 78.3 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_voc.yml) | -| MobileNet-V1-SSLD | 416 | 8 | 270e | - | 79.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_voc.yml) | -| MobileNet-V1-SSLD | 320 | 8 | 270e | - | 77.3 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_voc.yml) | -| MobileNet-V3-SSLD | 608 | 8 | 270e | - | 80.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_ssld_270e_voc.yml) | -| MobileNet-V3-SSLD | 416 | 8 | 270e | - | 79.2 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_ssld_270e_voc.yml) | -| MobileNet-V3-SSLD | 320 | 8 | 270e | - | 77.3 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_ssld_270e_voc.yml) | +| MobileNet-V1-SSLD | 608 | 8 | 270e | - | 78.3 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_voc.yml) | +| MobileNet-V1-SSLD | 416 | 8 | 270e | - | 79.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_voc.yml) | +| MobileNet-V1-SSLD | 320 | 8 | 270e | - | 77.3 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_voc.yml) | +| MobileNet-V3-SSLD | 608 | 8 | 270e | - | 80.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v3_large_ssld_270e_voc.yml) | +| MobileNet-V3-SSLD | 416 | 8 | 270e | - | 79.2 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v3_large_ssld_270e_voc.yml) | +| MobileNet-V3-SSLD | 320 | 8 | 270e | - | 77.3 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v3_large_ssld_270e_voc.yml) | **注意事项:** diff --git a/docs/feature_models/SSLD_PRETRAINED_MODEL_en.md b/docs/feature_models/SSLD_PRETRAINED_MODEL_en.md index b97c3b71ee5b8e439181740ea6d7c1a0d7a6d2ba..9c80b7e898c505339cc0e6e6f59492ac00c63733 100644 --- a/docs/feature_models/SSLD_PRETRAINED_MODEL_en.md +++ b/docs/feature_models/SSLD_PRETRAINED_MODEL_en.md @@ -6,33 +6,33 @@ English | [简体中文](SSLD_PRETRAINED_MODEL.md) | Backbone | Model | Images/GPU | Lr schd | FPS | Box AP | Mask AP | Download | Config | | :------------------- | :------------| :-----: | :-----: | :------------: | :-----: | :-----: | :-----------------------------------------------------: | :-----: | -| ResNet50-vd-SSLDv2-FPN | Faster | 1 | 1x | ---- | 41.4 | - | [model](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/faster_rcnn/faster_rcnn_r50_vd_fpn_ssld_1x_coco.yml) | -| ResNet50-vd-SSLDv2-FPN | Faster | 1 | 2x | ---- | 42.3 | - | [model](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/faster_rcnn/faster_rcnn_r50_vd_fpn_ssld_2x_coco.yml) | -| ResNet50-vd-SSLDv2-FPN | Mask | 1 | 1x | ---- | 42.0 | 38.2 | [model](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_r50_vd_fpn_ssld_1x_coco.yml) | -| ResNet50-vd-SSLDv2-FPN | Mask | 1 | 2x | ---- | 42.7 | 38.9 | [model](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_r50_vd_fpn_ssld_2x_coco.yml) | -| ResNet50-vd-SSLDv2-FPN | Cascade Faster | 1 | 1x | ---- | 44.4 | - | [model](https://paddledet.bj.bcebos.com/models/cascade_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/cascade_rcnn/cascade_rcnn_r50_vd_fpn_ssld_1x_coco.yml) | -| ResNet50-vd-SSLDv2-FPN | Cascade Faster | 1 | 2x | ---- | 45.0 | - | [model](https://paddledet.bj.bcebos.com/models/cascade_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/cascade_rcnn/cascade_rcnn_r50_vd_fpn_ssld_2x_coco.yml) | -| ResNet50-vd-SSLDv2-FPN | Cascade Mask | 1 | 1x | ---- | 44.9 | 39.1 | [model](https://paddledet.bj.bcebos.com/models/cascade_mask_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/cascade_rcnn/cascade_mask_rcnn_r50_vd_fpn_ssld_1x_coco.yml) | -| ResNet50-vd-SSLDv2-FPN | Cascade Mask | 1 | 2x | ---- | 45.7 | 39.7 | [model](https://paddledet.bj.bcebos.com/models/cascade_mask_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/cascade_rcnn/cascade_mask_rcnn_r50_vd_fpn_ssld_2x_coco.yml) | +| ResNet50-vd-SSLDv2-FPN | Faster | 1 | 1x | ---- | 41.4 | - | [model](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/faster_rcnn/faster_rcnn_r50_vd_fpn_ssld_1x_coco.yml) | +| ResNet50-vd-SSLDv2-FPN | Faster | 1 | 2x | ---- | 42.3 | - | [model](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/faster_rcnn/faster_rcnn_r50_vd_fpn_ssld_2x_coco.yml) | +| ResNet50-vd-SSLDv2-FPN | Mask | 1 | 1x | ---- | 42.0 | 38.2 | [model](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mask_rcnn/mask_rcnn_r50_vd_fpn_ssld_1x_coco.yml) | +| ResNet50-vd-SSLDv2-FPN | Mask | 1 | 2x | ---- | 42.7 | 38.9 | [model](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/mask_rcnn/mask_rcnn_r50_vd_fpn_ssld_2x_coco.yml) | +| ResNet50-vd-SSLDv2-FPN | Cascade Faster | 1 | 1x | ---- | 44.4 | - | [model](https://paddledet.bj.bcebos.com/models/cascade_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/cascade_rcnn/cascade_rcnn_r50_vd_fpn_ssld_1x_coco.yml) | +| ResNet50-vd-SSLDv2-FPN | Cascade Faster | 1 | 2x | ---- | 45.0 | - | [model](https://paddledet.bj.bcebos.com/models/cascade_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/cascade_rcnn/cascade_rcnn_r50_vd_fpn_ssld_2x_coco.yml) | +| ResNet50-vd-SSLDv2-FPN | Cascade Mask | 1 | 1x | ---- | 44.9 | 39.1 | [model](https://paddledet.bj.bcebos.com/models/cascade_mask_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/cascade_rcnn/cascade_mask_rcnn_r50_vd_fpn_ssld_1x_coco.yml) | +| ResNet50-vd-SSLDv2-FPN | Cascade Mask | 1 | 2x | ---- | 45.7 | 39.7 | [model](https://paddledet.bj.bcebos.com/models/cascade_mask_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/cascade_rcnn/cascade_mask_rcnn_r50_vd_fpn_ssld_2x_coco.yml) | ### YOLOv3 on COCO | Backbone | Input shape | Images/GPU | Lr schd | FPS | Box AP | Download | Config | | :----------------- | :-------- | :-----------: | :------: | :---------: | :----: | :----------------------------------------------------: | :-----: | -| MobileNet-V1-SSLD | 608 | 8 | 270e | ---- | 31.0 | [model](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_coco.yml) | -| MobileNet-V1-SSLD | 416 | 8 | 270e | ---- | 30.6 | [model](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_coco.yml) | -| MobileNet-V1-SSLD | 320 | 8 | 270e | ---- | 28.4 | [model](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_coco.yml) | +| MobileNet-V1-SSLD | 608 | 8 | 270e | ---- | 31.0 | [model](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_coco.yml) | +| MobileNet-V1-SSLD | 416 | 8 | 270e | ---- | 30.6 | [model](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_coco.yml) | +| MobileNet-V1-SSLD | 320 | 8 | 270e | ---- | 28.4 | [model](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_coco.yml) | ### YOLOv3 on Pasacl VOC | Backbone | Input shape | Images/GPU | Lr schd | FPS | Box AP | Download | Config | | :----------------- | :-------- | :-----------: | :------: | :---------: | :----: | :----------------------------------------------------: | :-----: | -| MobileNet-V1-SSLD | 608 | 8 | 270e | - | 78.3 | [model](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_voc.yml) | -| MobileNet-V1-SSLD | 416 | 8 | 270e | - | 79.6 | [model](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_voc.yml) | -| MobileNet-V1-SSLD | 320 | 8 | 270e | - | 77.3 | [model](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_voc.yml) | -| MobileNet-V3-SSLD | 608 | 8 | 270e | - | 80.4 | [model](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_ssld_270e_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_ssld_270e_voc.yml) | -| MobileNet-V3-SSLD | 416 | 8 | 270e | - | 79.2 | [model](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_ssld_270e_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_ssld_270e_voc.yml) | -| MobileNet-V3-SSLD | 320 | 8 | 270e | - | 77.3 | [model](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_ssld_270e_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_ssld_270e_voc.yml) | +| MobileNet-V1-SSLD | 608 | 8 | 270e | - | 78.3 | [model](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_voc.yml) | +| MobileNet-V1-SSLD | 416 | 8 | 270e | - | 79.6 | [model](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_voc.yml) | +| MobileNet-V1-SSLD | 320 | 8 | 270e | - | 77.3 | [model](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_voc.yml) | +| MobileNet-V3-SSLD | 608 | 8 | 270e | - | 80.4 | [model](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_ssld_270e_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v3_large_ssld_270e_voc.yml) | +| MobileNet-V3-SSLD | 416 | 8 | 270e | - | 79.2 | [model](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_ssld_270e_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v3_large_ssld_270e_voc.yml) | +| MobileNet-V3-SSLD | 320 | 8 | 270e | - | 77.3 | [model](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_ssld_270e_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/yolov3/yolov3_mobilenet_v3_large_ssld_270e_voc.yml) | **Notes:** diff --git "a/docs/tutorials/FAQ/FAQ\347\254\254\344\270\200\346\234\237.md" "b/docs/tutorials/FAQ/FAQ\347\254\254\344\270\200\346\234\237.md" index b7926d86d2135772af3e2f7a8c96f24b82d42e13..2ab6675eb1ec55b1f83c7d3c9d9286503e375535 100644 --- "a/docs/tutorials/FAQ/FAQ\347\254\254\344\270\200\346\234\237.md" +++ "b/docs/tutorials/FAQ/FAQ\347\254\254\344\270\200\346\234\237.md" @@ -2,7 +2,7 @@ **Q：**SOLOv2训练mAP值宽幅震荡，无上升趋势，检测效果不好，检测置信度超过了1的原因是？ -**A：** SOLOv2训练不收敛的话，先更新PaddleDetection到release/2.2或者develop分支尝试。 +**A：** SOLOv2训练不收敛的话，先更新PaddleDetection到release/2.2或者release/2.5分支尝试。 @@ -14,7 +14,7 @@ **Q：** 在tools/infer.py加入如下函数，得到FLOPs值为-1,请问原因？ -**A：** 更新PaddleDetection到release/2.2或者develop分支，`print_flops`设为True即可打印FLOPs。 +**A：** 更新PaddleDetection到release/2.2或者release/2.5分支，`print_flops`设为True即可打印FLOPs。 @@ -32,7 +32,7 @@ **Q：** Develop分支下FairMot预测视频问题：预测视频时不会完全运行完毕。比如用一个300frame的视频，代码会保存预测结果的每一帧图片，但只保存到299张就没了，并且也没有预测好的视频文件生成，该如何解决？ -**A：** 已经支持自己设置帧率infer视频，请使用develop分支或release/2.2分支，命令如下： +**A：** 已经支持自己设置帧率infer视频，请使用release/2.5分支或release/2.2分支，命令如下： ``` CUDA_VISIBLE_DEVICES=0 python tools/infer_mot.py -c configs/mot/fairmot/fairmot_dla34_30e_1088x608.yml -o weights=https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608.pdparams --video_file={your video name}.mp4 --frame_rate=20 --save_videos diff --git a/docs/tutorials/INSTALL.md b/docs/tutorials/INSTALL.md index 418289b0d4b34c3e4b3df05adb52c0dc277e33dd..2da0d24bdcd4d147adc695301dcbce25124b5964 100644 --- a/docs/tutorials/INSTALL.md +++ b/docs/tutorials/INSTALL.md @@ -6,7 +6,7 @@ English | [简体中文](INSTALL_cn.md) This document covers how to install PaddleDetection and its dependencies (including PaddlePaddle), together with COCO and Pascal VOC dataset. -For general information about PaddleDetection, please see [README.md](https://github.com/PaddlePaddle/PaddleDetection/tree/develop). +For general information about PaddleDetection, please see [README.md](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5). ## Requirements: @@ -116,7 +116,7 @@ OK We provide docker images containing the latest PaddleDetection code, and all environment and package dependencies are pre-installed. All you have to do is to **pull and run the docker image**. Then you can enjoy PaddleDetection without any extra steps. -Get these images and guidance in [docker hub](https://hub.docker.com/repository/docker/paddlecloud/paddledetection), including CPU, GPU, ROCm environment versions. +Get these images and guidance in [docker hub](https://hub.docker.com/repository/docker/paddlecloud/paddledetection), including CPU, GPU, ROCm environment versions. If you have some customized requirements about automatic building docker images, you can get it in github repo [PaddlePaddle/PaddleCloud](https://github.com/PaddlePaddle/PaddleCloud/tree/main/tekton). diff --git a/docs/tutorials/data/DetAnnoTools.md b/docs/tutorials/data/DetAnnoTools.md index fd7c8fee9124cddc2146cda252a11a9c95bf679f..71e858065548ea6620cfa756eed12df5e934cf7f 100644 --- a/docs/tutorials/data/DetAnnoTools.md +++ b/docs/tutorials/data/DetAnnoTools.md @@ -149,7 +149,7 @@ python labelme2voc.py data_annotated(标注文件所在文件夹) data_dataset_v #### 标注文件(json)-->COCO数据集 -使用[PaddleDetection提供的x2coco.py](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/tools/x2coco.py) 将labelme标注的数据转换为COCO数据集形式 +使用[PaddleDetection提供的x2coco.py](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/tools/x2coco.py) 将labelme标注的数据转换为COCO数据集形式 ```bash python tools/x2coco.py \ @@ -276,4 +276,3 @@ png/jpeg/jpg-->labelImg标注-->xml/txt/json #### 格式转换注意事项 **PaddleDetection支持VOC或COCO格式的数据**，经LabelImg标注导出后的标注文件，需要修改为**VOC或COCO格式**，调整说明可以参考[准备训练数据](./PrepareDataSet.md#%E5%87%86%E5%A4%87%E8%AE%AD%E7%BB%83%E6%95%B0%E6%8D%AE) - diff --git a/docs/tutorials/data/DetAnnoTools_en.md b/docs/tutorials/data/DetAnnoTools_en.md index 7b948d213fc0f1f49c6ee21276220ee94f3496c9..92f78f62d8a32f4e498f424a27f3bdc9c0f02bb9 100644 --- a/docs/tutorials/data/DetAnnoTools_en.md +++ b/docs/tutorials/data/DetAnnoTools_en.md @@ -131,7 +131,7 @@ Use this script [labelme2voc.py](https://github.com/wkentaro/labelme/blob/main/e python labelme2voc.py data_annotated(annotation folder) data_dataset_voc(output folder) --labels labels.txt ``` -Then, it will generate following contents: +Then, it will generate following contents: ``` # It generates: @@ -147,7 +147,7 @@ Then, it will generate following contents: #### Annotation file(json)—>COCO Dataset -Convert the data annotated by LabelMe to COCO dataset by the script [x2coco.py](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/tools/x2coco.py) provided by PaddleDetection. +Convert the data annotated by LabelMe to COCO dataset by the script [x2coco.py](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/tools/x2coco.py) provided by PaddleDetection. ```bash python tools/x2coco.py \ @@ -268,4 +268,3 @@ png/jpeg/jpg-->labelImg-->xml/txt/json #### Notes of Format Conversion **PaddleDetection supports the format of VOC or COCO.** The annotation file generated by LabelImg needs to be converted by VOC or COCO. You can refer to [PrepareDataSet](./PrepareDataSet.md#%E5%87%86%E5%A4%87%E8%AE%AD%E7%BB%83%E6%95%B0%E6%8D%AE). - diff --git a/docs/tutorials/data/KeyPointAnnoTools.md b/docs/tutorials/data/KeyPointAnnoTools.md index 678b94ac7571a76048dc9a232bd288e579a0483a..afe5a6dcb6687caf3cf963f933677c6a1642fc99 100755 --- a/docs/tutorials/data/KeyPointAnnoTools.md +++ b/docs/tutorials/data/KeyPointAnnoTools.md @@ -135,7 +135,7 @@ json-->labelme2coco.py-->COCO数据集 #### 标注文件(json)-->COCO数据集 -使用[PaddleDetection提供的x2coco.py](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/tools/x2coco.py) 将labelme标注的数据转换为COCO数据集形式 +使用[PaddleDetection提供的x2coco.py](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/tools/x2coco.py) 将labelme标注的数据转换为COCO数据集形式 ```bash python tools/x2coco.py \ @@ -162,4 +162,3 @@ dataset/xxx/ │ | ... ... ``` - diff --git a/docs/tutorials/data/KeyPointAnnoTools_en.md b/docs/tutorials/data/KeyPointAnnoTools_en.md index 3ef0548426d79cfd89267cbf6e8087e5dfa407dd..da9cd22fe31759698ac4b4820b813bc78b8c0518 100755 --- a/docs/tutorials/data/KeyPointAnnoTools_en.md +++ b/docs/tutorials/data/KeyPointAnnoTools_en.md @@ -135,7 +135,7 @@ json-->labelme2coco.py-->COCO dataset #### Annotation file(json)—>COCO Dataset -Convert the data annotated by LabelMe to COCO dataset by this script [x2coco.py](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/tools/x2coco.py). +Convert the data annotated by LabelMe to COCO dataset by this script [x2coco.py](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/tools/x2coco.py). ```bash python tools/x2coco.py \ @@ -162,4 +162,3 @@ dataset/xxx/ │ | ... ... ``` - diff --git a/docs/tutorials/data/PrepareDetDataSet_en.md b/docs/tutorials/data/PrepareDetDataSet_en.md index aa8c5f3e183146c078c57e1328008a7fb007001e..3d9570ea7f80bb4f8e8258ed23ea8b257958932b 100644 --- a/docs/tutorials/data/PrepareDetDataSet_en.md +++ b/docs/tutorials/data/PrepareDetDataSet_en.md @@ -330,7 +330,7 @@ dataset/xxx/ ``` ##### Reader of User Define Data - If new data in the dataset needs to be added to paddedetection, you can refer to the [add new data source] (../advanced_tutorials/READER.md#2.3_Customizing_Dataset) document section in the data processing document to develop corresponding code to complete the new data source support. At the same time, you can read the [data processing document] (../advanced_tutorials/READER.md) for specific code analysis of data processing + If new data in the dataset needs to be added to paddedetection, you can refer to the [add new data source] (../advanced_tutorials/READER.md#2.3_Customizing_Dataset) document section in the data processing document to release/2.5 corresponding code to complete the new data source support. At the same time, you can read the [data processing document] (../advanced_tutorials/READER.md) for specific code analysis of data processing The configuration file for the Dataset exists in the `configs/datasets` folder. For example, the COCO dataset configuration file is as follows: ``` diff --git a/ppdet/modeling/heads/roi_extractor.py b/ppdet/modeling/heads/roi_extractor.py index 5d2b1528f07003193b03a02bc1320bfb2d304a6d..260b375d953aeb2e62f2da57c9c2def430136b43 100644 --- a/ppdet/modeling/heads/roi_extractor.py +++ b/ppdet/modeling/heads/roi_extractor.py @@ -29,7 +29,7 @@ class RoIAlign(object): RoI Align module For more details, please refer to the document of roi_align in - in https://github.com/PaddlePaddle/Paddle/blob/develop/python/paddle/vision/ops.py + in https://github.com/PaddlePaddle/Paddle/blob/release/2.5/python/paddle/vision/ops.py Args: resolution (int): The output size, default 14 diff --git a/ppdet/modeling/layers.py b/ppdet/modeling/layers.py index a3253df77485ae1aafec6cfc047db642a0067629..8e0376b860047e8717cd13c8c9418ed60a5647d0 100644 --- a/ppdet/modeling/layers.py +++ b/ppdet/modeling/layers.py @@ -549,7 +549,7 @@ class MultiClassNMS(object): if background_label > -1: kwargs.update({'background_label': background_label}) kwargs.pop('trt') - # TODO(wangxinxin08): paddle version should be develop or 2.3 and above to run nms on tensorrt + # TODO(wangxinxin08): paddle version should be release/2.5 or 2.3 and above to run nms on tensorrt if self.trt and (int(paddle.version.major) == 0 or (int(paddle.version.major) >= 2 and int(paddle.version.minor) >= 3)): @@ -1429,7 +1429,7 @@ class ConvMixer(nn.Layer): Seq, ActBn = nn.Sequential, lambda x: Seq(x, nn.GELU(), nn.BatchNorm2D(dim)) Residual = type('Residual', (Seq, ), {'forward': lambda self, x: self[0](x) + x}) - return Seq(*[ + return Seq(* [ Seq(Residual( ActBn( nn.Conv2D( diff --git a/ppdet/utils/check.py b/ppdet/utils/check.py index 58c48806c82d8616d65f02fec80725dadd45d52b..c7e13683ff072705447766ca6bd1e905aca13822 100644 --- a/ppdet/utils/check.py +++ b/ppdet/utils/check.py @@ -93,7 +93,7 @@ def check_version(version='2.0'): not satisfied. """ err = "PaddlePaddle version {} or higher is required, " \ - "or a suitable develop version is satisfied as well. \n" \ + "or a suitable release/2.5 version is satisfied as well. \n" \ "Please make sure the version is good with your code.".format(version) version_installed = [ diff --git a/ppdet/utils/download.py b/ppdet/utils/download.py index 006733aa79f896e2ba4ebaa8069248c6ac43c1a0..f2134d9669482130fd6b03944c9a95a07fd3c0c2 100644 --- a/ppdet/utils/download.py +++ b/ppdet/utils/download.py @@ -397,7 +397,7 @@ def _download_dist(url, path, md5sum=None): # different machines in the case of multiple machines. # Different nodes will download data, and the same node # will only download data once. - # Reference https://github.com/PaddlePaddle/PaddleClas/blob/develop/ppcls/utils/download.py#L108 + # Reference https://github.com/PaddlePaddle/PaddleClas/blob/release/2.5/ppcls/utils/download.py#L108 rank_id_curr_node = int(os.environ.get("PADDLE_RANK_IN_NODE", 0)) num_trainers = int(env['PADDLE_TRAINERS_NUM']) if num_trainers <= 1: diff --git a/setup.py b/setup.py index ad2da38434a9f41765a3d41d72ffcb2ba8026408..0d52627fdc5a9e6d27a6c983e233b9c8b044fc28 100644 --- a/setup.py +++ b/setup.py @@ -21,7 +21,7 @@ from setuptools import find_packages, setup # ============== version definition ============== -PPDET_VERSION = "2.4.0" +PPDET_VERSION = "2.5.0" def parse_version(): diff --git a/test_tipc/docs/install.md b/test_tipc/docs/install.md index eaac6908dbb9f5c6f394644da438c0a4f8ca60f3..97f3a5625284e8a0675911260a9181cbb2cf44be 100644 --- a/test_tipc/docs/install.md +++ b/test_tipc/docs/install.md @@ -62,7 +62,7 @@ export PADDLE_DIR=/paddle/paddle_inference 如果当前环境满足CUDNN版本的要求，可以跳过此步骤。 -以CUDNN8.1 安装安装为例，安装步骤如下，首先下载CUDNN，从[Nvidia官网](https://developer.nvidia.com/rdp/cudnn-archive)下载CUDNN8.1版本，下载符合当前系统版本的三个deb文件，分别是： +以CUDNN8.1 安装安装为例，安装步骤如下，首先下载CUDNN，从[Nvidia官网](https://release/2.5er.nvidia.com/rdp/cudnn-archive)下载CUDNN8.1版本，下载符合当前系统版本的三个deb文件，分别是： - cuDNN Runtime Library ，如：libcudnn8_8.1.0.77-1+cuda10.2_amd64.deb - cuDNN Developer Library ，如：libcudnn8-dev_8.1.0.77-1+cuda10.2_amd64.deb - cuDNN Code Samples，如：libcudnn8-samples_8.1.0.77-1+cuda10.2_amd64.deb @@ -91,7 +91,7 @@ sudo apt-get install libfreeimage ### 3.2 安装TensorRT -首先，从[Nvidia官网TensorRT板块](https://developer.nvidia.com/tensorrt-getting-started)下载TensorRT，这里选择7.1.3.4版本的TensorRT，注意选择适合自己系统版本和CUDA版本的TensorRT，另外建议下载TAR package的安装包。 +首先，从[Nvidia官网TensorRT板块](https://release/2.5er.nvidia.com/tensorrt-getting-started)下载TensorRT，这里选择7.1.3.4版本的TensorRT，注意选择适合自己系统版本和CUDA版本的TensorRT，另外建议下载TAR package的安装包。 以Ubuntu16.04+CUDA10.2为例，下载并解压后可以参考[官方文档](https://docs.nvidia.com/deeplearning/tensorrt/archives/tensorrt-713/install-guide/index.html#installing-tar)的安装步骤，按照如下步骤安装: ``` diff --git a/test_tipc/docs/test_ptq_inference_python.md b/test_tipc/docs/test_ptq_inference_python.md index 7b1c04c5b01b5d67ba285e88b1b8c9e3361c2b82..a5aec3c2fd462b72c5230d1bb57818fddccafe5f 100644 --- a/test_tipc/docs/test_ptq_inference_python.md +++ b/test_tipc/docs/test_ptq_inference_python.md @@ -41,4 +41,4 @@ Run failed with command - yolov3_darknet53_270e_coco - python3.7 tools/post_quan ## 3. 更多教程 -本文档为功能测试用，更详细的离线量化功能使用教程请参考：[Paddle 离线量化官网教程](https://github.com/PaddlePaddle/PaddleSlim/blob/develop/docs/zh_cn/api_cn/static/quant/quantization_api.rst#quant_post_static) +本文档为功能测试用，更详细的离线量化功能使用教程请参考：[Paddle 离线量化官网教程](https://github.com/PaddlePaddle/PaddleSlim/blob/release/2.5/docs/zh_cn/api_cn/static/quant/quantization_api.rst#quant_post_static) diff --git a/test_tipc/docs/test_serving.md b/test_tipc/docs/test_serving.md index 593c7beabd7c9a535128d3dc201c2341e9880051..6526d42650e7f2a4410dd02db2522de000ff29be 100644 --- a/test_tipc/docs/test_serving.md +++ b/test_tipc/docs/test_serving.md @@ -88,4 +88,4 @@ Run failed with command - xxxxx ## 3. 更多教程 -本文档为功能测试用，更详细的Serving预测使用教程请参考：[PaddleDetection 服务化部署](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/deploy/serving) +本文档为功能测试用，更详细的Serving预测使用教程请参考：[PaddleDetection 服务化部署](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/deploy/serving)