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PaddleDetection
未验证 提交 99c7e3a7 编写于 作者: W wangxinxin08 提交者： GitHub
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configs/ppyolo/README.md
浏览文件 @ 99c7e3a7
...@@ -56,7 +56,7 @@ PP-YOLO improved performance and speed of YOLOv3 with following methods: ...@@ -56,7 +56,7 @@ PP-YOLO improved performance and speed of YOLOv3 with following methods:
**Notes:** **Notes:**
- PP-YOLO is trained on COCO train2017 dataset and evaluated on val2017 & test-dev2017 dataset，Box AP<sup>test</sup> is evaluation results of `mAP(IoU=0.5:0.95)`. - PP-YOLO is trained on COCO train2017 dataset and evaluated on val2017 & test-dev2017 dataset，Box AP<sup>test</sup> 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/release/2.1/static/docs/FAQ.md). - 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/2.1/docs/tutorials/FAQ.md).
- 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 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. - 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) - 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)
...@@ -71,7 +71,7 @@ PP-YOLO improved performance and speed of YOLOv3 with following methods: ...@@ -71,7 +71,7 @@ PP-YOLO improved performance and speed of YOLOv3 with following methods:
**Notes:** **Notes:**
- PP-YOLO_MobileNetV3 is trained on COCO train2017 datast and evaluated on val2017 dataset，Box AP<sup>val</sup> is evaluation results of `mAP(IoU=0.5:0.95)`, Box AP<sup>val</sup> is evaluation results of `mAP(IoU=0.5)`. - PP-YOLO_MobileNetV3 is trained on COCO train2017 datast and evaluated on val2017 dataset，Box AP<sup>val</sup> is evaluation results of `mAP(IoU=0.5:0.95)`, Box AP<sup>val</sup> 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/release/2.1/static/docs/FAQ.md). - 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/2.1/docs/tutorials/FAQ.md).
- PP-YOLO_MobileNetV3 inference speed is tested on Kirin 990 with 1 thread. - PP-YOLO_MobileNetV3 inference speed is tested on Kirin 990 with 1 thread.
### PP-YOLO tiny ### PP-YOLO tiny
...@@ -84,7 +84,7 @@ PP-YOLO improved performance and speed of YOLOv3 with following methods: ...@@ -84,7 +84,7 @@ PP-YOLO improved performance and speed of YOLOv3 with following methods:
**Notes:** **Notes:**
- PP-YOLO-tiny is trained on COCO train2017 datast and evaluated on val2017 dataset，Box AP<sup>val</sup> is evaluation results of `mAP(IoU=0.5:0.95)`, Box AP<sup>val</sup> is evaluation results of `mAP(IoU=0.5)`. - PP-YOLO-tiny is trained on COCO train2017 datast and evaluated on val2017 dataset，Box AP<sup>val</sup> is evaluation results of `mAP(IoU=0.5:0.95)`, Box AP<sup>val</sup> 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/release/2.1/static/docs/FAQ.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/2.1/docs/tutorials/FAQ.md).
- PP-YOLO-tiny inference speed is tested on Kirin 990 with 4 threads by arm8 - 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 - 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
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configs/ppyolo/README_cn.md
浏览文件 @ 99c7e3a7
...@@ -55,7 +55,7 @@ PP-YOLO从如下方面优化和提升YOLOv3模型的精度和速度： ...@@ -55,7 +55,7 @@ PP-YOLO从如下方面优化和提升YOLOv3模型的精度和速度：
**注意:** **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 AP<sup>test</sup>为`mAP(IoU=0.5:0.95)`评估结果。 - 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 AP<sup>test</sup>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/master/docs/FAQ.md)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/2.1/docs/tutorials/FAQ.md)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)。 - 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)。 - 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)。
...@@ -68,7 +68,7 @@ PP-YOLO从如下方面优化和提升YOLOv3模型的精度和速度： ...@@ -68,7 +68,7 @@ PP-YOLO从如下方面优化和提升YOLOv3模型的精度和速度：
| 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/2.1/configs/ppyolo/ppyolo_mbv3_small_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/2.1/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 AP<sup>val</sup>为`mAP(IoU=0.5:0.95)`评估结果, Box AP50<sup>val</sup>为`mAP(IoU=0.5)`评估结果。 - 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 AP<sup>val</sup>为`mAP(IoU=0.5:0.95)`评估结果, Box AP50<sup>val</sup>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/master/docs/FAQ.md)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/2.1/docs/tutorials/FAQ.md)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_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 ### PP-YOLO tiny模型
...@@ -79,7 +79,7 @@ PP-YOLO从如下方面优化和提升YOLOv3模型的精度和速度： ...@@ -79,7 +79,7 @@ PP-YOLO从如下方面优化和提升YOLOv3模型的精度和速度：
| 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/2.1/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/2.1/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 AP<sup>val</sup>为`mAP(IoU=0.5:0.95)`评估结果, Box AP50<sup>val</sup>为`mAP(IoU=0.5)`评估结果。 - 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 AP<sup>val</sup>为`mAP(IoU=0.5:0.95)`评估结果, Box AP50<sup>val</sup>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](../../docs/FAQ.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/2.1/docs/tutorials/FAQ.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。 - 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 - 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
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static/configs/acfpn/README.md
浏览文件 @ 99c7e3a7
...@@ -13,4 +13,4 @@ Cao J, Chen Q, Guo J, et al. Attention-guided Context Feature Pyramid Network fo ...@@ -13,4 +13,4 @@ Cao J, Chen Q, Guo J, et al. Attention-guided Context Feature Pyramid Network fo
| Backbone | Type | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download | Configs | | Backbone | Type | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download | Configs |
| :---------------------- | :-------------: | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: | :-----: | | :---------------------- | :-------------: | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: | :-----: |
| ResNet50-vd-ACFPN | Faster | 2 | 1x | 23.432 | 39.6 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_acfpn_1x.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/acfpn/faster_rcnn_r50_vd_acfpn_1x.yml) | | ResNet50-vd-ACFPN | Faster | 2 | 1x | 23.432 | 39.6 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_acfpn_1x.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/configs/acfpn/faster_rcnn_r50_vd_acfpn_1x.yml) |
static/configs/anchor_free/README.md
浏览文件 @ 99c7e3a7
...@@ -26,14 +26,14 @@ ...@@ -26,14 +26,14 @@
| 网络结构 | 骨干网络 | 图片个数/GPU | 预训练模型 | mAP | FPS | 模型下载 | 配置文件 | | 网络结构 | 骨干网络 | 图片个数/GPU | 预训练模型 | mAP | FPS | 模型下载 | 配置文件 |
|:------------:|:--------:|:----:|:-------:|:-------:|:---------:|:----------:|:----------:| |:------------:|:--------:|:----:|:-------:|:-------:|:---------:|:----------:|:----------:|
| CornerNet-Squeeze | Hourglass104 | 14 | 无 | 34.5 | 35.5 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cornernet_squeeze_hg104.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/anchor_free/cornernet_squeeze_hg104.yml) | | CornerNet-Squeeze | Hourglass104 | 14 | 无 | 34.5 | 35.5 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cornernet_squeeze_hg104.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/anchor_free/cornernet_squeeze_hg104.yml) |
| CornerNet-Squeeze | ResNet50-vd | 14 | [faster\_rcnn\_r50\_vd\_fpn\_2x](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_fpn_2x.tar) | 32.7 | 47.01 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cornernet_squeeze_r50_vd_fpn.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/anchor_free/cornernet_squeeze_r50_vd_fpn.yml) | | CornerNet-Squeeze | ResNet50-vd | 14 | [faster\_rcnn\_r50\_vd\_fpn\_2x](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_fpn_2x.tar) | 32.7 | 47.01 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cornernet_squeeze_r50_vd_fpn.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/anchor_free/cornernet_squeeze_r50_vd_fpn.yml) |
| CornerNet-Squeeze-dcn | ResNet50-vd | 14 | [faster\_rcnn\_dcn\_r50\_vd\_fpn\_2x](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_r50_vd_fpn_2x.tar) | 34.9 | 40.43 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cornernet_squeeze_dcn_r50_vd_fpn.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/anchor_free/cornernet_squeeze_dcn_r50_vd_fpn.yml) | | CornerNet-Squeeze-dcn | ResNet50-vd | 14 | [faster\_rcnn\_dcn\_r50\_vd\_fpn\_2x](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_r50_vd_fpn_2x.tar) | 34.9 | 40.43 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cornernet_squeeze_dcn_r50_vd_fpn.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/anchor_free/cornernet_squeeze_dcn_r50_vd_fpn.yml) |
| CornerNet-Squeeze-dcn-mixup-cosine* | ResNet50-vd | 14 | [faster\_rcnn\_dcn\_r50\_vd\_fpn\_2x](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_r50_vd_fpn_2x.tar) | 38.2 | 39.70 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cornernet_squeeze_dcn_r50_vd_fpn_mixup_cosine.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/anchor_free/cornernet_squeeze_dcn_r50_vd_fpn_mixup_cosine.yml) | | CornerNet-Squeeze-dcn-mixup-cosine* | ResNet50-vd | 14 | [faster\_rcnn\_dcn\_r50\_vd\_fpn\_2x](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_r50_vd_fpn_2x.tar) | 38.2 | 39.70 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cornernet_squeeze_dcn_r50_vd_fpn_mixup_cosine.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/anchor_free/cornernet_squeeze_dcn_r50_vd_fpn_mixup_cosine.yml) |
| FCOS | ResNet50 | 2 | [ResNet50\_cos\_pretrained](https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_cos_pretrained.tar) | 39.8 | 18.85 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/fcos_r50_fpn_1x.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/anchor_free/fcos_r50_fpn_1x.yml) | | FCOS | ResNet50 | 2 | [ResNet50\_cos\_pretrained](https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_cos_pretrained.tar) | 39.8 | 18.85 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/fcos_r50_fpn_1x.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/anchor_free/fcos_r50_fpn_1x.yml) |
| FCOS+multiscale_train | ResNet50 | 2 | [ResNet50\_cos\_pretrained](https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_cos_pretrained.tar) | 42.0 | 19.05 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/fcos_r50_fpn_multiscale_2x.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/anchor_free/fcos_r50_fpn_multiscale_2x.yml) | | FCOS+multiscale_train | ResNet50 | 2 | [ResNet50\_cos\_pretrained](https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_cos_pretrained.tar) | 42.0 | 19.05 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/fcos_r50_fpn_multiscale_2x.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/anchor_free/fcos_r50_fpn_multiscale_2x.yml) |
| FCOS+DCN | ResNet50 | 2 | [ResNet50\_cos\_pretrained](https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_cos_pretrained.tar) | 44.4 | 13.66 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/fcos_dcn_r50_fpn_1x.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/anchor_free/fcos_dcn_r50_fpn_1x.yml) | | FCOS+DCN | ResNet50 | 2 | [ResNet50\_cos\_pretrained](https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_cos_pretrained.tar) | 44.4 | 13.66 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/fcos_dcn_r50_fpn_1x.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/anchor_free/fcos_dcn_r50_fpn_1x.yml) |
| TTFNet | DarkNet53 | 12 | [DarkNet53_pretrained](https://paddle-imagenet-models-name.bj.bcebos.com/DarkNet53_pretrained.tar) | 32.9 | 85.92 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ttfnet_darknet.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/anchor_free/ttfnet_darknet.yml) | | TTFNet | DarkNet53 | 12 | [DarkNet53_pretrained](https://paddle-imagenet-models-name.bj.bcebos.com/DarkNet53_pretrained.tar) | 32.9 | 85.92 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ttfnet_darknet.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/anchor_free/ttfnet_darknet.yml) |
**注意:** **注意:**
......
static/configs/autoaugment/README.md
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| Backbone | Type | AutoAug policy | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download | Configs | | Backbone | Type | AutoAug policy | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download | Configs |
| :---------------------- | :-------------:| :-------: | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: | :-----: | | :---------------------- | :-------------:| :-------: | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: | :-----: |
| ResNet50-vd-FPN | Faster | v1 | 2 | 3x | 22.800 | 39.9 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_fpn_aa_3x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/autoaugment/faster_rcnn_r50_vd_fpn_aa_3x.yml) | | ResNet50-vd-FPN | Faster | v1 | 2 | 3x | 22.800 | 39.9 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_fpn_aa_3x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/autoaugment/faster_rcnn_r50_vd_fpn_aa_3x.yml) |
| ResNet101-vd-FPN | Faster | v1 | 2 | 3x | 17.652 | 42.5 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_vd_fpn_aa_3x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/autoaugment/faster_rcnn_r101_vd_fpn_aa_3x.yml) | | ResNet101-vd-FPN | Faster | v1 | 2 | 3x | 17.652 | 42.5 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_vd_fpn_aa_3x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/autoaugment/faster_rcnn_r101_vd_fpn_aa_3x.yml) |
static/configs/gcnet/README.md
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...@@ -30,5 +30,5 @@ ...@@ -30,5 +30,5 @@
| Backbone | Type | Context| Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download | Configs | | Backbone | Type | Context| Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download | Configs |
| :---------------------- | :-------------: | :-------------: | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: | :-----: | | :---------------------- | :-------------: | :-------------: | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: | :-----: |
| ResNet50-vd-FPN | Mask | GC(c3-c5, r16, add) | 2 | 2x | 15.31 | 41.4 | 36.8 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_vd_fpn_gcb_add_r16_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/gcnet/mask_rcnn_r50_vd_fpn_gcb_add_r16_2x.yml) | | ResNet50-vd-FPN | Mask | GC(c3-c5, r16, add) | 2 | 2x | 15.31 | 41.4 | 36.8 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_vd_fpn_gcb_add_r16_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/gcnet/mask_rcnn_r50_vd_fpn_gcb_add_r16_2x.yml) |
| ResNet50-vd-FPN | Mask | GC(c3-c5, r16, mul) | 2 | 2x | 15.35 | 40.7 | 36.1 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_vd_fpn_gcb_mul_r16_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/gcnet/mask_rcnn_r50_vd_fpn_gcb_mul_r16_2x.yml) | | ResNet50-vd-FPN | Mask | GC(c3-c5, r16, mul) | 2 | 2x | 15.35 | 40.7 | 36.1 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_vd_fpn_gcb_mul_r16_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/gcnet/mask_rcnn_r50_vd_fpn_gcb_mul_r16_2x.yml) |
static/configs/gcnet/README_cn.md
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...@@ -42,8 +42,8 @@ SNL模块可以抽象为上下文建模、特征转换和特征聚合三个部 ...@@ -42,8 +42,8 @@ SNL模块可以抽象为上下文建模、特征转换和特征聚合三个部
| 骨架网络 | 网络类型 | Context设置 | 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 | | 骨架网络 | 网络类型 | Context设置 | 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 | Mask | GC(c3-c5, r16, add) | 2 | 2x | 15.31 | 41.4 | 36.8 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_vd_fpn_gcb_add_r16_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/gcnet/mask_rcnn_r50_vd_fpn_gcb_add_r16_2x.yml) | | ResNet50-vd-FPN | Mask | GC(c3-c5, r16, add) | 2 | 2x | 15.31 | 41.4 | 36.8 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_vd_fpn_gcb_add_r16_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/gcnet/mask_rcnn_r50_vd_fpn_gcb_add_r16_2x.yml) |
| ResNet50-vd-FPN | Mask | GC(c3-c5, r16, mul) | 2 | 2x | 15.35 | 40.7 | 36.1 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_vd_fpn_gcb_mul_r16_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/gcnet/mask_rcnn_r50_vd_fpn_gcb_mul_r16_2x.yml) | | ResNet50-vd-FPN | Mask | GC(c3-c5, r16, mul) | 2 | 2x | 15.35 | 40.7 | 36.1 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_vd_fpn_gcb_mul_r16_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/gcnet/mask_rcnn_r50_vd_fpn_gcb_mul_r16_2x.yml) |
## 引用 ## 引用
......
static/configs/gridmask/README.md
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| Backbone | Type | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download | Configs | | Backbone | Type | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download | Configs |
| :---------------------- | :-------------: | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: | :-----: | | :---------------------- | :-------------: | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: | :-----: |
| ResNet50-vd-FPN | Faster | 2 | 4x | 21.847 | 39.1% | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_fpn_gridmask_4x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/gridmask/faster_rcnn_r50_vd_fpn_gridmask_4x.yml) | | ResNet50-vd-FPN | Faster | 2 | 4x | 21.847 | 39.1% | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_fpn_gridmask_4x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/gridmask/faster_rcnn_r50_vd_fpn_gridmask_4x.yml) |
static/configs/hrnet/README.md
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...@@ -30,5 +30,5 @@ ...@@ -30,5 +30,5 @@
| Backbone | Type | deformable Conv | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download | Configs | | Backbone | Type | deformable Conv | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download | Configs |
| :---------------------- | :------------- | :---: | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: | :-----: | | :---------------------- | :------------- | :---: | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: | :-----: |
| HRNetV2p_W18 | Faster | False | 2 | 1x | 17.509 | 36.0 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_hrnetv2p_w18_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/hrnet/faster_rcnn_hrnetv2p_w18_1x.yml) | | HRNetV2p_W18 | Faster | False | 2 | 1x | 17.509 | 36.0 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_hrnetv2p_w18_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/hrnet/faster_rcnn_hrnetv2p_w18_1x.yml) |
| HRNetV2p_W18 | Faster | False | 2 | 2x | 17.509 | 38.0 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_hrnetv2p_w18_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/hrnet/faster_rcnn_hrnetv2p_w18_2x.yml) | | HRNetV2p_W18 | Faster | False | 2 | 2x | 17.509 | 38.0 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_hrnetv2p_w18_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/hrnet/faster_rcnn_hrnetv2p_w18_2x.yml) |
static/configs/iou_loss/README.md
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...@@ -43,6 +43,6 @@ ...@@ -43,6 +43,6 @@
| Backbone | Type | Loss Type | Loss Weight | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download | Configs | | Backbone | Type | Loss Type | Loss Weight | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download | Configs |
| :---------------------- | :------------- | :---: | :---: | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: | :---: | | :---------------------- | :------------- | :---: | :---: | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: | :---: |
| ResNet50-vd-FPN | Faster | GIOU | 10 | 2 | 1x | 22.94 | 39.4 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_fpn_giou_loss_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/iou_loss/faster_rcnn_r50_vd_fpn_giou_loss_1x.yml) | | ResNet50-vd-FPN | Faster | GIOU | 10 | 2 | 1x | 22.94 | 39.4 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_fpn_giou_loss_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/iou_loss/faster_rcnn_r50_vd_fpn_giou_loss_1x.yml) |
| ResNet50-vd-FPN | Faster | DIOU | 12 | 2 | 1x | 22.94 | 39.2 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_fpn_diou_loss_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/iou_loss/faster_rcnn_r50_vd_fpn_diou_loss_1x.yml) | | ResNet50-vd-FPN | Faster | DIOU | 12 | 2 | 1x | 22.94 | 39.2 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_fpn_diou_loss_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/iou_loss/faster_rcnn_r50_vd_fpn_diou_loss_1x.yml) |
| ResNet50-vd-FPN | Faster | CIOU | 12 | 2 | 1x | 22.95 | 39.6 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_fpn_ciou_loss_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/iou_loss/faster_rcnn_r50_vd_fpn_ciou_loss_1x.yml) | | ResNet50-vd-FPN | Faster | CIOU | 12 | 2 | 1x | 22.95 | 39.6 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_fpn_ciou_loss_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/iou_loss/faster_rcnn_r50_vd_fpn_ciou_loss_1x.yml) |
static/configs/iou_loss/README_cn.md
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...@@ -83,9 +83,9 @@ CIOU loss使得在边框回归时，与目标框有重叠甚至包含时能够 ...@@ -83,9 +83,9 @@ CIOU loss使得在边框回归时，与目标框有重叠甚至包含时能够
| 骨架网络 | 网络类型 | Loss类型 | Loss权重 | 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 | | 骨架网络 | 网络类型 | Loss类型 | Loss权重 | 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 | Faster | GIOU | 10 | 2 | 1x | 22.94 | 39.4 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_fpn_giou_loss_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/iou_loss/faster_rcnn_r50_vd_fpn_giou_loss_1x.yml) | | ResNet50-vd-FPN | Faster | GIOU | 10 | 2 | 1x | 22.94 | 39.4 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_fpn_giou_loss_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/iou_loss/faster_rcnn_r50_vd_fpn_giou_loss_1x.yml) |
| ResNet50-vd-FPN | Faster | DIOU | 12 | 2 | 1x | 22.94 | 39.2 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_fpn_diou_loss_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/iou_loss/faster_rcnn_r50_vd_fpn_diou_loss_1x.yml) | | ResNet50-vd-FPN | Faster | DIOU | 12 | 2 | 1x | 22.94 | 39.2 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_fpn_diou_loss_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/iou_loss/faster_rcnn_r50_vd_fpn_diou_loss_1x.yml) |
| ResNet50-vd-FPN | Faster | CIOU | 12 | 2 | 1x | 22.95 | 39.6 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_fpn_ciou_loss_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/iou_loss/faster_rcnn_r50_vd_fpn_ciou_loss_1x.yml) | | ResNet50-vd-FPN | Faster | CIOU | 12 | 2 | 1x | 22.95 | 39.6 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_fpn_ciou_loss_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/iou_loss/faster_rcnn_r50_vd_fpn_ciou_loss_1x.yml) |
......
static/configs/libra_rcnn/README.md
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...@@ -19,5 +19,5 @@ ...@@ -19,5 +19,5 @@
| Backbone | Type | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download | Configs | | Backbone | Type | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download | Configs |
| :---------------------- | :-------------: | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: | :-----: | | :---------------------- | :-------------: | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: | :-----: |
| ResNet50-vd-BFP | Faster | 2 | 1x | 18.247 | 40.5 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/libra_rcnn_r50_vd_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/libra_rcnn/libra_rcnn_r50_vd_fpn_1x.yml) | | ResNet50-vd-BFP | Faster | 2 | 1x | 18.247 | 40.5 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/libra_rcnn_r50_vd_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/libra_rcnn/libra_rcnn_r50_vd_fpn_1x.yml) |
| ResNet101-vd-BFP | Faster | 2 | 1x | 14.865 | 42.5 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/libra_rcnn_r101_vd_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/libra_rcnn/libra_rcnn_r101_vd_fpn_1x.yml) | | ResNet101-vd-BFP | Faster | 2 | 1x | 14.865 | 42.5 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/libra_rcnn_r101_vd_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/libra_rcnn/libra_rcnn_r101_vd_fpn_1x.yml) |
static/configs/libra_rcnn/README_cn.md
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...@@ -60,8 +60,8 @@ Faster RCNN中生成许多候选框之后，使用随机的方法挑选正负样 ...@@ -60,8 +60,8 @@ Faster RCNN中生成许多候选框之后，使用随机的方法挑选正负样
| 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 | | 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-BFP | Faster | 2 | 1x | 18.247 | 40.5 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/libra_rcnn_r50_vd_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/libra_rcnn/libra_rcnn_r50_vd_fpn_1x.yml) | | ResNet50-vd-BFP | Faster | 2 | 1x | 18.247 | 40.5 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/libra_rcnn_r50_vd_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/libra_rcnn/libra_rcnn_r50_vd_fpn_1x.yml) |
| ResNet101-vd-BFP | Faster | 2 | 1x | 14.865 | 42.5 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/libra_rcnn_r101_vd_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/libra_rcnn/libra_rcnn_r101_vd_fpn_1x.yml) | | ResNet101-vd-BFP | Faster | 2 | 1x | 14.865 | 42.5 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/libra_rcnn_r101_vd_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/libra_rcnn/libra_rcnn_r101_vd_fpn_1x.yml) |
## 引用 ## 引用
......
static/configs/ppyolo/README.md
浏览文件 @ 99c7e3a7
...@@ -38,23 +38,23 @@ PP-YOLO improved performance and speed of YOLOv3 with following methods: ...@@ -38,23 +38,23 @@ PP-YOLO improved performance and speed of YOLOv3 with following methods:
| Model | GPU number | images/GPU | backbone | input shape | Box AP<sup>val</sup> | Box AP<sup>test</sup> | V100 FP32(FPS) | V100 TensorRT FP16(FPS) | download | config | | Model | GPU number | images/GPU | backbone | input shape | Box AP<sup>val</sup> | Box AP<sup>test</sup> | V100 FP32(FPS) | V100 TensorRT FP16(FPS) | download | config |
|:------------------------:|:----------:|:----------:|:----------:| :----------:| :------------------: | :-------------------: | :------------: | :---------------------: | :------: | :-----: | |:------------------------:|:----------:|:----------:|:----------:| :----------:| :------------------: | :-------------------: | :------------: | :---------------------: | :------: | :-----: |
| YOLOv4(AlexyAB) | - | - | CSPDarknet | 608 | - | 43.5 | 62 | 105.5 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov4_cspdarknet.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/yolov4/yolov4_csdarknet.yml) | | YOLOv4(AlexyAB) | - | - | CSPDarknet | 608 | - | 43.5 | 62 | 105.5 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov4_cspdarknet.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov4/yolov4_csdarknet.yml) |
| YOLOv4(AlexyAB) | - | - | CSPDarknet | 512 | - | 43.0 | 83 | 138.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov4_cspdarknet.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/yolov4/yolov4_csdarknet.yml) | | YOLOv4(AlexyAB) | - | - | CSPDarknet | 512 | - | 43.0 | 83 | 138.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov4_cspdarknet.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov4/yolov4_csdarknet.yml) |
| YOLOv4(AlexyAB) | - | - | CSPDarknet | 416 | - | 41.2 | 96 | 164.0 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov4_cspdarknet.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/yolov4/yolov4_csdarknet.yml) | | YOLOv4(AlexyAB) | - | - | CSPDarknet | 416 | - | 41.2 | 96 | 164.0 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov4_cspdarknet.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov4/yolov4_csdarknet.yml) |
| YOLOv4(AlexyAB) | - | - | CSPDarknet | 320 | - | 38.0 | 123 | 199.0 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov4_cspdarknet.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/yolov4/yolov4_csdarknet.yml) | | YOLOv4(AlexyAB) | - | - | CSPDarknet | 320 | - | 38.0 | 123 | 199.0 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov4_cspdarknet.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov4/yolov4_csdarknet.yml) |
| PP-YOLO | 8 | 24 | ResNet50vd | 608 | 44.8 | 45.2 | 72.9 | 155.6 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolo.yml) | | PP-YOLO | 8 | 24 | ResNet50vd | 608 | 44.8 | 45.2 | 72.9 | 155.6 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolo.yml) |
| PP-YOLO | 8 | 24 | ResNet50vd | 512 | 43.9 | 44.4 | 89.9 | 188.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolo.yml) | | PP-YOLO | 8 | 24 | ResNet50vd | 512 | 43.9 | 44.4 | 89.9 | 188.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolo.yml) |
| PP-YOLO | 8 | 24 | ResNet50vd | 416 | 42.1 | 42.5 | 109.1 | 215.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolo.yml) | | PP-YOLO | 8 | 24 | ResNet50vd | 416 | 42.1 | 42.5 | 109.1 | 215.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolo.yml) |
| PP-YOLO | 8 | 24 | ResNet50vd | 320 | 38.9 | 39.3 | 132.2 | 242.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolo.yml) | | PP-YOLO | 8 | 24 | ResNet50vd | 320 | 38.9 | 39.3 | 132.2 | 242.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolo.yml) |
| PP-YOLO_2x | 8 | 24 | ResNet50vd | 608 | 45.3 | 45.9 | 72.9 | 155.6 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_2x.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolo_2x.yml) | | PP-YOLO_2x | 8 | 24 | ResNet50vd | 608 | 45.3 | 45.9 | 72.9 | 155.6 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_2x.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolo_2x.yml) |
| PP-YOLO_2x | 8 | 24 | ResNet50vd | 512 | 44.4 | 45.0 | 89.9 | 188.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_2x.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolo_2x.yml) | | PP-YOLO_2x | 8 | 24 | ResNet50vd | 512 | 44.4 | 45.0 | 89.9 | 188.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_2x.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolo_2x.yml) |
| PP-YOLO_2x | 8 | 24 | ResNet50vd | 416 | 42.7 | 43.2 | 109.1 | 215.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_2x.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolo_2x.yml) | | PP-YOLO_2x | 8 | 24 | ResNet50vd | 416 | 42.7 | 43.2 | 109.1 | 215.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_2x.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolo_2x.yml) |
| PP-YOLO_2x | 8 | 24 | ResNet50vd | 320 | 39.5 | 40.1 | 132.2 | 242.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_2x.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolo_2x.yml) | | PP-YOLO_2x | 8 | 24 | ResNet50vd | 320 | 39.5 | 40.1 | 132.2 | 242.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_2x.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolo_2x.yml) |
| PP-YOLO | 4 | 32 | ResNet18vd | 512 | 29.3 | 29.5 | 357.1 | 657.9 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_r18vd.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolo_r18vd.yml) | | PP-YOLO | 4 | 32 | ResNet18vd | 512 | 29.3 | 29.5 | 357.1 | 657.9 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_r18vd.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolo_r18vd.yml) |
| PP-YOLO | 4 | 32 | ResNet18vd | 416 | 28.6 | 28.9 | 409.8 | 719.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_r18vd.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolo_r18vd.yml) | | PP-YOLO | 4 | 32 | ResNet18vd | 416 | 28.6 | 28.9 | 409.8 | 719.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_r18vd.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolo_r18vd.yml) |
| PP-YOLO | 4 | 32 | ResNet18vd | 320 | 26.2 | 26.4 | 480.7 | 763.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_r18vd.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolo_r18vd.yml) | | PP-YOLO | 4 | 32 | ResNet18vd | 320 | 26.2 | 26.4 | 480.7 | 763.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_r18vd.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolo_r18vd.yml) |
| PP-YOLOv2 | 8 | 12 | ResNet50vd | 640 | 49.1 | 49.5 | 68.9 | 106.5 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolov2_r50vd_dcn.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolov2_r50vd_dcn.yml) | | PP-YOLOv2 | 8 | 12 | ResNet50vd | 640 | 49.1 | 49.5 | 68.9 | 106.5 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolov2_r50vd_dcn.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolov2_r50vd_dcn.yml) |
| PP-YOLOv2 | 8 | 12 | ResNet101vd | 640 | 49.7 | 50.3 | 49.5 | 87.0 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolov2_r101vd_dcn.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolov2_r101vd_dcn.yml) | | PP-YOLOv2 | 8 | 12 | ResNet101vd | 640 | 49.7 | 50.3 | 49.5 | 87.0 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolov2_r101vd_dcn.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolov2_r101vd_dcn.yml) |
**Notes:** **Notes:**
...@@ -72,8 +72,8 @@ PP-YOLO improved performance and speed of YOLOv3 with following methods: ...@@ -72,8 +72,8 @@ PP-YOLO improved performance and speed of YOLOv3 with following methods:
| Model | GPU number | images/GPU | Model Size | input shape | Box AP<sup>val</sup> | Box AP50<sup>val</sup> | Kirin 990 1xCore(FPS) | download | inference model download | config | | Model | GPU number | images/GPU | Model Size | input shape | Box AP<sup>val</sup> | Box AP50<sup>val</sup> | Kirin 990 1xCore(FPS) | download | inference model download | config |
|:----------------------------:|:----------:|:----------:| :--------: | :----------:| :------------------: | :--------------------: | :-------------------: | :------: | :----------------------: | :-----: | |:----------------------------:|:----------:|:----------:| :--------: | :----------:| :------------------: | :--------------------: | :-------------------: | :------: | :----------------------: | :-----: |
| PP-YOLO_MobileNetV3_large | 4 | 32 | 18MB | 320 | 23.2 | 42.6 | 15.6 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_mobilenet_v3_large.pdparams) | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_mobilenet_v3_large.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolo_mobilenet_v3_large.yml) | | PP-YOLO_MobileNetV3_large | 4 | 32 | 18MB | 320 | 23.2 | 42.6 | 15.6 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_mobilenet_v3_large.pdparams) | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_mobilenet_v3_large.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolo_mobilenet_v3_large.yml) |
| PP-YOLO_MobileNetV3_small | 4 | 32 | 11MB | 320 | 17.2 | 33.8 | 28.6 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_mobilenet_v3_small.pdparams) | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_mobilenet_v3_small.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolo_mobilenet_v3_small.yml) | | PP-YOLO_MobileNetV3_small | 4 | 32 | 11MB | 320 | 17.2 | 33.8 | 28.6 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_mobilenet_v3_small.pdparams) | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_mobilenet_v3_small.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolo_mobilenet_v3_small.yml) |
**Notes:** **Notes:**
...@@ -85,7 +85,7 @@ PP-YOLO improved performance and speed of YOLOv3 with following methods: ...@@ -85,7 +85,7 @@ PP-YOLO improved performance and speed of YOLOv3 with following methods:
| Model | GPU number | images/GPU | Prune Ratio | Teacher Model | Model Size | input shape | Box AP<sup>val</sup> | Kirin 990 1xCore(FPS) | download | inference model download | config | | Model | GPU number | images/GPU | Prune Ratio | Teacher Model | Model Size | input shape | Box AP<sup>val</sup> | Kirin 990 1xCore(FPS) | download | inference model download | config |
|:----------------------------:|:----------:|:----------:| :---------: | :-----------------------: | :--------: | :----------:| :------------------: | :-------------------: | :------: | :----------------------: | :-----: | |:----------------------------:|:----------:|:----------:| :---------: | :-----------------------: | :--------: | :----------:| :------------------: | :-------------------: | :------: | :----------------------: | :-----: |
| PP-YOLO_MobileNetV3_small | 4 | 32 | 75% | PP-YOLO_MobileNetV3_large | 4.2MB | 320 | 16.2 | 39.8 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_mobilenet_v3_small_prune75_distillby_mobilenet_v3_large.pdparams) | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_mobilenet_v3_small_prune75_distillby_mobilenet_v3_large.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolo_mobilenet_v3_small.yml) | | PP-YOLO_MobileNetV3_small | 4 | 32 | 75% | PP-YOLO_MobileNetV3_large | 4.2MB | 320 | 16.2 | 39.8 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_mobilenet_v3_small_prune75_distillby_mobilenet_v3_large.pdparams) | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_mobilenet_v3_small_prune75_distillby_mobilenet_v3_large.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolo_mobilenet_v3_small.yml) |
- Slim PP-YOLO is trained by slim traing method from [Distill pruned model](../../slim/extensions/distill_pruned_model/README.md)，distill training pruned PP-YOLO_MobileNetV3_small model with PP-YOLO_MobileNetV3_large model as the teacher model - Slim PP-YOLO is trained by slim traing method from [Distill pruned model](../../slim/extensions/distill_pruned_model/README.md)，distill training pruned PP-YOLO_MobileNetV3_small model with PP-YOLO_MobileNetV3_large model as the teacher model
- Pruning detectiom head of PP-YOLO model with ratio as 75%, while the arguments are `--pruned_params="yolo_block.0.2.conv.weights,yolo_block.0.tip.conv.weights,yolo_block.1.2.conv.weights,yolo_block.1.tip.conv.weights" --pruned_ratios="0.75,0.75,0.75,0.75"` - Pruning detectiom head of PP-YOLO model with ratio as 75%, while the arguments are `--pruned_params="yolo_block.0.2.conv.weights,yolo_block.0.tip.conv.weights,yolo_block.1.2.conv.weights,yolo_block.1.tip.conv.weights" --pruned_ratios="0.75,0.75,0.75,0.75"`
...@@ -95,13 +95,13 @@ PP-YOLO improved performance and speed of YOLOv3 with following methods: ...@@ -95,13 +95,13 @@ PP-YOLO improved performance and speed of YOLOv3 with following methods:
| Model | GPU number | images/GPU | Model Size | Post Quant Model Size | input shape | Box AP<sup>val</sup> | Kirin 990 4xCore(FPS) | download | config | config | post quant model | | Model | GPU number | images/GPU | Model Size | Post Quant Model Size | input shape | Box AP<sup>val</sup> | Kirin 990 4xCore(FPS) | download | config | config | post quant model |
|:----------------------------:|:-------:|:-------------:|:----------:| :-------------------: | :----------:| :------------------: | :-------------------: | :------: | :----: | :----: | :--------------: | |:----------------------------:|:-------:|:-------------:|:----------:| :-------------------: | :----------:| :------------------: | :-------------------: | :------: | :----: | :----: | :--------------: |
| PP-YOLO tiny | 8 | 32 | 4.2MB | **1.3M** | 320 | 20.6 | 92.3 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_tiny.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolo_tiny.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://paddlemodels.bj.bcebos.com/object_detection/ppyolo_tiny.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolo_tiny.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://paddlemodels.bj.bcebos.com/object_detection/ppyolo_tiny.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolo_tiny.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://paddlemodels.bj.bcebos.com/object_detection/ppyolo_tiny.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolo_tiny.yml) | [inference model](https://paddledet.bj.bcebos.com/models/ppyolo_tiny_quant.tar) |
**Notes:** **Notes:**
- PP-YOLO-tiny is trained on COCO train2017 datast and evaluated on val2017 dataset，Box AP<sup>val</sup> is evaluation results of `mAP(IoU=0.5:0.95)`, Box AP<sup>val</sup> is evaluation results of `mAP(IoU=0.5)`. - PP-YOLO-tiny is trained on COCO train2017 datast and evaluated on val2017 dataset，Box AP<sup>val</sup> is evaluation results of `mAP(IoU=0.5:0.95)`, Box AP<sup>val</sup> 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/master/docs/FAQ.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/2.1/static/docs/FAQ.md).
- PP-YOLO-tiny inference speed is tested on Kirin 990 with 4 threads by arm8 - 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 - 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
...@@ -111,9 +111,9 @@ PP-YOLO trained on Pascal VOC dataset as follows: ...@@ -111,9 +111,9 @@ PP-YOLO trained on Pascal VOC dataset as follows:
| Model | GPU number | images/GPU | backbone | input shape | Box AP50<sup>val</sup> | download | config | | Model | GPU number | images/GPU | backbone | input shape | Box AP50<sup>val</sup> | download | config |
|:------------------:|:----------:|:----------:|:----------:| :----------:| :--------------------: | :------: | :-----: | |:------------------:|:----------:|:----------:|:----------:| :----------:| :--------------------: | :------: | :-----: |
| PP-YOLO | 8 | 12 | ResNet50vd | 608 | 84.9 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolo_voc.yml) | | PP-YOLO | 8 | 12 | ResNet50vd | 608 | 84.9 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolo_voc.yml) |
| PP-YOLO | 8 | 12 | ResNet50vd | 416 | 84.3 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolo_voc.yml) | | PP-YOLO | 8 | 12 | ResNet50vd | 416 | 84.3 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolo_voc.yml) |
| PP-YOLO | 8 | 12 | ResNet50vd | 320 | 82.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolo_voc.yml) | | PP-YOLO | 8 | 12 | ResNet50vd | 320 | 82.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolo_voc.yml) |
## Getting Start ## Getting Start
......
static/configs/ppyolo/README_cn.md
浏览文件 @ 99c7e3a7
...@@ -38,23 +38,23 @@ PP-YOLO从如下方面优化和提升YOLOv3模型的精度和速度： ...@@ -38,23 +38,23 @@ PP-YOLO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 AP<sup>val</sup> | Box AP<sup>test</sup> | V100 FP32(FPS) | V100 TensorRT FP16(FPS) | 模型下载 | 配置文件 | | 模型 | GPU个数 | 每GPU图片个数 | 骨干网络 | 输入尺寸 | Box AP<sup>val</sup> | Box AP<sup>test</sup> | V100 FP32(FPS) | V100 TensorRT FP16(FPS) | 模型下载 | 配置文件 |
|:------------------------:|:-------:|:-------------:|:----------:| :-------:| :------------------: | :-------------------: | :------------: | :---------------------: | :------: | :------: | |:------------------------:|:-------:|:-------------:|:----------:| :-------:| :------------------: | :-------------------: | :------------: | :---------------------: | :------: | :------: |
| YOLOv4(AlexyAB) | - | - | CSPDarknet | 608 | - | 43.5 | 62 | 105.5 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov4_cspdarknet.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/yolov4/yolov4_csdarknet.yml) | | YOLOv4(AlexyAB) | - | - | CSPDarknet | 608 | - | 43.5 | 62 | 105.5 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov4_cspdarknet.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov4/yolov4_csdarknet.yml) |
| YOLOv4(AlexyAB) | - | - | CSPDarknet | 512 | - | 43.0 | 83 | 138.4 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov4_cspdarknet.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/yolov4/yolov4_csdarknet.yml) | | YOLOv4(AlexyAB) | - | - | CSPDarknet | 512 | - | 43.0 | 83 | 138.4 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov4_cspdarknet.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov4/yolov4_csdarknet.yml) |
| YOLOv4(AlexyAB) | - | - | CSPDarknet | 416 | - | 41.2 | 96 | 164.0 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov4_cspdarknet.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/yolov4/yolov4_csdarknet.yml) | | YOLOv4(AlexyAB) | - | - | CSPDarknet | 416 | - | 41.2 | 96 | 164.0 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov4_cspdarknet.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov4/yolov4_csdarknet.yml) |
| YOLOv4(AlexyAB) | - | - | CSPDarknet | 320 | - | 38.0 | 123 | 199.0 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov4_cspdarknet.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/yolov4/yolov4_csdarknet.yml) | | YOLOv4(AlexyAB) | - | - | CSPDarknet | 320 | - | 38.0 | 123 | 199.0 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov4_cspdarknet.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov4/yolov4_csdarknet.yml) |
| PP-YOLO | 8 | 24 | ResNet50vd | 608 | 44.8 | 45.2 | 72.9 | 155.6 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolo.yml) | | PP-YOLO | 8 | 24 | ResNet50vd | 608 | 44.8 | 45.2 | 72.9 | 155.6 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolo.yml) |
| PP-YOLO | 8 | 24 | ResNet50vd | 512 | 43.9 | 44.4 | 89.9 | 188.4 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolo.yml) | | PP-YOLO | 8 | 24 | ResNet50vd | 512 | 43.9 | 44.4 | 89.9 | 188.4 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolo.yml) |
| PP-YOLO | 8 | 24 | ResNet50vd | 416 | 42.1 | 42.5 | 109.1 | 215.4 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolo.yml) | | PP-YOLO | 8 | 24 | ResNet50vd | 416 | 42.1 | 42.5 | 109.1 | 215.4 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolo.yml) |
| PP-YOLO | 8 | 24 | ResNet50vd | 320 | 38.9 | 39.3 | 132.2 | 242.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolo.yml) | | PP-YOLO | 8 | 24 | ResNet50vd | 320 | 38.9 | 39.3 | 132.2 | 242.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolo.yml) |
| PP-YOLO_2x | 8 | 24 | ResNet50vd | 608 | 45.3 | 45.9 | 72.9 | 155.6 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_2x.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolo_2x.yml) | | PP-YOLO_2x | 8 | 24 | ResNet50vd | 608 | 45.3 | 45.9 | 72.9 | 155.6 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_2x.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolo_2x.yml) |
| PP-YOLO_2x | 8 | 24 | ResNet50vd | 512 | 44.4 | 45.0 | 89.9 | 188.4 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_2x.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolo_2x.yml) | | PP-YOLO_2x | 8 | 24 | ResNet50vd | 512 | 44.4 | 45.0 | 89.9 | 188.4 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_2x.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolo_2x.yml) |
| PP-YOLO_2x | 8 | 24 | ResNet50vd | 416 | 42.7 | 43.2 | 109.1 | 215.4 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_2x.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolo_2x.yml) | | PP-YOLO_2x | 8 | 24 | ResNet50vd | 416 | 42.7 | 43.2 | 109.1 | 215.4 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_2x.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolo_2x.yml) |
| PP-YOLO_2x | 8 | 24 | ResNet50vd | 320 | 39.5 | 40.1 | 132.2 | 242.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_2x.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolo_2x.yml) | | PP-YOLO_2x | 8 | 24 | ResNet50vd | 320 | 39.5 | 40.1 | 132.2 | 242.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_2x.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolo_2x.yml) |
| PP-YOLO | 4 | 32 | ResNet18vd | 512 | 29.3 | 29.5 | 357.1 | 657.9 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_r18vd.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolo_r18vd.yml) | | PP-YOLO | 4 | 32 | ResNet18vd | 512 | 29.3 | 29.5 | 357.1 | 657.9 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_r18vd.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolo_r18vd.yml) |
| PP-YOLO | 4 | 32 | ResNet18vd | 416 | 28.6 | 28.9 | 409.8 | 719.4 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_r18vd.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolo_r18vd.yml) | | PP-YOLO | 4 | 32 | ResNet18vd | 416 | 28.6 | 28.9 | 409.8 | 719.4 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_r18vd.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolo_r18vd.yml) |
| PP-YOLO | 4 | 32 | ResNet18vd | 320 | 26.2 | 26.4 | 480.7 | 763.4 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_r18vd.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolo_r18vd.yml) | | PP-YOLO | 4 | 32 | ResNet18vd | 320 | 26.2 | 26.4 | 480.7 | 763.4 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_r18vd.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolo_r18vd.yml) |
| PP-YOLOv2 | 8 | 12 | ResNet50vd | 640 | 49.1 | 49.5 | 68.9 | 106.5 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolov2_r50vd_dcn.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolov2_r50vd_dcn.yml) | | PP-YOLOv2 | 8 | 12 | ResNet50vd | 640 | 49.1 | 49.5 | 68.9 | 106.5 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolov2_r50vd_dcn.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolov2_r50vd_dcn.yml) |
| PP-YOLOv2 | 8 | 12 | ResNet101vd | 640 | 49.7 | 50.3 | 49.5 | 87.0 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolov2_r101vd_dcn.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolov2_r101vd_dcn.yml) | | PP-YOLOv2 | 8 | 12 | ResNet101vd | 640 | 49.7 | 50.3 | 49.5 | 87.0 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolov2_r101vd_dcn.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolov2_r101vd_dcn.yml) |
**注意:** **注意:**
...@@ -72,8 +72,8 @@ PP-YOLO从如下方面优化和提升YOLOv3模型的精度和速度： ...@@ -72,8 +72,8 @@ PP-YOLO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 AP<sup>val</sup> | Box AP50<sup>val</sup> | Kirin 990 1xCore (FPS) | 模型下载 | 预测模型下载 | 配置文件 | | 模型 | GPU个数 | 每GPU图片个数 | 模型体积 | 输入尺寸 | Box AP<sup>val</sup> | Box AP50<sup>val</sup> | Kirin 990 1xCore (FPS) | 模型下载 | 预测模型下载 | 配置文件 |
|:----------------------------:|:-------:|:-------------:|:----------:| :-------:| :------------------: | :--------------------: | :--------------------: | :------: | :----------: | :------: | |:----------------------------:|:-------:|:-------------:|:----------:| :-------:| :------------------: | :--------------------: | :--------------------: | :------: | :----------: | :------: |
| PP-YOLO_MobileNetV3_large | 4 | 32 | 18MB | 320 | 23.2 | 42.6 | 14.1 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_mobilenet_v3_large.pdparams) | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_mobilenet_v3_large.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolo_mobilenet_v3_large.yml) | | PP-YOLO_MobileNetV3_large | 4 | 32 | 18MB | 320 | 23.2 | 42.6 | 14.1 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_mobilenet_v3_large.pdparams) | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_mobilenet_v3_large.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolo_mobilenet_v3_large.yml) |
| PP-YOLO_MobileNetV3_small | 4 | 32 | 11MB | 320 | 17.2 | 33.8 | 21.5 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_mobilenet_v3_small.pdparams) | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_mobilenet_v3_large.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolo_mobilenet_v3_small.yml) | | PP-YOLO_MobileNetV3_small | 4 | 32 | 11MB | 320 | 17.2 | 33.8 | 21.5 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_mobilenet_v3_small.pdparams) | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_mobilenet_v3_large.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolo_mobilenet_v3_small.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 AP<sup>val</sup>为`mAP(IoU=0.5:0.95)`评估结果, Box AP50<sup>val</sup>为`mAP(IoU=0.5)`评估结果。 - 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 AP<sup>val</sup>为`mAP(IoU=0.5:0.95)`评估结果, Box AP50<sup>val</sup>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](../../docs/FAQ.md)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](../../docs/FAQ.md)调整学习率和迭代次数。
...@@ -83,7 +83,7 @@ PP-YOLO从如下方面优化和提升YOLOv3模型的精度和速度： ...@@ -83,7 +83,7 @@ PP-YOLO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 | 裁剪率 | Teacher模型 | 模型体积 | 输入尺寸 | Box AP<sup>val</sup> | Kirin 990 1xCore (FPS) | 模型下载 | 预测模型下载 | 配置文件 | | 模型 | GPU 个数 | 每GPU图片个数 | 裁剪率 | Teacher模型 | 模型体积 | 输入尺寸 | Box AP<sup>val</sup> | Kirin 990 1xCore (FPS) | 模型下载 | 预测模型下载 | 配置文件 |
|:----------------------------:|:----------:|:-------------:| :---------: | :-----------------------: | :--------: | :----------:| :------------------: | :--------------------: | :------: | :----------: | :------: | |:----------------------------:|:----------:|:-------------:| :---------: | :-----------------------: | :--------: | :----------:| :------------------: | :--------------------: | :------: | :----------: | :------: |
| PP-YOLO_MobileNetV3_small | 4 | 32 | 75% | PP-YOLO_MobileNetV3_large | 4.2MB | 320 | 16.2 | 39.8 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_mobilenet_v3_small_prune75_distillby_mobilenet_v3_large.pdparams) | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_mobilenet_v3_small_prune75_distillby_mobilenet_v3_large.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolo_mobilenet_v3_small.yml) | | PP-YOLO_MobileNetV3_small | 4 | 32 | 75% | PP-YOLO_MobileNetV3_large | 4.2MB | 320 | 16.2 | 39.8 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_mobilenet_v3_small_prune75_distillby_mobilenet_v3_large.pdparams) | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_mobilenet_v3_small_prune75_distillby_mobilenet_v3_large.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolo_mobilenet_v3_small.yml) |
- PP-YOLO 轻量级裁剪模型采用[蒸馏通道剪裁模型](../../slim/extensions/distill_pruned_model/README.md) 的方式训练得到，基于 PP-YOLO_MobileNetV3_small 模型对Head部分做卷积通道剪裁后使用 PP-YOLO_MobileNetV3_large 模型进行蒸馏训练 - PP-YOLO 轻量级裁剪模型采用[蒸馏通道剪裁模型](../../slim/extensions/distill_pruned_model/README.md) 的方式训练得到，基于 PP-YOLO_MobileNetV3_small 模型对Head部分做卷积通道剪裁后使用 PP-YOLO_MobileNetV3_large 模型进行蒸馏训练
- 卷积通道检测对Head部分剪裁掉75%的通道数，及剪裁参数为`--pruned_params="yolo_block.0.2.conv.weights,yolo_block.0.tip.conv.weights,yolo_block.1.2.conv.weights,yolo_block.1.tip.conv.weights" --pruned_ratios="0.75,0.75,0.75,0.75"` - 卷积通道检测对Head部分剪裁掉75%的通道数，及剪裁参数为`--pruned_params="yolo_block.0.2.conv.weights,yolo_block.0.tip.conv.weights,yolo_block.1.2.conv.weights,yolo_block.1.tip.conv.weights" --pruned_ratios="0.75,0.75,0.75,0.75"`
...@@ -93,8 +93,8 @@ PP-YOLO从如下方面优化和提升YOLOv3模型的精度和速度： ...@@ -93,8 +93,8 @@ PP-YOLO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 | 后量化模型体积 | 输入尺寸 | Box AP<sup>val</sup> | Kirin 990 1xCore (FPS) | 模型下载 | 配置文件 | 量化后模型 | | 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 AP<sup>val</sup> | 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://paddlemodels.bj.bcebos.com/object_detection/ppyolo_tiny.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolo_tiny.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://paddlemodels.bj.bcebos.com/object_detection/ppyolo_tiny.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolo_tiny.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://paddlemodels.bj.bcebos.com/object_detection/ppyolo_tiny.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolo_tiny.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://paddlemodels.bj.bcebos.com/object_detection/ppyolo_tiny.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolo_tiny.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 AP<sup>val</sup>为`mAP(IoU=0.5:0.95)`评估结果, Box AP50<sup>val</sup>为`mAP(IoU=0.5)`评估结果。 - 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 AP<sup>val</sup>为`mAP(IoU=0.5:0.95)`评估结果, Box AP50<sup>val</sup>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](../../docs/FAQ.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](../../docs/FAQ.md)调整学习率和迭代次数。
...@@ -107,9 +107,9 @@ PP-YOLO在Pascal VOC数据集上训练模型如下: ...@@ -107,9 +107,9 @@ 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 AP50<sup>val</sup> | 模型下载 | 配置文件 | | 模型 | GPU个数 | 每GPU图片个数 | 骨干网络 | 输入尺寸 | Box AP50<sup>val</sup> | 模型下载 | 配置文件 |
|:------------------:|:-------:|:-------------:|:----------:| :----------:| :--------------------: | :------: | :-----: | |:------------------:|:-------:|:-------------:|:----------:| :----------:| :--------------------: | :------: | :-----: |
| PP-YOLO | 8 | 12 | ResNet50vd | 608 | 84.9 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolo_voc.yml) | | PP-YOLO | 8 | 12 | ResNet50vd | 608 | 84.9 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolo_voc.yml) |
| PP-YOLO | 8 | 12 | ResNet50vd | 416 | 84.3 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolo_voc.yml) | | PP-YOLO | 8 | 12 | ResNet50vd | 416 | 84.3 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolo_voc.yml) |
| PP-YOLO | 8 | 12 | ResNet50vd | 320 | 82.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/static/configs/ppyolo/ppyolo_voc.yml) | | PP-YOLO | 8 | 12 | ResNet50vd | 320 | 82.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ppyolo/ppyolo_voc.yml) |
## 使用说明 ## 使用说明
......
static/configs/random_erasing/README.md
浏览文件 @ 99c7e3a7
...@@ -18,4 +18,4 @@ ...@@ -18,4 +18,4 @@
| Backbone | Type | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download | Configs | | Backbone | Type | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download | Configs |
| :---------------------- | :-------------: | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: | :-----: | | :---------------------- | :-------------: | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: | :-----: |
| ResNet50-vd-FPN | Faster | 2 | 4x | 21.847 | 39.0% | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_fpn_random_erasing_4x.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/random_erasing/faster_rcnn_r50_vd_fpn_random_erasing_4x.yml) | | ResNet50-vd-FPN | Faster | 2 | 4x | 21.847 | 39.0% | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_fpn_random_erasing_4x.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/random_erasing/faster_rcnn_r50_vd_fpn_random_erasing_4x.yml) |
static/configs/rcnn_enhance/README.md
浏览文件 @ 99c7e3a7
...@@ -32,9 +32,9 @@ ...@@ -32,9 +32,9 @@
| 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 | | 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 | 41.6 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_r50_vd_fpn_3x_server_side.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/rcnn_enhance/faster_rcnn_dcn_r50_vd_fpn_3x_server_side.yml) | | ResNet50-vd-FPN-Dcnv2 | Faster | 2 | 3x | 61.425 | 41.6 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_r50_vd_fpn_3x_server_side.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/rcnn_enhance/faster_rcnn_dcn_r50_vd_fpn_3x_server_side.yml) |
| ResNet50-vd-FPN-Dcnv2 | Cascade Faster | 2 | 3x | 20.001 | 47.8 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_r50_vd_fpn_3x_server_side.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/rcnn_enhance/cascade_rcnn_dcn_r50_vd_fpn_3x_server_side.yml) | | ResNet50-vd-FPN-Dcnv2 | Cascade Faster | 2 | 3x | 20.001 | 47.8 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_r50_vd_fpn_3x_server_side.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/rcnn_enhance/cascade_rcnn_dcn_r50_vd_fpn_3x_server_side.yml) |
| ResNet101-vd-FPN-Dcnv2 | Cascade Faster | 2 | 3x | 19.523 | 49.4 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_r101_vd_fpn_3x_server_side.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/rcnn_enhance/cascade_rcnn_dcn_r101_vd_fpn_3x_server_side.yml) | | ResNet101-vd-FPN-Dcnv2 | Cascade Faster | 2 | 3x | 19.523 | 49.4 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_r101_vd_fpn_3x_server_side.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/rcnn_enhance/cascade_rcnn_dcn_r101_vd_fpn_3x_server_side.yml) |
**注**：generic文件夹下面的配置文件对应的预训练模型均只支持预测，不支持训练与评估。 **注**：generic文件夹下面的配置文件对应的预训练模型均只支持预测，不支持训练与评估。
static/configs/rcnn_enhance/README_en.md
浏览文件 @ 99c7e3a7
...@@ -36,9 +36,9 @@ And the following figure shows `mAP-Speed` curves for some common detectors. ...@@ -36,9 +36,9 @@ And the following figure shows `mAP-Speed` curves for some common detectors.
| Backbone | Type | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download | Configs | | Backbone | Type | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download | Configs |
| :---------------------- | :-------------: | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: | :-----: | | :---------------------- | :-------------: | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: | :-----: |
| ResNet50-vd-FPN-Dcnv2 | Faster | 2 | 3x | 61.425 | 41.6 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_r50_vd_fpn_3x_server_side.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/rcnn_enhance/faster_rcnn_dcn_r50_vd_fpn_3x_server_side.yml) | | ResNet50-vd-FPN-Dcnv2 | Faster | 2 | 3x | 61.425 | 41.6 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_r50_vd_fpn_3x_server_side.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/rcnn_enhance/faster_rcnn_dcn_r50_vd_fpn_3x_server_side.yml) |
| ResNet50-vd-FPN-Dcnv2 | Cascade Faster | 2 | 3x | 20.001 | 47.8 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_r50_vd_fpn_3x_server_side.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/rcnn_enhance/cascade_rcnn_dcn_r50_vd_fpn_3x_server_side.yml) | | ResNet50-vd-FPN-Dcnv2 | Cascade Faster | 2 | 3x | 20.001 | 47.8 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_r50_vd_fpn_3x_server_side.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/rcnn_enhance/cascade_rcnn_dcn_r50_vd_fpn_3x_server_side.yml) |
| ResNet101-vd-FPN-Dcnv2 | Cascade Faster | 2 | 3x | 19.523 | 49.4 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_r101_vd_fpn_3x_server_side.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/rcnn_enhance/cascade_rcnn_dcn_r101_vd_fpn_3x_server_side.yml) | | ResNet101-vd-FPN-Dcnv2 | Cascade Faster | 2 | 3x | 19.523 | 49.4 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_r101_vd_fpn_3x_server_side.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/rcnn_enhance/cascade_rcnn_dcn_r101_vd_fpn_3x_server_side.yml) |
**Attention**: Pretrained models whose congigurations are in the directory `generic` just support inference but do not support training and evaluation as now. **Attention**: Pretrained models whose congigurations are in the directory `generic` just support inference but do not support training and evaluation as now.
static/configs/res2net/README.md
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...@@ -30,7 +30,7 @@ ...@@ -30,7 +30,7 @@
| Backbone | Type | deformable Conv | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download | Configs | | Backbone | Type | deformable Conv | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download | Configs |
| :---------------------- | :------------- | :---: | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: | :-----: | | :---------------------- | :------------- | :---: | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: | :-----: |
| Res2Net50-FPN | Faster | False | 2 | 1x | 20.320 | 39.5 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_res2net50_vb_26w_4s_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/res2net/faster_rcnn_res2net50_vb_26w_4s_fpn_1x.yml) | | Res2Net50-FPN | Faster | False | 2 | 1x | 20.320 | 39.5 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_res2net50_vb_26w_4s_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/res2net/faster_rcnn_res2net50_vb_26w_4s_fpn_1x.yml) |
| Res2Net50-FPN | Mask | False | 2 | 2x | 16.069 | 40.7 | 36.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_res2net50_vb_26w_4s_fpn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/res2net/faster_rcnn_res2net50_vb_26w_4s_fpn_2x.yml) | | Res2Net50-FPN | Mask | False | 2 | 2x | 16.069 | 40.7 | 36.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_res2net50_vb_26w_4s_fpn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/res2net/faster_rcnn_res2net50_vb_26w_4s_fpn_2x.yml) |
| Res2Net50-vd-FPN | Mask | False | 2 | 2x | 15.816 | 40.9 | 36.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_res2net50_vd_26w_4s_fpn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/res2net/mask_rcnn_res2net50_vd_26w_4s_fpn_2x.yml) | | Res2Net50-vd-FPN | Mask | False | 2 | 2x | 15.816 | 40.9 | 36.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_res2net50_vd_26w_4s_fpn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/res2net/mask_rcnn_res2net50_vd_26w_4s_fpn_2x.yml) |
| Res2Net50-vd-FPN | Mask | True | 2 | 2x | 14.478 | 43.5 | 38.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_res2net50_vd_26w_4s_fpn_dcnv2_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/res2net/mask_rcnn_res2net50_vd_26w_4s_fpn_dcnv2_1x.yml) | | Res2Net50-vd-FPN | Mask | True | 2 | 2x | 14.478 | 43.5 | 38.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_res2net50_vd_26w_4s_fpn_dcnv2_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/res2net/mask_rcnn_res2net50_vd_26w_4s_fpn_dcnv2_1x.yml) |
static/configs/solov2/README.md
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...@@ -25,15 +25,15 @@ SOLOv2 (Segmenting Objects by Locations) is a fast instance segmentation framewo ...@@ -25,15 +25,15 @@ SOLOv2 (Segmenting Objects by Locations) is a fast instance segmentation framewo
| BlendMask | R50-FPN | True | 3x | 37.8 | 13.5 | V100 | - | - | | BlendMask | R50-FPN | True | 3x | 37.8 | 13.5 | V100 | - | - |
| SOLOv2 (Paper) | R50-FPN | False | 1x | 34.8 | 18.5 | 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 (Paper) | X101-DCN-FPN | True | 3x | 42.4 | 5.9 | V100 | - | - |
| SOLOv2 | Mobilenetv3-FPN | True | 3x | 30.0 | 50 | V100 | [model](https://paddlemodels.bj.bcebos.com/object_detection/solov2_mobilenetv3_fpn_448_3x.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/solov2/solov2_mobilenetv3_fpn_448_3x.yml) | | SOLOv2 | Mobilenetv3-FPN | True | 3x | 30.0 | 50 | V100 | [model](https://paddlemodels.bj.bcebos.com/object_detection/solov2_mobilenetv3_fpn_448_3x.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/solov2/solov2_mobilenetv3_fpn_448_3x.yml) |
| SOLOv2 | R50-FPN | False | 1x | 35.6 | 21.9 | V100 | [model](https://paddlemodels.bj.bcebos.com/object_detection/solov2_r50_fpn_1x.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/solov2/solov2_r50_fpn_1x.yml) | | SOLOv2 | R50-FPN | False | 1x | 35.6 | 21.9 | V100 | [model](https://paddlemodels.bj.bcebos.com/object_detection/solov2_r50_fpn_1x.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/solov2/solov2_r50_fpn_1x.yml) |
| SOLOv2 | R50-FPN | True | 3x | 37.9 | 21.9 | V100 | [model](https://paddlemodels.bj.bcebos.com/object_detection/solov2_r50_fpn_3x.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/solov2/solov2_r50_fpn_3x.yml) | | SOLOv2 | R50-FPN | True | 3x | 37.9 | 21.9 | V100 | [model](https://paddlemodels.bj.bcebos.com/object_detection/solov2_r50_fpn_3x.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/solov2/solov2_r50_fpn_3x.yml) |
| SOLOv2 | R101-VD-FPN | True | 3x | 42.6 | 12.1 | V100 | [model](https://paddlemodels.bj.bcebos.com/object_detection/solov2_r101_vd_fpn_3x.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/solov2/solov2_r101_vd_fpn_3x.yml) | | SOLOv2 | R101-VD-FPN | True | 3x | 42.6 | 12.1 | V100 | [model](https://paddlemodels.bj.bcebos.com/object_detection/solov2_r101_vd_fpn_3x.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/solov2/solov2_r101_vd_fpn_3x.yml) |
## Enhanced model ## Enhanced model
| Backbone | Input size | Lr schd | V100 FP32(FPS) | Mask AP<sup>val</sup> | Download | Configs | | Backbone | Input size | Lr schd | V100 FP32(FPS) | Mask AP<sup>val</sup> | Download | Configs |
| :---------------------: | :-------------------: | :-----: | :------------: | :-----: | :---------: | :------------------------: | | :---------------------: | :-------------------: | :-----: | :------------: | :-----: | :---------: | :------------------------: |
| Light-R50-VD-DCN-FPN | 512 | 3x | 38.6 | 38.8 | [model](https://paddlemodels.bj.bcebos.com/object_detection/solov2_light_r50_vd_fpn_dcn_512_3x.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/solov2/solov2_light_r50_vd_fpn_dcn_512_3x.yml) | | Light-R50-VD-DCN-FPN | 512 | 3x | 38.6 | 38.8 | [model](https://paddlemodels.bj.bcebos.com/object_detection/solov2_light_r50_vd_fpn_dcn_512_3x.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/solov2/solov2_light_r50_vd_fpn_dcn_512_3x.yml) |
**Notes:** **Notes:**
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| | GPU个数 | 测试集 | 骨干网络 | 精度 | 模型下载 | 配置文件 | | | GPU个数 | 测试集 | 骨干网络 | 精度 | 模型下载 | 配置文件 |
|:------------------------:|:-------:|:------:|:--------------------------:|:------------------------:| :---------:| :-----: | |:------------------------:|:-------:|:------:|:--------------------------:|:------------------------:| :---------:| :-----: |
| YOLO v4 | - |test-dev2019 | CSPDarkNet53 | 43.5 |[下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov4_cspdarknet.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov4/yolov4_cspdarknet.yml) | | YOLO v4 | - |test-dev2019 | CSPDarkNet53 | 43.5 |[下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov4_cspdarknet.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov4/yolov4_cspdarknet.yml) |
| YOLO v4 VOC | 2 | VOC2007 | CSPDarkNet53 | 85.5 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov4_cspdarknet_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov4/yolov4_cspdarknet_voc.yml) | | YOLO v4 VOC | 2 | VOC2007 | CSPDarkNet53 | 85.5 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov4_cspdarknet_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov4/yolov4_cspdarknet_voc.yml) |
**注意:** **注意:**
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## 模型导出 ## 模型导出
训练得到一个满足要求的模型后，如果想要将该模型接入到C++服务器端预测库或移动端预测库，需要通过`tools/export_model.py`导出该模型。 训练得到一个满足要求的模型后，如果想要将该模型接入到C++服务器端预测库或移动端预测库，需要通过`tools/export_model.py`导出该模型。
- [导出教程](https://github.com/PaddlePaddle/PaddleDetection/blob/master/docs/advanced_tutorials/deploy/EXPORT_MODEL.md) - [导出教程](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/docs/advanced_tutorials/deploy/EXPORT_MODEL.md)
模型导出后, 目录结构如下(以`yolov3_darknet`为例): 模型导出后, 目录结构如下(以`yolov3_darknet`为例):
``` ```
...@@ -21,8 +21,8 @@ yolov3_darknet # 模型目录 ...@@ -21,8 +21,8 @@ yolov3_darknet # 模型目录
预测时，该目录所在的路径会作为程序的输入参数。 预测时，该目录所在的路径会作为程序的输入参数。
## 预测部署 ## 预测部署
- [1. Python预测(支持 Linux 和 Windows)](https://github.com/PaddlePaddle/PaddleDetection/blob/master/deploy/python) - [1. Python预测(支持 Linux 和 Windows)](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/deploy/python)
- [2. C++预测(支持 Linux 和 Windows)](https://github.com/PaddlePaddle/PaddleDetection/blob/master/deploy/cpp) - [2. C++预测(支持 Linux 和 Windows)](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/deploy/cpp)
- [3. 在线服务化部署](./serving/README.md) - [3. 在线服务化部署](./serving/README.md)
- [4. 移动端部署](https://github.com/PaddlePaddle/Paddle-Lite-Demo) - [4. 移动端部署](https://github.com/PaddlePaddle/Paddle-Lite-Demo)
- [5. Jetson设备部署](./cpp/docs/Jetson_build.md) - [5. Jetson设备部署](./cpp/docs/Jetson_build.md)
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## 3.编译部署 ## 3.编译部署
### 3.1 导出模型 ### 3.1 导出模型
请确认您已经基于`PaddleDetection`的[export_model.py](https://github.com/PaddlePaddle/PaddleDetection/blob/master/tools/export_model.py)导出您的模型，并妥善保存到合适的位置。导出模型细节请参考 [导出模型教程](https://github.com/PaddlePaddle/PaddleDetection/blob/master/docs/advanced_tutorials/deploy/EXPORT_MODEL.md)。 请确认您已经基于`PaddleDetection`的[export_model.py](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/tools/export_model.py)导出您的模型，并妥善保存到合适的位置。导出模型细节请参考 [导出模型教程](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/docs/advanced_tutorials/deploy/EXPORT_MODEL.md)。
模型导出后, 目录结构如下(以`yolov3_darknet`为例): 模型导出后, 目录结构如下(以`yolov3_darknet`为例):
``` ```
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Python预测可以使用`tools/infer.py`，此种方式依赖PaddleDetection源码；也可以使用本篇教程预测方式，先将模型导出，使用一个独立的文件进行预测。 Python预测可以使用`tools/infer.py`，此种方式依赖PaddleDetection源码；也可以使用本篇教程预测方式，先将模型导出，使用一个独立的文件进行预测。
本篇教程使用AnalysisPredictor对[导出模型](https://github.com/PaddlePaddle/PaddleDetection/blob/master/docs/advanced_tutorials/deploy/EXPORT_MODEL.md)进行高性能预测。 本篇教程使用AnalysisPredictor对[导出模型](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/docs/advanced_tutorials/deploy/EXPORT_MODEL.md)进行高性能预测。
在PaddlePaddle中预测引擎和训练引擎底层有着不同的优化方法, 下面列出了两种不同的预测方式。Executor同时支持训练和预测，AnalysisPredictor则专门针对推理进行了优化，是基于[C++预测库](https://www.paddlepaddle.org.cn/documentation/docs/zh/advanced_guide/inference_deployment/inference/native_infer.html)的Python接口，该引擎可以对模型进行多项图优化，减少不必要的内存拷贝。如果用户在部署已训练模型的过程中对性能有较高的要求，我们提供了独立于PaddleDetection的预测脚本，方便用户直接集成部署。 在PaddlePaddle中预测引擎和训练引擎底层有着不同的优化方法, 下面列出了两种不同的预测方式。Executor同时支持训练和预测，AnalysisPredictor则专门针对推理进行了优化，是基于[C++预测库](https://www.paddlepaddle.org.cn/documentation/docs/zh/advanced_guide/inference_deployment/inference/native_infer.html)的Python接口，该引擎可以对模型进行多项图优化，减少不必要的内存拷贝。如果用户在部署已训练模型的过程中对性能有较高的要求，我们提供了独立于PaddleDetection的预测脚本，方便用户直接集成部署。
...@@ -18,7 +18,7 @@ Python预测可以使用`tools/infer.py`，此种方式依赖PaddleDetection源 ...@@ -18,7 +18,7 @@ Python预测可以使用`tools/infer.py`，此种方式依赖PaddleDetection源
## 1. 导出预测模型 ## 1. 导出预测模型
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/master/docs/advanced_tutorials/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/2.1/static/docs/advanced_tutorials/deploy/EXPORT_MODEL.md)
导出后目录下，包括`__model__`，`__params__`和`infer_cfg.yml`三个文件。 导出后目录下，包括`__model__`，`__params__`和`infer_cfg.yml`三个文件。
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``` ```
## 3. 导出模型 ## 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/master/docs/advanced_tutorials/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/2.1/static/docs/advanced_tutorials/deploy/EXPORT_MODEL.md)
``` ```
python tools/export_serving_model.py -c configs/yolov3_mobilenet_v1_roadsign.yml -o use_gpu=true weights=https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1_roadsign.pdparams --output_dir=./inference_model python tools/export_serving_model.py -c configs/yolov3_mobilenet_v1_roadsign.yml -o use_gpu=true weights=https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1_roadsign.pdparams --output_dir=./inference_model
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| Backbone | Type | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download | Configs | | Backbone | Type | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download | Configs |
| :---------------------- | :------------- | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: | :----: | | :---------------------- | :------------- | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: | :----: |
| ResNet50 | Faster | 1 | 1x | 12.747 | 35.2 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r50_1x.yml) | | ResNet50 | Faster | 1 | 1x | 12.747 | 35.2 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/faster_rcnn_r50_1x.yml) |
| ResNet50 | Faster | 1 | 2x | 12.686 | 37.1 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r50_2x.yml) | | ResNet50 | Faster | 1 | 2x | 12.686 | 37.1 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/faster_rcnn_r50_2x.yml) |
| ResNet50 | Mask | 1 | 1x | 11.615 | 36.5 | 32.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/mask_rcnn_r50_1x.yml) | | ResNet50 | Mask | 1 | 1x | 11.615 | 36.5 | 32.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/mask_rcnn_r50_1x.yml) |
| ResNet50 | Mask | 1 | 2x | 11.494 | 38.2 | 33.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/mask_rcnn_r50_2x.yml) | | ResNet50 | Mask | 1 | 2x | 11.494 | 38.2 | 33.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/mask_rcnn_r50_2x.yml) |
| ResNet50-vd | Faster | 1 | 1x | 12.575 | 36.4 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r50_vd_1x.yml) | | ResNet50-vd | Faster | 1 | 1x | 12.575 | 36.4 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/faster_rcnn_r50_vd_1x.yml) |
| ResNet34-FPN | Faster | 2 | 1x | - | 36.7 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r34_fpn_1x.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r34_fpn_1x.yml) | | ResNet34-FPN | Faster | 2 | 1x | - | 36.7 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r34_fpn_1x.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/faster_rcnn_r34_fpn_1x.yml) |
| ResNet34-vd-FPN | Faster | 2 | 1x | - | 37.4 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r34_vd_fpn_1x.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r34_vd_fpn_1x.yml) | | ResNet34-vd-FPN | Faster | 2 | 1x | - | 37.4 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r34_vd_fpn_1x.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/faster_rcnn_r34_vd_fpn_1x.yml) |
| ResNet50-FPN | Faster | 2 | 1x | 22.273 | 37.2 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r50_fpn_1x.yml) | | ResNet50-FPN | Faster | 2 | 1x | 22.273 | 37.2 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/faster_rcnn_r50_fpn_1x.yml) |
| ResNet50-FPN | Faster | 2 | 2x | 22.297 | 37.7 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_fpn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r50_fpn_2x.yml) | | ResNet50-FPN | Faster | 2 | 2x | 22.297 | 37.7 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_fpn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/faster_rcnn_r50_fpn_2x.yml) |
| ResNet50-FPN | Mask | 1 | 1x | 15.184 | 37.9 | 34.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/mask_rcnn_r50_fpn_1x.yml) | | ResNet50-FPN | Mask | 1 | 1x | 15.184 | 37.9 | 34.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/mask_rcnn_r50_fpn_1x.yml) |
| ResNet50-FPN | Mask | 1 | 2x | 15.881 | 38.7 | 34.7 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_fpn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/mask_rcnn_r50_fpn_2x.yml) | | ResNet50-FPN | Mask | 1 | 2x | 15.881 | 38.7 | 34.7 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_fpn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/mask_rcnn_r50_fpn_2x.yml) |
| ResNet50-FPN | Cascade Faster | 2 | 1x | 17.507 | 40.9 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_r50_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/cascade_rcnn_r50_fpn_1x.yml) | | ResNet50-FPN | Cascade Faster | 2 | 1x | 17.507 | 40.9 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_r50_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/cascade_rcnn_r50_fpn_1x.yml) |
| ResNet50-FPN | Cascade Mask | 1 | 1x | 12.43 | 41.3 | 35.5 | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_mask_rcnn_r50_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/cascade_mask_rcnn_r50_fpn_1x.yml) | | ResNet50-FPN | Cascade Mask | 1 | 1x | 12.43 | 41.3 | 35.5 | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_mask_rcnn_r50_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/cascade_mask_rcnn_r50_fpn_1x.yml) |
| ResNet50-vd-FPN | Faster | 2 | 2x | 21.847 | 38.9 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_fpn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r50_vd_fpn_2x.yml) | | ResNet50-vd-FPN | Faster | 2 | 2x | 21.847 | 38.9 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_fpn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/faster_rcnn_r50_vd_fpn_2x.yml) |
| ResNet50-vd-FPN | Mask | 1 | 2x | 15.825 | 39.8 | 35.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_vd_fpn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/mask_rcnn_r50_vd_fpn_2x.yml) | | ResNet50-vd-FPN | Mask | 1 | 2x | 15.825 | 39.8 | 35.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_vd_fpn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/mask_rcnn_r50_vd_fpn_2x.yml) |
| CBResNet50-vd-FPN | Faster | 2 | 1x | - | 39.7 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_cbr50_vd_dual_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_cbr50_vd_dual_fpn_1x.yml) | | CBResNet50-vd-FPN | Faster | 2 | 1x | - | 39.7 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_cbr50_vd_dual_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/faster_rcnn_cbr50_vd_dual_fpn_1x.yml) |
| ResNet101 | Faster | 1 | 1x | 9.316 | 38.3 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r101_1x.yml) | | ResNet101 | Faster | 1 | 1x | 9.316 | 38.3 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/faster_rcnn_r101_1x.yml) |
| ResNet101-FPN | Faster | 1 | 1x | 17.297 | 38.7 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r101_fpn_1x.yml) | | ResNet101-FPN | Faster | 1 | 1x | 17.297 | 38.7 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/faster_rcnn_r101_fpn_1x.yml) |
| ResNet101-FPN | Faster | 1 | 2x | 17.246 | 39.1 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_fpn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r101_fpn_2x.yml) | | ResNet101-FPN | Faster | 1 | 2x | 17.246 | 39.1 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_fpn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/faster_rcnn_r101_fpn_2x.yml) |
| ResNet101-FPN | Mask | 1 | 1x | 12.983 | 39.5 | 35.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r101_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/mask_rcnn_r101_fpn_1x.yml) | | ResNet101-FPN | Mask | 1 | 1x | 12.983 | 39.5 | 35.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r101_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/mask_rcnn_r101_fpn_1x.yml) |
| ResNet101-vd-FPN | Faster | 1 | 1x | 17.011 | 40.5 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_vd_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r101_vd_fpn_1x.yml) | | ResNet101-vd-FPN | Faster | 1 | 1x | 17.011 | 40.5 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_vd_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/faster_rcnn_r101_vd_fpn_1x.yml) |
| ResNet101-vd-FPN | Faster | 1 | 2x | 16.934 | 40.8 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_vd_fpn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r101_vd_fpn_2x.yml) | | ResNet101-vd-FPN | Faster | 1 | 2x | 16.934 | 40.8 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_vd_fpn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/faster_rcnn_r101_vd_fpn_2x.yml) |
| ResNet101-vd-FPN | Mask | 1 | 1x | 13.105 | 41.4 | 36.8 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r101_vd_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/mask_rcnn_r101_vd_fpn_1x.yml) | | ResNet101-vd-FPN | Mask | 1 | 1x | 13.105 | 41.4 | 36.8 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r101_vd_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/mask_rcnn_r101_vd_fpn_1x.yml) |
| CBResNet101-vd-FPN | Faster | 2 | 1x | - | 42.7 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_cbr101_vd_dual_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_cbr101_vd_dual_fpn_1x.yml) | | CBResNet101-vd-FPN | Faster | 2 | 1x | - | 42.7 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_cbr101_vd_dual_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/faster_rcnn_cbr101_vd_dual_fpn_1x.yml) |
| ResNeXt101-vd-64x4d-FPN | Faster | 1 | 1x | 8.815 | 42.2 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_x101_vd_64x4d_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_x101_vd_64x4d_fpn_1x.yml) | | ResNeXt101-vd-64x4d-FPN | Faster | 1 | 1x | 8.815 | 42.2 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_x101_vd_64x4d_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/faster_rcnn_x101_vd_64x4d_fpn_1x.yml) |
| ResNeXt101-vd-64x4d-FPN | Faster | 1 | 2x | 8.809 | 41.7 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_x101_vd_64x4d_fpn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_x101_vd_64x4d_fpn_2x.yml) | | ResNeXt101-vd-64x4d-FPN | Faster | 1 | 2x | 8.809 | 41.7 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_x101_vd_64x4d_fpn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/faster_rcnn_x101_vd_64x4d_fpn_2x.yml) |
| ResNeXt101-vd-64x4d-FPN | Mask | 1 | 1x | 7.689 | 42.9 | 37.9 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_x101_vd_64x4d_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/mask_rcnn_x101_vd_64x4d_fpn_1x.yml) | | ResNeXt101-vd-64x4d-FPN | Mask | 1 | 1x | 7.689 | 42.9 | 37.9 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_x101_vd_64x4d_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/mask_rcnn_x101_vd_64x4d_fpn_1x.yml) |
| ResNeXt101-vd-64x4d-FPN | Mask | 1 | 2x | 7.859 | 42.6 | 37.6 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_x101_vd_64x4d_fpn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/mask_rcnn_x101_vd_64x4d_fpn_2x.yml) | | ResNeXt101-vd-64x4d-FPN | Mask | 1 | 2x | 7.859 | 42.6 | 37.6 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_x101_vd_64x4d_fpn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/mask_rcnn_x101_vd_64x4d_fpn_2x.yml) |
| SENet154-vd-FPN | Faster | 1 | 1.44x | 3.408 | 42.9 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_se154_vd_fpn_s1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_se154_vd_fpn_s1x.yml) | | SENet154-vd-FPN | Faster | 1 | 1.44x | 3.408 | 42.9 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_se154_vd_fpn_s1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/faster_rcnn_se154_vd_fpn_s1x.yml) |
| SENet154-vd-FPN | Mask | 1 | 1.44x | 3.233 | 44.0 | 38.7 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_se154_vd_fpn_s1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/mask_rcnn_se154_vd_fpn_s1x.yml) | | SENet154-vd-FPN | Mask | 1 | 1.44x | 3.233 | 44.0 | 38.7 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_se154_vd_fpn_s1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/mask_rcnn_se154_vd_fpn_s1x.yml) |
| ResNet101-vd-FPN | CascadeClsAware Faster | 2 | 1x | - | 44.7(softnms) | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_cls_aware_r101_vd_fpn_1x_softnms.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/cascade_rcnn_cls_aware_r101_vd_fpn_1x_softnms.yml) | | ResNet101-vd-FPN | CascadeClsAware Faster | 2 | 1x | - | 44.7(softnms) | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_cls_aware_r101_vd_fpn_1x_softnms.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/cascade_rcnn_cls_aware_r101_vd_fpn_1x_softnms.yml) |
| ResNet101-vd-FPN | CascadeClsAware Faster | 2 | 1x | - | 46.5(multi-scale test) | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_cls_aware_r101_vd_fpn_1x_softnms.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/cascade_rcnn_cls_aware_r101_vd_fpn_1x_softnms.yml) | | ResNet101-vd-FPN | CascadeClsAware Faster | 2 | 1x | - | 46.5(multi-scale test) | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_cls_aware_r101_vd_fpn_1x_softnms.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/cascade_rcnn_cls_aware_r101_vd_fpn_1x_softnms.yml) |
### Deformable ConvNets v2 ### Deformable ConvNets v2
| Backbone | Type | Conv | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download | Configs | | Backbone | Type | Conv | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download | Configs |
| :---------------------- | :------------- | :---: | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: | :----: | | :---------------------- | :------------- | :---: | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: | :----: |
| ResNet50-FPN | Faster | c3-c5 | 2 | 1x | 19.978 | 41.0 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_r50_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/faster_rcnn_dcn_r50_fpn_1x.yml) | | ResNet50-FPN | Faster | c3-c5 | 2 | 1x | 19.978 | 41.0 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_r50_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/dcn/faster_rcnn_dcn_r50_fpn_1x.yml) |
| ResNet50-vd-FPN | Faster | c3-c5 | 2 | 2x | 19.222 | 42.4 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_r50_vd_fpn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/faster_rcnn_dcn_r50_vd_fpn_2x.yml) | | ResNet50-vd-FPN | Faster | c3-c5 | 2 | 2x | 19.222 | 42.4 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_r50_vd_fpn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/dcn/faster_rcnn_dcn_r50_vd_fpn_2x.yml) |
| ResNet101-vd-FPN | Faster | c3-c5 | 2 | 1x | 14.477 | 44.1 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_r101_vd_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/faster_rcnn_dcn_r101_vd_fpn_1x.yml) | | ResNet101-vd-FPN | Faster | c3-c5 | 2 | 1x | 14.477 | 44.1 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_r101_vd_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/dcn/faster_rcnn_dcn_r101_vd_fpn_1x.yml) |
| ResNeXt101-vd-64x4d-FPN | Faster | c3-c5 | 1 | 1x | 7.209 | 45.2 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_x101_vd_64x4d_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/faster_rcnn_dcn_x101_vd_64x4d_fpn_1x.yml) | | ResNeXt101-vd-64x4d-FPN | Faster | c3-c5 | 1 | 1x | 7.209 | 45.2 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_x101_vd_64x4d_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/dcn/faster_rcnn_dcn_x101_vd_64x4d_fpn_1x.yml) |
| ResNet50-FPN | Mask | c3-c5 | 1 | 1x | 14.53 | 41.9 | 37.3 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_dcn_r50_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/mask_rcnn_dcn_r50_fpn_1x.yml) | | ResNet50-FPN | Mask | c3-c5 | 1 | 1x | 14.53 | 41.9 | 37.3 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_dcn_r50_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/dcn/mask_rcnn_dcn_r50_fpn_1x.yml) |
| ResNet50-vd-FPN | Mask | c3-c5 | 1 | 2x | 14.832 | 42.9 | 38.0 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_dcn_r50_vd_fpn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/mask_rcnn_dcn_r50_vd_fpn_2x.yml) | | ResNet50-vd-FPN | Mask | c3-c5 | 1 | 2x | 14.832 | 42.9 | 38.0 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_dcn_r50_vd_fpn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/dcn/mask_rcnn_dcn_r50_vd_fpn_2x.yml) |
| ResNet101-vd-FPN | Mask | c3-c5 | 1 | 1x | 11.546 | 44.6 | 39.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_dcn_r101_vd_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/mask_rcnn_dcn_r101_vd_fpn_1x.yml) | | ResNet101-vd-FPN | Mask | c3-c5 | 1 | 1x | 11.546 | 44.6 | 39.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_dcn_r101_vd_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/dcn/mask_rcnn_dcn_r101_vd_fpn_1x.yml) |
| ResNeXt101-vd-64x4d-FPN | Mask | c3-c5 | 1 | 1x | 6.45 | 46.2 | 40.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_dcn_x101_vd_64x4d_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/mask_rcnn_dcn_x101_vd_64x4d_fpn_1x.yml) | | ResNeXt101-vd-64x4d-FPN | Mask | c3-c5 | 1 | 1x | 6.45 | 46.2 | 40.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_dcn_x101_vd_64x4d_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/dcn/mask_rcnn_dcn_x101_vd_64x4d_fpn_1x.yml) |
| ResNet50-FPN | Cascade Faster | c3-c5 | 2 | 1x | - | 44.2 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_r50_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/cascade_rcnn_dcn_r50_fpn_1x.yml) | | ResNet50-FPN | Cascade Faster | c3-c5 | 2 | 1x | - | 44.2 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_r50_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/dcn/cascade_rcnn_dcn_r50_fpn_1x.yml) |
| ResNet101-vd-FPN | Cascade Faster | c3-c5 | 2 | 1x | - | 46.4 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_r101_vd_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/cascade_rcnn_dcn_r101_vd_fpn_1x.yml) | | ResNet101-vd-FPN | Cascade Faster | c3-c5 | 2 | 1x | - | 46.4 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_r101_vd_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/dcn/cascade_rcnn_dcn_r101_vd_fpn_1x.yml) |
| ResNeXt101-vd-FPN | Cascade Faster | c3-c5 | 2 | 1x | - | 47.3 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_x101_vd_64x4d_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/cascade_rcnn_dcn_x101_vd_64x4d_fpn_1x.yml) | | ResNeXt101-vd-FPN | Cascade Faster | c3-c5 | 2 | 1x | - | 47.3 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_x101_vd_64x4d_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/dcn/cascade_rcnn_dcn_x101_vd_64x4d_fpn_1x.yml) |
| SENet154-vd-FPN | Cascade Mask | c3-c5 | 1 | 1.44x | - | 51.9 | 43.9 | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_mask_rcnn_dcnv2_se154_vd_fpn_gn_s1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/cascade_mask_rcnn_dcnv2_se154_vd_fpn_gn_s1x.yml) | | SENet154-vd-FPN | Cascade Mask | c3-c5 | 1 | 1.44x | - | 51.9 | 43.9 | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_mask_rcnn_dcnv2_se154_vd_fpn_gn_s1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/dcn/cascade_mask_rcnn_dcnv2_se154_vd_fpn_gn_s1x.yml) |
| ResNet200-vd-FPN-Nonlocal | CascadeClsAware Faster | c3-c5 | 1 | 2.5x | 3.103 | 51.7%(softnms) | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.yml) | | ResNet200-vd-FPN-Nonlocal | CascadeClsAware Faster | c3-c5 | 1 | 2.5x | 3.103 | 51.7%(softnms) | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/dcn/cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.yml) |
| CBResNet200-vd-FPN-Nonlocal | Cascade Faster | c3-c5 | 1 | 2.5x | 1.68 | 53.3%(softnms) | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_cbr200_vd_fpn_dcnv2_nonlocal_softnms.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/cascade_rcnn_cbr200_vd_fpn_dcnv2_nonlocal_softnms.yml) | | CBResNet200-vd-FPN-Nonlocal | Cascade Faster | c3-c5 | 1 | 2.5x | 1.68 | 53.3%(softnms) | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_cbr200_vd_fpn_dcnv2_nonlocal_softnms.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/dcn/cascade_rcnn_cbr200_vd_fpn_dcnv2_nonlocal_softnms.yml) |
**Notes:** **Notes:**
- Deformable ConvNets v2(dcn_v2) reference from [Deformable ConvNets v2](https://arxiv.org/abs/1811.11168). - Deformable ConvNets v2(dcn_v2) reference from [Deformable ConvNets v2](https://arxiv.org/abs/1811.11168).
- `c3-c5` means adding `dcn` in resnet stage 3 to 5. - `c3-c5` means adding `dcn` in resnet stage 3 to 5.
- Detailed configuration file in [configs/dcn](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn) - Detailed configuration file in [configs/dcn](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/dcn)
### HRNet ### HRNet
* See more details in [HRNet model zoo](https://github.com/PaddlePaddle/PaddleDetection/blob/master/configs/hrnet/). * See more details in [HRNet model zoo](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/configs/hrnet/).
### Res2Net ### Res2Net
* See more details in [Res2Net model zoo](https://github.com/PaddlePaddle/PaddleDetection/blob/master/configs/res2net/). * See more details in [Res2Net model zoo](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/configs/res2net/).
### IOU loss ### IOU loss
* GIOU loss and DIOU loss are included now. See more details in [IOU loss model zoo](https://github.com/PaddlePaddle/PaddleDetection/blob/master/configs/iou_loss/). * GIOU loss and DIOU loss are included now. See more details in [IOU loss model zoo](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/configs/iou_loss/).
### GCNet ### GCNet
* See more details in [GCNet model zoo](https://github.com/PaddlePaddle/PaddleDetection/blob/master/configs/gcnet/). * See more details in [GCNet model zoo](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/configs/gcnet/).
### Libra R-CNN ### Libra R-CNN
* See more details in [Libra R-CNN model zoo](https://github.com/PaddlePaddle/PaddleDetection/blob/master/configs/libra_rcnn/). * See more details in [Libra R-CNN model zoo](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/configs/libra_rcnn/).
### Auto Augmentation ### Auto Augmentation
* See more details in [Auto Augmentation model zoo](https://github.com/PaddlePaddle/PaddleDetection/blob/master/configs/autoaugment/). * See more details in [Auto Augmentation model zoo](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/configs/autoaugment/).
### Group Normalization ### Group Normalization
| Backbone | Type | Image/gpu | Lr schd | Box AP | Mask AP | Download | Configs | | Backbone | Type | Image/gpu | Lr schd | Box AP | Mask AP | Download | Configs |
| :------------------- | :------------- | :-----: | :-----: | :----: | :-----: | :----------------------------------------------------------: |:----: | | :------------------- | :------------- | :-----: | :-----: | :----: | :-----: | :----------------------------------------------------------: |:----: |
| ResNet50-FPN | Faster | 2 | 2x | 39.7 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_fpn_gn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/gn/faster_rcnn_r50_fpn_gn_2x.yml) | | ResNet50-FPN | Faster | 2 | 2x | 39.7 | - | [model](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_fpn_gn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/gn/faster_rcnn_r50_fpn_gn_2x.yml) |
| ResNet50-FPN | Mask | 1 | 2x | 40.1 | 35.8 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_fpn_gn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/gn/mask_rcnn_r50_fpn_gn_2x.yml) | | ResNet50-FPN | Mask | 1 | 2x | 40.1 | 35.8 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_fpn_gn_2x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/gn/mask_rcnn_r50_fpn_gn_2x.yml) |
**Notes:** **Notes:**
- Group Normalization reference from [Group Normalization](https://arxiv.org/abs/1803.08494). - Group Normalization reference from [Group Normalization](https://arxiv.org/abs/1803.08494).
- Detailed configuration file in [configs/gn](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/gn) - Detailed configuration file in [configs/gn](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/gn)
### YOLO v3 ### YOLO v3
...@@ -134,35 +134,35 @@ The backbone models pretrained on ImageNet are available. All backbone models ar ...@@ -134,35 +134,35 @@ The backbone models pretrained on ImageNet are available. All backbone models ar
| DarkNet53 (paper) | ImageNet | 608 | False | 8 | 270e | - | 33.0 | - | - | | DarkNet53 (paper) | ImageNet | 608 | False | 8 | 270e | - | 33.0 | - | - |
| DarkNet53 (paper) | ImageNet | 416 | False | 8 | 270e | - | 31.0 | - | - | | DarkNet53 (paper) | ImageNet | 416 | False | 8 | 270e | - | 31.0 | - | - |
| DarkNet53 (paper) | ImageNet | 320 | False | 8 | 270e | - | 28.2 | - | - | | DarkNet53 (paper) | ImageNet | 320 | False | 8 | 270e | - | 28.2 | - | - |
| DarkNet53 | ImageNet | 608 | False | 8 | 270e | 45.571 | 38.9 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_darknet.yml) | | DarkNet53 | ImageNet | 608 | False | 8 | 270e | 45.571 | 38.9 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_darknet.yml) |
| DarkNet53 | ImageNet | 416 | False | 8 | 270e | - | 37.5 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_darknet.yml) | | DarkNet53 | ImageNet | 416 | False | 8 | 270e | - | 37.5 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_darknet.yml) |
| DarkNet53 | ImageNet | 320 | False | 8 | 270e | - | 34.8 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_darknet.yml) | | DarkNet53 | ImageNet | 320 | False | 8 | 270e | - | 34.8 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_darknet.yml) |
| MobileNet-V1 | ImageNet | 608 | False | 8 | 270e | 78.302 | 29.3 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_mobilenet_v1.yml) | | MobileNet-V1 | ImageNet | 608 | False | 8 | 270e | 78.302 | 29.3 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_mobilenet_v1.yml) |
| MobileNet-V1 | ImageNet | 416 | False | 8 | 270e | - | 29.3 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_mobilenet_v1.yml) | | MobileNet-V1 | ImageNet | 416 | False | 8 | 270e | - | 29.3 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_mobilenet_v1.yml) |
| MobileNet-V1 | ImageNet | 320 | False | 8 | 270e | - | 27.1 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_mobilenet_v1.yml) | | MobileNet-V1 | ImageNet | 320 | False | 8 | 270e | - | 27.1 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_mobilenet_v1.yml) |
| MobileNet-V3 | ImageNet | 608 | False | 8 | 270e | - | 31.6 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v3.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_mobilenet_v3.yml) | | MobileNet-V3 | ImageNet | 608 | False | 8 | 270e | - | 31.6 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v3.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_mobilenet_v3.yml) |
| MobileNet-V3 | ImageNet | 416 | False | 8 | 270e | - | 29.9 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v3.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_mobilenet_v3.yml) | | MobileNet-V3 | ImageNet | 416 | False | 8 | 270e | - | 29.9 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v3.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_mobilenet_v3.yml) |
| MobileNet-V3 | ImageNet | 320 | False | 8 | 270e | - | 27.1 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v3.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_mobilenet_v3.yml) | | MobileNet-V3 | ImageNet | 320 | False | 8 | 270e | - | 27.1 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v3.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_mobilenet_v3.yml) |
| ResNet34 | ImageNet | 608 | False | 8 | 270e | 63.356 | 36.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_r34.yml) | | ResNet34 | ImageNet | 608 | False | 8 | 270e | 63.356 | 36.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_r34.yml) |
| ResNet34 | ImageNet | 416 | False | 8 | 270e | - | 34.3 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_r34.yml) | | ResNet34 | ImageNet | 416 | False | 8 | 270e | - | 34.3 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_r34.yml) |
| ResNet34 | ImageNet | 320 | False | 8 | 270e | - | 31.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_r34.yml) | | ResNet34 | ImageNet | 320 | False | 8 | 270e | - | 31.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_r34.yml) |
| ResNet50_vd | ImageNet | 608 | True | 8 | 270e | - | 39.1 | [model](https://paddlemodels.bj.bcebos.com/object_detection/dcn/yolov3_r50vd_dcn.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/yolov3_r50vd_dcn.yml) | | ResNet50_vd | ImageNet | 608 | True | 8 | 270e | - | 39.1 | [model](https://paddlemodels.bj.bcebos.com/object_detection/dcn/yolov3_r50vd_dcn.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/dcn/yolov3_r50vd_dcn.yml) |
| ResNet50_vd | Object365 | 608 | True | 8 | 270e | - | 41.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn_obj365_pretrained_coco.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/yolov3_r50vd_dcn_obj365_pretrained_coco.yml) | | ResNet50_vd | Object365 | 608 | True | 8 | 270e | - | 41.4 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn_obj365_pretrained_coco.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/dcn/yolov3_r50vd_dcn_obj365_pretrained_coco.yml) |
### YOLO v3 on Pascal VOC ### YOLO v3 on Pascal VOC
| Backbone | Size | Image/gpu | Lr schd | Inf time (fps) | Box AP(0.5) | Download | Configs | | Backbone | Size | Image/gpu | Lr schd | Inf time (fps) | Box AP(0.5) | Download | Configs |
| :----------- | :--: | :-------: | :-----: | :------------: | :----: | :----------------------------------------------------------: | :----: | | :----------- | :--: | :-------: | :-----: | :------------: | :----: | :----------------------------------------------------------: | :----: |
| DarkNet53 | 608 | 8 | 270e | 54.977 | 83.5 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet_voc.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_darknet_voc.yml) | | DarkNet53 | 608 | 8 | 270e | 54.977 | 83.5 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet_voc.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_darknet_voc.yml) |
| DarkNet53 | 416 | 8 | 270e | - | 83.6 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet_voc.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_darknet_voc.yml) | | DarkNet53 | 416 | 8 | 270e | - | 83.6 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet_voc.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_darknet_voc.yml) |
| DarkNet53 | 320 | 8 | 270e | - | 82.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet_voc.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_darknet_voc.yml) | | DarkNet53 | 320 | 8 | 270e | - | 82.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet_voc.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_darknet_voc.yml) |
| DarkNet53 Diou-Loss | 608 | 8 | 270e | - | 83.5 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet_voc_diouloss.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_darknet_voc_diouloss.yml) | | DarkNet53 Diou-Loss | 608 | 8 | 270e | - | 83.5 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet_voc_diouloss.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_darknet_voc_diouloss.yml) |
| MobileNet-V1 | 608 | 8 | 270e | 104.291 | 76.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1_voc.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_mobilenet_v1_voc.yml) | | MobileNet-V1 | 608 | 8 | 270e | 104.291 | 76.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1_voc.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_mobilenet_v1_voc.yml) |
| MobileNet-V1 | 416 | 8 | 270e | - | 76.7 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1_voc.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_mobilenet_v1_voc.yml) | | MobileNet-V1 | 416 | 8 | 270e | - | 76.7 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1_voc.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_mobilenet_v1_voc.yml) |
| MobileNet-V1 | 320 | 8 | 270e | - | 75.3 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1_voc.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_mobilenet_v1_voc.yml) | | MobileNet-V1 | 320 | 8 | 270e | - | 75.3 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1_voc.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_mobilenet_v1_voc.yml) |
| ResNet34 | 608 | 8 | 270e | 82.247 | 82.6 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34_voc.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_r34_voc.yml) | | ResNet34 | 608 | 8 | 270e | 82.247 | 82.6 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34_voc.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_r34_voc.yml) |
| ResNet34 | 416 | 8 | 270e | - | 81.9 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34_voc.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_r34_voc.yml) | | ResNet34 | 416 | 8 | 270e | - | 81.9 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34_voc.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_r34_voc.yml) |
| ResNet34 | 320 | 8 | 270e | - | 80.1 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34_voc.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_r34_voc.yml) | | ResNet34 | 320 | 8 | 270e | - | 80.1 | [model](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34_voc.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_r34_voc.yml) |
**Notes:** **Notes:**
...@@ -179,9 +179,9 @@ results of image size 608/416/320 above. Deformable conv is added on stage 5 of ...@@ -179,9 +179,9 @@ results of image size 608/416/320 above. Deformable conv is added on stage 5 of
| Backbone | Image/gpu | Lr schd | Inf time (fps) | Box AP | Download | Configs | | Backbone | Image/gpu | Lr schd | Inf time (fps) | Box AP | Download | Configs |
| :---------------: | :-----: | :-----: | :----: | :----: | :-------: | :----: | | :---------------: | :-----: | :-----: | :----: | :----: | :-------: | :----: |
| ResNet50-FPN | 2 | 1x | - | 36.0 | [model](https://paddlemodels.bj.bcebos.com/object_detection/retinanet_r50_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/retinanet_r50_fpn_1x.yml) | | ResNet50-FPN | 2 | 1x | - | 36.0 | [model](https://paddlemodels.bj.bcebos.com/object_detection/retinanet_r50_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/retinanet_r50_fpn_1x.yml) |
| ResNet101-FPN | 2 | 1x | - | 37.3 | [model](https://paddlemodels.bj.bcebos.com/object_detection/retinanet_r101_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/retinanet_r101_fpn_1x.yml) | | ResNet101-FPN | 2 | 1x | - | 37.3 | [model](https://paddlemodels.bj.bcebos.com/object_detection/retinanet_r101_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/retinanet_r101_fpn_1x.yml) |
| ResNeXt101-vd-FPN | 1 | 1x | - | 40.5 | [model](https://paddlemodels.bj.bcebos.com/object_detection/retinanet_x101_vd_64x4d_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/retinanet_x101_vd_64x4d_fpn_1x.yml) | | ResNeXt101-vd-FPN | 1 | 1x | - | 40.5 | [model](https://paddlemodels.bj.bcebos.com/object_detection/retinanet_x101_vd_64x4d_fpn_1x.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/retinanet_x101_vd_64x4d_fpn_1x.yml) |
**Notes:** In RetinaNet, the base LR is changed to 0.01 for minibatch size 16. **Notes:** In RetinaNet, the base LR is changed to 0.01 for minibatch size 16.
...@@ -197,12 +197,12 @@ results of image size 608/416/320 above. Deformable conv is added on stage 5 of ...@@ -197,12 +197,12 @@ results of image size 608/416/320 above. Deformable conv is added on stage 5 of
| Backbone | Size | Image/gpu | Lr schd | Inf time (fps) | Box AP | Download | Configs | | Backbone | Size | Image/gpu | Lr schd | Inf time (fps) | Box AP | Download | Configs |
| :------: | :--: | :-------: | :-----: | :------------: | :----: | :----------------------------------------------------------: | :----: | | :------: | :--: | :-------: | :-----: | :------------: | :----: | :----------------------------------------------------------: | :----: |
| MobileNet_v1 | 300 | 64 | Cosine decay(40w) | - | 23.6 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ssdlite_mobilenet_v1.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ssd/ssdlite_mobilenet_v1.yml) | | MobileNet_v1 | 300 | 64 | Cosine decay(40w) | - | 23.6 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ssdlite_mobilenet_v1.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ssd/ssdlite_mobilenet_v1.yml) |
| MobileNet_v3 small | 320 | 64 | Cosine decay(40w) | - | 16.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/ssdlite_mobilenet_v3_small.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ssd/ssdlite_mobilenet_v3_small.yml) | | MobileNet_v3 small | 320 | 64 | Cosine decay(40w) | - | 16.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/ssdlite_mobilenet_v3_small.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ssd/ssdlite_mobilenet_v3_small.yml) |
| MobileNet_v3 large | 320 | 64 | Cosine decay(40w) | - | 23.3 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/ssdlite_mobilenet_v3_large.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ssd/ssdlite_mobilenet_v3_large.yml) | | MobileNet_v3 large | 320 | 64 | Cosine decay(40w) | - | 23.3 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/ssdlite_mobilenet_v3_large.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ssd/ssdlite_mobilenet_v3_large.yml) |
| MobileNet_v3 small w/ FPN | 320 | 64 | Cosine decay(40w) | - | 18.9 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/ssdlite_mobilenet_v3_small_fpn.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ssd/ssdlite_mobilenet_v3_small_fpn.yml) | | MobileNet_v3 small w/ FPN | 320 | 64 | Cosine decay(40w) | - | 18.9 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/ssdlite_mobilenet_v3_small_fpn.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ssd/ssdlite_mobilenet_v3_small_fpn.yml) |
| MobileNet_v3 large w/ FPN | 320 | 64 | Cosine decay(40w) | - | 24.3 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/ssdlite_mobilenet_v3_large_fpn.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ssd/ssdlite_mobilenet_v3_large_fpn.yml) | | MobileNet_v3 large w/ FPN | 320 | 64 | Cosine decay(40w) | - | 24.3 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/ssdlite_mobilenet_v3_large_fpn.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ssd/ssdlite_mobilenet_v3_large_fpn.yml) |
| GhostNet | 320 | 64 | Cosine decay(40w) | - | 23.3 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/ssdlite_ghostnet.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ssd/ssdlite_ghostnet.yml) | | GhostNet | 320 | 64 | Cosine decay(40w) | - | 23.3 | [model](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/ssdlite_ghostnet.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ssd/ssdlite_ghostnet.yml) |
**Notes:** `SSDLite` is trained in 8 GPU with total batch size as 512 and uses cosine decay strategy to train. **Notes:** `SSDLite` is trained in 8 GPU with total batch size as 512 and uses cosine decay strategy to train.
...@@ -210,8 +210,8 @@ results of image size 608/416/320 above. Deformable conv is added on stage 5 of ...@@ -210,8 +210,8 @@ results of image size 608/416/320 above. Deformable conv is added on stage 5 of
| Backbone | Size | Image/gpu | Lr schd | Inf time (fps) | Box AP | Download | Configs | | Backbone | Size | Image/gpu | Lr schd | Inf time (fps) | Box AP | Download | Configs |
| :------: | :--: | :-------: | :-----: | :------------: | :----: | :----------------------------------------------------------: | :----: | | :------: | :--: | :-------: | :-----: | :------------: | :----: | :----------------------------------------------------------: | :----: |
| VGG16 | 300 | 8 | 40w | 81.613 | 25.1 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ssd_vgg16_300.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ssd/ssd_vgg16_300.yml) | | VGG16 | 300 | 8 | 40w | 81.613 | 25.1 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ssd_vgg16_300.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ssd/ssd_vgg16_300.yml) |
| VGG16 | 512 | 8 | 40w | 46.007 | 29.1 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ssd_vgg16_512.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ssd/ssd_vgg16_512.yml) | | VGG16 | 512 | 8 | 40w | 46.007 | 29.1 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ssd_vgg16_512.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ssd/ssd_vgg16_512.yml) |
**Notes:** VGG-SSD is trained in 4 GPU with total batch size as 32 and trained 400000 iters. **Notes:** VGG-SSD is trained in 4 GPU with total batch size as 32 and trained 400000 iters.
...@@ -219,9 +219,9 @@ results of image size 608/416/320 above. Deformable conv is added on stage 5 of ...@@ -219,9 +219,9 @@ results of image size 608/416/320 above. Deformable conv is added on stage 5 of
| Backbone | Size | Image/gpu | Lr schd | Inf time (fps) | Box AP(0.5) | Download | Configs | | Backbone | Size | Image/gpu | Lr schd | Inf time (fps) | Box AP(0.5) | Download | Configs |
| :----------- | :--: | :-------: | :-----: | :------------: | :----: | :----------------------------------------------------------: | :----: | | :----------- | :--: | :-------: | :-----: | :------------: | :----: | :----------------------------------------------------------: | :----: |
| MobileNet v1 | 300 | 32 | 120e | 159.543 | 73.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ssd_mobilenet_v1_voc.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ssd/ssd_mobilenet_v1_voc.yml) | | MobileNet v1 | 300 | 32 | 120e | 159.543 | 73.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ssd_mobilenet_v1_voc.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ssd/ssd_mobilenet_v1_voc.yml) |
| VGG16 | 300 | 8 | 240e | 117.279 | 77.5 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ssd_vgg16_300_voc.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ssd/ssd_vgg16_300_voc.yml) | | VGG16 | 300 | 8 | 240e | 117.279 | 77.5 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ssd_vgg16_300_voc.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ssd/ssd_vgg16_300_voc.yml) |
| VGG16 | 512 | 8 | 240e | 65.975 | 80.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ssd_vgg16_512_voc.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ssd/ssd_vgg16_512_voc.yml) | | VGG16 | 512 | 8 | 240e | 65.975 | 80.2 | [model](https://paddlemodels.bj.bcebos.com/object_detection/ssd_vgg16_512_voc.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ssd/ssd_vgg16_512_voc.yml) |
**NOTE**: MobileNet-SSD is trained in 2 GPU with totoal batch size as 64 and trained 120 epoches. VGG-SSD is trained in 4 GPU with total batch size as 32 and trained 240 epoches. SSD training data augmentations: randomly color distortion, **NOTE**: MobileNet-SSD is trained in 2 GPU with totoal batch size as 64 and trained 120 epoches. VGG-SSD is trained in 4 GPU with total batch size as 32 and trained 240 epoches. SSD training data augmentations: randomly color distortion,
randomly cropping, randomly expansion, randomly flipping. randomly cropping, randomly expansion, randomly flipping.
......
static/docs/MODEL_ZOO_cn.md
浏览文件 @ 99c7e3a7
...@@ -33,95 +33,95 @@ Paddle提供基于ImageNet的骨架网络预训练模型。所有预训练模型 ...@@ -33,95 +33,95 @@ Paddle提供基于ImageNet的骨架网络预训练模型。所有预训练模型
| 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 | Mask AP | 下载 | 配置文件 | | 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 | Faster | 1 | 1x | 12.747 | 35.2 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r50_1x.yml) | | ResNet50 | Faster | 1 | 1x | 12.747 | 35.2 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/faster_rcnn_r50_1x.yml) |
| ResNet50 | Faster | 1 | 2x | 12.686 | 37.1 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r50_2x.yml) | | ResNet50 | Faster | 1 | 2x | 12.686 | 37.1 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/faster_rcnn_r50_2x.yml) |
| ResNet50 | Mask | 1 | 1x | 11.615 | 36.5 | 32.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/mask_rcnn_r50_1x.yml) | | ResNet50 | Mask | 1 | 1x | 11.615 | 36.5 | 32.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/mask_rcnn_r50_1x.yml) |
| ResNet50 | Mask | 1 | 2x | 11.494 | 38.2 | 33.4 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/mask_rcnn_r50_2x.yml) | | ResNet50 | Mask | 1 | 2x | 11.494 | 38.2 | 33.4 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/mask_rcnn_r50_2x.yml) |
| ResNet50-vd | Faster | 1 | 1x | 12.575 | 36.4 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r50_vd_1x.yml) | | ResNet50-vd | Faster | 1 | 1x | 12.575 | 36.4 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/faster_rcnn_r50_vd_1x.yml) |
| ResNet34-FPN | Faster | 2 | 1x | - | 36.7 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r34_fpn_1x.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r34_fpn_1x.yml) | | ResNet34-FPN | Faster | 2 | 1x | - | 36.7 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r34_fpn_1x.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/faster_rcnn_r34_fpn_1x.yml) |
| ResNet34-vd-FPN | Faster | 2 | 1x | - | 37.4 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r34_vd_fpn_1x.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r34_vd_fpn_1x.yml) | | ResNet34-vd-FPN | Faster | 2 | 1x | - | 37.4 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r34_vd_fpn_1x.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/faster_rcnn_r34_vd_fpn_1x.yml) |
| ResNet50-FPN | Faster | 2 | 1x | 22.273 | 37.2 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r50_fpn_1x.yml) | | ResNet50-FPN | Faster | 2 | 1x | 22.273 | 37.2 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/faster_rcnn_r50_fpn_1x.yml) |
| ResNet50-FPN | Faster | 2 | 2x | 22.297 | 37.7 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_fpn_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r50_fpn_2x.yml) | | ResNet50-FPN | Faster | 2 | 2x | 22.297 | 37.7 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_fpn_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/faster_rcnn_r50_fpn_2x.yml) |
| ResNet50-FPN | Mask | 1 | 1x | 15.184 | 37.9 | 34.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/mask_rcnn_r50_fpn_1x.yml) | | ResNet50-FPN | Mask | 1 | 1x | 15.184 | 37.9 | 34.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/mask_rcnn_r50_fpn_1x.yml) |
| ResNet50-FPN | Mask | 1 | 2x | 15.881 | 38.7 | 34.7 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_fpn_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/mask_rcnn_r50_fpn_2x.yml) | | ResNet50-FPN | Mask | 1 | 2x | 15.881 | 38.7 | 34.7 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_fpn_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/mask_rcnn_r50_fpn_2x.yml) |
| ResNet50-FPN | Cascade Faster | 2 | 1x | 17.507 | 40.9 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_r50_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/cascade_rcnn_r50_fpn_1x.yml) | | ResNet50-FPN | Cascade Faster | 2 | 1x | 17.507 | 40.9 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_r50_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/cascade_rcnn_r50_fpn_1x.yml) |
| ResNet50-FPN | Cascade Mask | 1 | 1x | 12.43 | 41.3 | 35.5 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_mask_rcnn_r50_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/cascade_mask_rcnn_r50_fpn_1x.yml) | | ResNet50-FPN | Cascade Mask | 1 | 1x | 12.43 | 41.3 | 35.5 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_mask_rcnn_r50_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/cascade_mask_rcnn_r50_fpn_1x.yml) |
| ResNet50-vd-FPN | Faster | 2 | 2x | 21.847 | 38.9 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_fpn_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r50_vd_fpn_2x.yml) | | ResNet50-vd-FPN | Faster | 2 | 2x | 21.847 | 38.9 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_fpn_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/faster_rcnn_r50_vd_fpn_2x.yml) |
| ResNet50-vd-FPN | Mask | 1 | 2x | 15.825 | 39.8 | 35.4 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_vd_fpn_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/mask_rcnn_r50_vd_fpn_2x.yml) | | ResNet50-vd-FPN | Mask | 1 | 2x | 15.825 | 39.8 | 35.4 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_vd_fpn_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/mask_rcnn_r50_vd_fpn_2x.yml) |
| CBResNet50-vd-FPN | Faster | 2 | 1x | - | 39.7 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_cbr50_vd_dual_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_cbr50_vd_dual_fpn_1x.yml) | | CBResNet50-vd-FPN | Faster | 2 | 1x | - | 39.7 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_cbr50_vd_dual_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/faster_rcnn_cbr50_vd_dual_fpn_1x.yml) |
| ResNet101 | Faster | 1 | 1x | 9.316 | 38.3 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r101_1x.yml) | | ResNet101 | Faster | 1 | 1x | 9.316 | 38.3 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/faster_rcnn_r101_1x.yml) |
| ResNet101-FPN | Faster | 1 | 1x | 17.297 | 38.7 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r101_fpn_1x.yml) | | ResNet101-FPN | Faster | 1 | 1x | 17.297 | 38.7 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/faster_rcnn_r101_fpn_1x.yml) |
| ResNet101-FPN | Faster | 1 | 2x | 17.246 | 39.1 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_fpn_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r101_fpn_2x.yml) | | ResNet101-FPN | Faster | 1 | 2x | 17.246 | 39.1 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_fpn_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/faster_rcnn_r101_fpn_2x.yml) |
| ResNet101-FPN | Mask | 1 | 1x | 12.983 | 39.5 | 35.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r101_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/mask_rcnn_r101_fpn_1x.yml) | | ResNet101-FPN | Mask | 1 | 1x | 12.983 | 39.5 | 35.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r101_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/mask_rcnn_r101_fpn_1x.yml) |
| ResNet101-vd-FPN | Faster | 1 | 1x | 17.011 | 40.5 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_vd_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r101_vd_fpn_1x.yml) | | ResNet101-vd-FPN | Faster | 1 | 1x | 17.011 | 40.5 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_vd_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/faster_rcnn_r101_vd_fpn_1x.yml) |
| ResNet101-vd-FPN | Faster | 1 | 2x | 16.934 | 40.8 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_vd_fpn_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_r101_vd_fpn_2x.yml) | | ResNet101-vd-FPN | Faster | 1 | 2x | 16.934 | 40.8 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r101_vd_fpn_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/faster_rcnn_r101_vd_fpn_2x.yml) |
| ResNet101-vd-FPN | Mask | 1 | 1x | 13.105 | 41.4 | 36.8 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r101_vd_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/mask_rcnn_r101_vd_fpn_1x.yml) | | ResNet101-vd-FPN | Mask | 1 | 1x | 13.105 | 41.4 | 36.8 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r101_vd_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/mask_rcnn_r101_vd_fpn_1x.yml) |
| CBResNet101-vd-FPN | Faster | 2 | 1x | - | 42.7 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_cbr101_vd_dual_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_cbr101_vd_dual_fpn_1x.yml) | | CBResNet101-vd-FPN | Faster | 2 | 1x | - | 42.7 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_cbr101_vd_dual_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/faster_rcnn_cbr101_vd_dual_fpn_1x.yml) |
| ResNeXt101-vd-FPN | Faster | 1 | 1x | 8.815 | 42.2 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_x101_vd_64x4d_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_x101_vd_64x4d_fpn_1x.yml) | | ResNeXt101-vd-FPN | Faster | 1 | 1x | 8.815 | 42.2 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_x101_vd_64x4d_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/faster_rcnn_x101_vd_64x4d_fpn_1x.yml) |
| ResNeXt101-vd-FPN | Faster | 1 | 2x | 8.809 | 41.7 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_x101_vd_64x4d_fpn_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_x101_vd_64x4d_fpn_2x.yml) | | ResNeXt101-vd-FPN | Faster | 1 | 2x | 8.809 | 41.7 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_x101_vd_64x4d_fpn_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/faster_rcnn_x101_vd_64x4d_fpn_2x.yml) |
| ResNeXt101-vd-FPN | Mask | 1 | 1x | 7.689 | 42.9 | 37.9 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_x101_vd_64x4d_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/mask_rcnn_x101_vd_64x4d_fpn_1x.yml) | | ResNeXt101-vd-FPN | Mask | 1 | 1x | 7.689 | 42.9 | 37.9 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_x101_vd_64x4d_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/mask_rcnn_x101_vd_64x4d_fpn_1x.yml) |
| ResNeXt101-vd-FPN | Mask | 1 | 2x | 7.859 | 42.6 | 37.6 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_x101_vd_64x4d_fpn_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/mask_rcnn_x101_vd_64x4d_fpn_2x.yml) | | ResNeXt101-vd-FPN | Mask | 1 | 2x | 7.859 | 42.6 | 37.6 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_x101_vd_64x4d_fpn_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/mask_rcnn_x101_vd_64x4d_fpn_2x.yml) |
| SENet154-vd-FPN | Faster | 1 | 1.44x | 3.408 | 42.9 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_se154_vd_fpn_s1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/faster_rcnn_se154_vd_fpn_s1x.yml) | | SENet154-vd-FPN | Faster | 1 | 1.44x | 3.408 | 42.9 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_se154_vd_fpn_s1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/faster_rcnn_se154_vd_fpn_s1x.yml) |
| SENet154-vd-FPN | Mask | 1 | 1.44x | 3.233 | 44.0 | 38.7 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_se154_vd_fpn_s1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/mask_rcnn_se154_vd_fpn_s1x.yml) | | SENet154-vd-FPN | Mask | 1 | 1.44x | 3.233 | 44.0 | 38.7 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_se154_vd_fpn_s1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/mask_rcnn_se154_vd_fpn_s1x.yml) |
| ResNet101-vd-FPN | CascadeClsAware Faster | 2 | 1x | - | 44.7(softnms) | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_cls_aware_r101_vd_fpn_1x_softnms.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/cascade_rcnn_cls_aware_r101_vd_fpn_1x_softnms.yml) | | ResNet101-vd-FPN | CascadeClsAware Faster | 2 | 1x | - | 44.7(softnms) | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_cls_aware_r101_vd_fpn_1x_softnms.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/cascade_rcnn_cls_aware_r101_vd_fpn_1x_softnms.yml) |
| ResNet101-vd-FPN | CascadeClsAware Faster | 2 | 1x | - | 46.5(multi-scale test) | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_cls_aware_r101_vd_fpn_1x_softnms.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/cascade_rcnn_cls_aware_r101_vd_fpn_1x_softnms.yml) | | ResNet101-vd-FPN | CascadeClsAware Faster | 2 | 1x | - | 46.5(multi-scale test) | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_cls_aware_r101_vd_fpn_1x_softnms.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/cascade_rcnn_cls_aware_r101_vd_fpn_1x_softnms.yml) |
### Deformable 卷积网络v2 ### Deformable 卷积网络v2
| 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 | | 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 | 2 | 1x | 19.978 | 41.0 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_r50_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/faster_rcnn_dcn_r50_fpn_1x.yml) | | ResNet50-FPN | Faster | c3-c5 | 2 | 1x | 19.978 | 41.0 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_r50_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/dcn/faster_rcnn_dcn_r50_fpn_1x.yml) |
| ResNet50-vd-FPN | Faster | c3-c5 | 2 | 2x | 19.222 | 42.4 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_r50_vd_fpn_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/faster_rcnn_dcn_r50_vd_fpn_2x.yml) | | ResNet50-vd-FPN | Faster | c3-c5 | 2 | 2x | 19.222 | 42.4 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_r50_vd_fpn_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/dcn/faster_rcnn_dcn_r50_vd_fpn_2x.yml) |
| ResNet101-vd-FPN | Faster | c3-c5 | 2 | 1x | 14.477 | 44.1 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_r101_vd_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/faster_rcnn_dcn_r101_vd_fpn_1x.yml) | | ResNet101-vd-FPN | Faster | c3-c5 | 2 | 1x | 14.477 | 44.1 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_r101_vd_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/dcn/faster_rcnn_dcn_r101_vd_fpn_1x.yml) |
| ResNeXt101-vd-FPN | Faster | c3-c5 | 1 | 1x | 7.209 | 45.2 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_x101_vd_64x4d_fpn_1x.tar) |[配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/faster_rcnn_dcn_x101_vd_64x4d_fpn_1x.yml) | | ResNeXt101-vd-FPN | Faster | c3-c5 | 1 | 1x | 7.209 | 45.2 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_dcn_x101_vd_64x4d_fpn_1x.tar) |[配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/dcn/faster_rcnn_dcn_x101_vd_64x4d_fpn_1x.yml) |
| ResNet50-FPN | Mask | c3-c5 | 1 | 1x | 14.53 | 41.9 | 37.3 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_dcn_r50_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/mask_rcnn_dcn_r50_fpn_1x.yml) | | ResNet50-FPN | Mask | c3-c5 | 1 | 1x | 14.53 | 41.9 | 37.3 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_dcn_r50_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/dcn/mask_rcnn_dcn_r50_fpn_1x.yml) |
| ResNet50-vd-FPN | Mask | c3-c5 | 1 | 2x | 14.832 | 42.9 | 38.0 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_dcn_r50_vd_fpn_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/mask_rcnn_dcn_r50_vd_fpn_2x.yml) | | ResNet50-vd-FPN | Mask | c3-c5 | 1 | 2x | 14.832 | 42.9 | 38.0 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_dcn_r50_vd_fpn_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/dcn/mask_rcnn_dcn_r50_vd_fpn_2x.yml) |
| ResNet101-vd-FPN | Mask | c3-c5 | 1 | 1x | 11.546 | 44.6 | 39.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_dcn_r101_vd_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/mask_rcnn_dcn_r101_vd_fpn_1x.yml) | | ResNet101-vd-FPN | Mask | c3-c5 | 1 | 1x | 11.546 | 44.6 | 39.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_dcn_r101_vd_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/dcn/mask_rcnn_dcn_r101_vd_fpn_1x.yml) |
| ResNeXt101-vd-FPN | Mask | c3-c5 | 1 | 1x | 6.45 | 46.2 | 40.4 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_dcn_x101_vd_64x4d_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/mask_rcnn_dcn_x101_vd_64x4d_fpn_1x.yml) | | ResNeXt101-vd-FPN | Mask | c3-c5 | 1 | 1x | 6.45 | 46.2 | 40.4 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_dcn_x101_vd_64x4d_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/dcn/mask_rcnn_dcn_x101_vd_64x4d_fpn_1x.yml) |
| ResNet50-FPN | Cascade Faster | c3-c5 | 2 | 1x | - | 44.2 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_r50_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/cascade_rcnn_dcn_r50_fpn_1x.yml) | | ResNet50-FPN | Cascade Faster | c3-c5 | 2 | 1x | - | 44.2 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_r50_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/dcn/cascade_rcnn_dcn_r50_fpn_1x.yml) |
| ResNet101-vd-FPN | Cascade Faster | c3-c5 | 2 | 1x | - | 46.4 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_r101_vd_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/cascade_rcnn_dcn_r101_vd_fpn_1x.yml) | | ResNet101-vd-FPN | Cascade Faster | c3-c5 | 2 | 1x | - | 46.4 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_r101_vd_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/dcn/cascade_rcnn_dcn_r101_vd_fpn_1x.yml) |
| ResNeXt101-vd-FPN | Cascade Faster | c3-c5 | 2 | 1x | - | 47.3 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_x101_vd_64x4d_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/cascade_rcnn_dcn_x101_vd_64x4d_fpn_1x.yml) | | ResNeXt101-vd-FPN | Cascade Faster | c3-c5 | 2 | 1x | - | 47.3 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_x101_vd_64x4d_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/dcn/cascade_rcnn_dcn_x101_vd_64x4d_fpn_1x.yml) |
| SENet154-vd-FPN | Cascade Mask | c3-c5 | 1 | 1.44x | - | 51.9 | 43.9 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_mask_rcnn_dcnv2_se154_vd_fpn_gn_s1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/cascade_mask_rcnn_dcnv2_se154_vd_fpn_gn_s1x.yml) | | SENet154-vd-FPN | Cascade Mask | c3-c5 | 1 | 1.44x | - | 51.9 | 43.9 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_mask_rcnn_dcnv2_se154_vd_fpn_gn_s1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/dcn/cascade_mask_rcnn_dcnv2_se154_vd_fpn_gn_s1x.yml) |
| ResNet200-vd-FPN-Nonlocal | CascadeClsAware Faster | c3-c5 | 1 | 2.5x | 3.103 | 51.7%(softnms) | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.yml) | | ResNet200-vd-FPN-Nonlocal | CascadeClsAware Faster | c3-c5 | 1 | 2.5x | 3.103 | 51.7%(softnms) | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/dcn/cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.yml) |
| CBResNet200-vd-FPN-Nonlocal | Cascade Faster | c3-c5 | 1 | 2.5x | 1.68 | 53.3%(softnms) | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_cbr200_vd_fpn_dcnv2_nonlocal_softnms.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/cascade_rcnn_cbr200_vd_fpn_dcnv2_nonlocal_softnms.yml) | | CBResNet200-vd-FPN-Nonlocal | Cascade Faster | c3-c5 | 1 | 2.5x | 1.68 | 53.3%(softnms) | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_cbr200_vd_fpn_dcnv2_nonlocal_softnms.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/dcn/cascade_rcnn_cbr200_vd_fpn_dcnv2_nonlocal_softnms.yml) |
**注意事项:** **注意事项:**
- Deformable卷积网络v2(dcn_v2)参考自论文[Deformable ConvNets v2](https://arxiv.org/abs/1811.11168). - Deformable卷积网络v2(dcn_v2)参考自论文[Deformable ConvNets v2](https://arxiv.org/abs/1811.11168).
- `c3-c5`意思是在resnet模块的3到5阶段增加`dcn`. - `c3-c5`意思是在resnet模块的3到5阶段增加`dcn`.
- 详细的配置文件在[configs/dcn](https://github.com/PaddlePaddle/PaddleDetection/blob/master/configs/dcn) - 详细的配置文件在[configs/dcn](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/configs/dcn)
### HRNet ### HRNet
* 详情见[HRNet模型库](https://github.com/PaddlePaddle/PaddleDetection/blob/master/configs/hrnet/)。 * 详情见[HRNet模型库](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/configs/hrnet/)。
### Res2Net ### Res2Net
* 详情见[Res2Net模型库](https://github.com/PaddlePaddle/PaddleDetection/blob/master/configs/res2net/)。 * 详情见[Res2Net模型库](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/configs/res2net/)。
### IOU loss ### IOU loss
* 目前模型库中包括GIOU loss和DIOU loss，详情见[IOU loss模型库](https://github.com/PaddlePaddle/PaddleDetection/blob/master//configs/iou_loss/). * 目前模型库中包括GIOU loss和DIOU loss，详情见[IOU loss模型库](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static//configs/iou_loss/).
### GCNet ### GCNet
* 详情见[GCNet模型库](https://github.com/PaddlePaddle/PaddleDetection/blob/master/configs/gcnet/). * 详情见[GCNet模型库](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/configs/gcnet/).
### Libra R-CNN ### Libra R-CNN
* 详情见[Libra R-CNN模型库](https://github.com/PaddlePaddle/PaddleDetection/blob/master/configs/libra_rcnn/). * 详情见[Libra R-CNN模型库](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/configs/libra_rcnn/).
### Auto Augmentation ### Auto Augmentation
* 详情见[Auto Augmentation模型库](https://github.com/PaddlePaddle/PaddleDetection/blob/master/configs/autoaugment/). * 详情见[Auto Augmentation模型库](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/configs/autoaugment/).
### Group Normalization ### Group Normalization
| 骨架网络 | 网络类型 | 每张GPU图片个数 | 学习率策略 | Box AP | Mask AP | 下载 | 配置文件 | | 骨架网络 | 网络类型 | 每张GPU图片个数 | 学习率策略 | Box AP | Mask AP | 下载 | 配置文件 |
| :------------------- | :------------- |:--------: | :-----: | :----: | :-----: | :----------------------------------------------------------: | :----: | | :------------------- | :------------- |:--------: | :-----: | :----: | :-----: | :----------------------------------------------------------: | :----: |
| ResNet50-FPN | Faster | 2 | 2x | 39.7 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_fpn_gn_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/gn/faster_rcnn_r50_fpn_gn_2x.yml) | | ResNet50-FPN | Faster | 2 | 2x | 39.7 | - | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_fpn_gn_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/gn/faster_rcnn_r50_fpn_gn_2x.yml) |
| ResNet50-FPN | Mask | 1 | 2x | 40.1 | 35.8 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_fpn_gn_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/gn/mask_rcnn_r50_fpn_gn_2x.yml) | | ResNet50-FPN | Mask | 1 | 2x | 40.1 | 35.8 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mask_rcnn_r50_fpn_gn_2x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/gn/mask_rcnn_r50_fpn_gn_2x.yml) |
**注意事项:** **注意事项:**
- Group Normalization参考论文[Group Normalization](https://arxiv.org/abs/1803.08494). - Group Normalization参考论文[Group Normalization](https://arxiv.org/abs/1803.08494).
- 详细的配置文件在[configs/gn](https://github.com/PaddlePaddle/PaddleDetection/blob/master/configs/gn) - 详细的配置文件在[configs/gn](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/configs/gn)
### YOLO v3 ### YOLO v3
...@@ -130,35 +130,35 @@ Paddle提供基于ImageNet的骨架网络预训练模型。所有预训练模型 ...@@ -130,35 +130,35 @@ Paddle提供基于ImageNet的骨架网络预训练模型。所有预训练模型
| DarkNet53 (paper) | ImageNet | 608 | 否 | 8 | 270e | - | 33.0 | - | - | | DarkNet53 (paper) | ImageNet | 608 | 否 | 8 | 270e | - | 33.0 | - | - |
| DarkNet53 (paper) | ImageNet | 416 | 否 | 8 | 270e | - | 31.0 | - | - | | DarkNet53 (paper) | ImageNet | 416 | 否 | 8 | 270e | - | 31.0 | - | - |
| DarkNet53 (paper) | ImageNet | 320 | 否 | 8 | 270e | - | 28.2 | - | - | | DarkNet53 (paper) | ImageNet | 320 | 否 | 8 | 270e | - | 28.2 | - | - |
| DarkNet53 | ImageNet | 608 | 否 | 8 | 270e | 45.571 | 38.9 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_darknet.yml) | | DarkNet53 | ImageNet | 608 | 否 | 8 | 270e | 45.571 | 38.9 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_darknet.yml) |
| DarkNet53 | ImageNet | 416 | 否 | 8 | 270e | - | 37.5 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_darknet.yml) | | DarkNet53 | ImageNet | 416 | 否 | 8 | 270e | - | 37.5 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_darknet.yml) |
| DarkNet53 | ImageNet | 320 | 否 | 8 | 270e | - | 34.8 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_darknet.yml) | | DarkNet53 | ImageNet | 320 | 否 | 8 | 270e | - | 34.8 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_darknet.yml) |
| MobileNet-V1 | ImageNet | 608 | 否 | 8 | 270e | 78.302 | 29.3 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_mobilenet_v1.yml) | | MobileNet-V1 | ImageNet | 608 | 否 | 8 | 270e | 78.302 | 29.3 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_mobilenet_v1.yml) |
| MobileNet-V1 | ImageNet | 416 | 否 | 8 | 270e | - | 29.3 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_mobilenet_v1.yml) | | MobileNet-V1 | ImageNet | 416 | 否 | 8 | 270e | - | 29.3 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_mobilenet_v1.yml) |
| MobileNet-V1 | ImageNet | 320 | 否 | 8 | 270e | - | 27.1 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_mobilenet_v1.yml) | | MobileNet-V1 | ImageNet | 320 | 否 | 8 | 270e | - | 27.1 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_mobilenet_v1.yml) |
| MobileNet-V3 | ImageNet | 608 | 否 | 8 | 270e | - | 31.6 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v3.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_mobilenet_v3.yml) | | MobileNet-V3 | ImageNet | 608 | 否 | 8 | 270e | - | 31.6 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v3.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_mobilenet_v3.yml) |
| MobileNet-V3 | ImageNet | 416 | 否 | 8 | 270e | - | 29.9 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v3.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_mobilenet_v3.yml) | | MobileNet-V3 | ImageNet | 416 | 否 | 8 | 270e | - | 29.9 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v3.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_mobilenet_v3.yml) |
| MobileNet-V3 | ImageNet | 320 | 否 | 8 | 270e | - | 27.1 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v3.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_mobilenet_v3.yml) | | MobileNet-V3 | ImageNet | 320 | 否 | 8 | 270e | - | 27.1 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v3.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_mobilenet_v3.yml) |
| ResNet34 | ImageNet | 608 | 否 | 8 | 270e | 63.356 | 36.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_r34.yml) | | ResNet34 | ImageNet | 608 | 否 | 8 | 270e | 63.356 | 36.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_r34.yml) |
| ResNet34 | ImageNet | 416 | 否 | 8 | 270e | - | 34.3 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_r34.yml) | | ResNet34 | ImageNet | 416 | 否 | 8 | 270e | - | 34.3 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_r34.yml) |
| ResNet34 | ImageNet | 320 | 否 | 8 | 270e | - | 31.4 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_r34.yml) | | ResNet34 | ImageNet | 320 | 否 | 8 | 270e | - | 31.4 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_r34.yml) |
| ResNet50_vd | ImageNet | 608 | 是 | 8 | 270e | - | 39.1 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/yolov3_r50vd_dcn.yml) | | ResNet50_vd | ImageNet | 608 | 是 | 8 | 270e | - | 39.1 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/dcn/yolov3_r50vd_dcn.yml) |
| ResNet50_vd | Object365 | 608 | 是 | 8 | 270e | - | 41.4 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn_obj365_pretrained_coco.tar) |[配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/yolov3_r50vd_dcn_obj365_pretrained_coco.yml) | | ResNet50_vd | Object365 | 608 | 是 | 8 | 270e | - | 41.4 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn_obj365_pretrained_coco.tar) |[配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/dcn/yolov3_r50vd_dcn_obj365_pretrained_coco.yml) |
### YOLO v3 基于Pasacl VOC数据集 ### YOLO v3 基于Pasacl VOC数据集
| 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 | | 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 |
| :----------- | :--: | :-----: | :-----: |:------------: |:----: | :-------: | :----: | | :----------- | :--: | :-----: | :-----: |:------------: |:----: | :-------: | :----: |
| DarkNet53 | 608 | 8 | 270e | 54.977 | 83.5 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet_voc.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_darknet_voc.yml) | | DarkNet53 | 608 | 8 | 270e | 54.977 | 83.5 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet_voc.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_darknet_voc.yml) |
| DarkNet53 | 416 | 8 | 270e | - | 83.6 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet_voc.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_darknet_voc.yml) | | DarkNet53 | 416 | 8 | 270e | - | 83.6 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet_voc.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_darknet_voc.yml) |
| DarkNet53 | 320 | 8 | 270e | - | 82.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet_voc.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_darknet_voc.yml) | | DarkNet53 | 320 | 8 | 270e | - | 82.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet_voc.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_darknet_voc.yml) |
| DarkNet53 Diou-Loss | 608 | 8 | 270e | - | 83.5 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet_voc_diouloss.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_darknet_voc_diouloss.yml) | | DarkNet53 Diou-Loss | 608 | 8 | 270e | - | 83.5 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet_voc_diouloss.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_darknet_voc_diouloss.yml) |
| MobileNet-V1 | 608 | 8 | 270e | 104.291 | 76.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1_voc.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_mobilenet_v1_voc.yml) | | MobileNet-V1 | 608 | 8 | 270e | 104.291 | 76.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1_voc.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_mobilenet_v1_voc.yml) |
| MobileNet-V1 | 416 | 8 | 270e | - | 76.7 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1_voc.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_mobilenet_v1_voc.yml) | | MobileNet-V1 | 416 | 8 | 270e | - | 76.7 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1_voc.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_mobilenet_v1_voc.yml) |
| MobileNet-V1 | 320 | 8 | 270e | - | 75.3 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1_voc.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_mobilenet_v1_voc.yml) | | MobileNet-V1 | 320 | 8 | 270e | - | 75.3 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_mobilenet_v1_voc.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_mobilenet_v1_voc.yml) |
| ResNet34 | 608 | 8 | 270e | 82.247 | 82.6 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34_voc.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_r34_voc.yml) | | ResNet34 | 608 | 8 | 270e | 82.247 | 82.6 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34_voc.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_r34_voc.yml) |
| ResNet34 | 416 | 8 | 270e | - | 81.9 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34_voc.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_r34_voc.yml) | | ResNet34 | 416 | 8 | 270e | - | 81.9 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34_voc.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_r34_voc.yml) |
| ResNet34 | 320 | 8 | 270e | - | 80.1 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34_voc.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_r34_voc.yml) | | ResNet34 | 320 | 8 | 270e | - | 80.1 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r34_voc.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_r34_voc.yml) |
**注意事项:** **注意事项:**
...@@ -171,9 +171,9 @@ Paddle提供基于ImageNet的骨架网络预训练模型。所有预训练模型 ...@@ -171,9 +171,9 @@ Paddle提供基于ImageNet的骨架网络预训练模型。所有预训练模型
| 骨架网络 | 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 | | 骨架网络 | 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 |
| :---------------: | :-----: | :-----: | :----: | :----: | :-------: | :----: | | :---------------: | :-----: | :-----: | :----: | :----: | :-------: | :----: |
| ResNet50-FPN | 2 | 1x | - | 36.0 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/retinanet_r50_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/retinanet_r50_fpn_1x.yml) | | ResNet50-FPN | 2 | 1x | - | 36.0 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/retinanet_r50_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/retinanet_r50_fpn_1x.yml) |
| ResNet101-FPN | 2 | 1x | - | 37.3 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/retinanet_r101_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/retinanet_r101_fpn_1x.yml) | | ResNet101-FPN | 2 | 1x | - | 37.3 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/retinanet_r101_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/retinanet_r101_fpn_1x.yml) |
| ResNeXt101-vd-FPN | 1 | 1x | - | 40.5 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/retinanet_x101_vd_64x4d_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/retinanet_x101_vd_64x4d_fpn_1x.yml) | | ResNeXt101-vd-FPN | 1 | 1x | - | 40.5 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/retinanet_x101_vd_64x4d_fpn_1x.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/retinanet_x101_vd_64x4d_fpn_1x.yml) |
**注意事项:** RetinaNet系列模型中，在总batch size为16下情况下，初始学习率改为0.01。 **注意事项:** RetinaNet系列模型中，在总batch size为16下情况下，初始学习率改为0.01。
...@@ -181,7 +181,7 @@ Paddle提供基于ImageNet的骨架网络预训练模型。所有预训练模型 ...@@ -181,7 +181,7 @@ Paddle提供基于ImageNet的骨架网络预训练模型。所有预训练模型
| 尺度 | 每张GPU图片个数 | 学习率策略 | Box AP | 下载 | 配置文件 | | 尺度 | 每张GPU图片个数 | 学习率策略 | Box AP | 下载 | 配置文件 |
| :---------------: | :-----: | :-----: | :----: | :-------: | :----: | | :---------------: | :-----: | :-----: | :----: | :-------: | :----: |
| EfficientDet-D0 | 16 | 300 epochs | 33.8 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/efficientdet_d0.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/efficientdet_d0.yml) | | EfficientDet-D0 | 16 | 300 epochs | 33.8 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/efficientdet_d0.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/efficientdet_d0.yml) |
**注意事项:** 在总batch size为128(8x16)时，基础学习率改为0.16。 **注意事项:** 在总batch size为128(8x16)时，基础学习率改为0.16。
...@@ -189,12 +189,12 @@ Paddle提供基于ImageNet的骨架网络预训练模型。所有预训练模型 ...@@ -189,12 +189,12 @@ Paddle提供基于ImageNet的骨架网络预训练模型。所有预训练模型
| 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 | | 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 | 300 | 64 | Cosine decay(40w) | - | 23.6 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ssdlite_mobilenet_v1.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ssd/ssdlite_mobilenet_v1.yml) | | MobileNet_v1 | 300 | 64 | Cosine decay(40w) | - | 23.6 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ssdlite_mobilenet_v1.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ssd/ssdlite_mobilenet_v1.yml) |
| MobileNet_v3 small | 320 | 64 | Cosine decay(40w) | - | 16.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/ssdlite_mobilenet_v3_small.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ssd/ssdlite_mobilenet_v3_small.yml) | | MobileNet_v3 small | 320 | 64 | Cosine decay(40w) | - | 16.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/ssdlite_mobilenet_v3_small.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ssd/ssdlite_mobilenet_v3_small.yml) |
| MobileNet_v3 large | 320 | 64 | Cosine decay(40w) | - | 23.3 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/ssdlite_mobilenet_v3_large.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ssd/ssdlite_mobilenet_v3_large.yml) | | MobileNet_v3 large | 320 | 64 | Cosine decay(40w) | - | 23.3 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/ssdlite_mobilenet_v3_large.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ssd/ssdlite_mobilenet_v3_large.yml) |
| MobileNet_v3 small w/ FPN | 320 | 64 | Cosine decay(40w) | - | 18.9 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/ssdlite_mobilenet_v3_small_fpn.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ssd/ssdlite_mobilenet_v3_small_fpn.yml) | | MobileNet_v3 small w/ FPN | 320 | 64 | Cosine decay(40w) | - | 18.9 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/ssdlite_mobilenet_v3_small_fpn.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ssd/ssdlite_mobilenet_v3_small_fpn.yml) |
| MobileNet_v3 large w/ FPN | 320 | 64 | Cosine decay(40w) | - | 24.3 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/ssdlite_mobilenet_v3_large_fpn.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ssd/ssdlite_mobilenet_v3_large_fpn.yml) | | MobileNet_v3 large w/ FPN | 320 | 64 | Cosine decay(40w) | - | 24.3 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/ssdlite_mobilenet_v3_large_fpn.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ssd/ssdlite_mobilenet_v3_large_fpn.yml) |
| GhostNet | 320 | 64 | Cosine decay(40w) | - | 23.3 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/ssdlite_ghostnet.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ssd/ssdlite_ghostnet.yml) | | GhostNet | 320 | 64 | Cosine decay(40w) | - | 23.3 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/ssdlite_ghostnet.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ssd/ssdlite_ghostnet.yml) |
**注意事项:** SSDLite模型使用学习率余弦衰减策略在8卡GPU下总batch size为512。 **注意事项:** SSDLite模型使用学习率余弦衰减策略在8卡GPU下总batch size为512。
...@@ -202,8 +202,8 @@ Paddle提供基于ImageNet的骨架网络预训练模型。所有预训练模型 ...@@ -202,8 +202,8 @@ Paddle提供基于ImageNet的骨架网络预训练模型。所有预训练模型
| 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 | | 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 |
| :----------: | :--: | :-----: | :-----: |:------------: |:----: | :-------: | :----: | | :----------: | :--: | :-----: | :-----: |:------------: |:----: | :-------: | :----: |
| VGG16 | 300 | 8 | 40万 | 81.613 | 25.1 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ssd_vgg16_300.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ssd/ssd_vgg16_300.yml) | | VGG16 | 300 | 8 | 40万 | 81.613 | 25.1 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ssd_vgg16_300.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ssd/ssd_vgg16_300.yml) |
| VGG16 | 512 | 8 | 40万 | 46.007 | 29.1 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ssd_vgg16_512.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ssd/ssd_vgg16_512.yml) | | VGG16 | 512 | 8 | 40万 | 46.007 | 29.1 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ssd_vgg16_512.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ssd/ssd_vgg16_512.yml) |
**注意事项:** VGG-SSD在总batch size为32下训练40万轮。 **注意事项:** VGG-SSD在总batch size为32下训练40万轮。
...@@ -211,9 +211,9 @@ Paddle提供基于ImageNet的骨架网络预训练模型。所有预训练模型 ...@@ -211,9 +211,9 @@ Paddle提供基于ImageNet的骨架网络预训练模型。所有预训练模型
| 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 | | 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 | 300 | 32 | 120e | 159.543 | 73.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ssd_mobilenet_v1_voc.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ssd/ssd_mobilenet_v1_voc.yml) | | MobileNet v1 | 300 | 32 | 120e | 159.543 | 73.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ssd_mobilenet_v1_voc.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ssd/ssd_mobilenet_v1_voc.yml) |
| VGG16 | 300 | 8 | 240e | 117.279 | 77.5 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ssd_vgg16_300_voc.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ssd/ssd_vgg16_300_voc.yml) | | VGG16 | 300 | 8 | 240e | 117.279 | 77.5 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ssd_vgg16_300_voc.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ssd/ssd_vgg16_300_voc.yml) |
| VGG16 | 512 | 8 | 240e | 65.975 | 80.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ssd_vgg16_512_voc.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/ssd/ssd_vgg16_512_voc.yml) | | VGG16 | 512 | 8 | 240e | 65.975 | 80.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/ssd_vgg16_512_voc.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/ssd/ssd_vgg16_512_voc.yml) |
**注意事项:** MobileNet-SSD在2卡，总batch size为64下训练120周期。VGG-SSD在总batch size为32下训练240周期。数据增强包括：随机颜色失真，随机剪裁，随机扩张，随机翻转。 **注意事项:** MobileNet-SSD在2卡，总batch size为64下训练120周期。VGG-SSD在总batch size为32下训练240周期。数据增强包括：随机颜色失真，随机剪裁，随机扩张，随机翻转。
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static/docs/advanced_tutorials/MODEL_TECHNICAL.md
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...@@ -34,7 +34,7 @@ PaddleDetection的网络模型模块所有代码逻辑在`ppdet/modeling/`中， ...@@ -34,7 +34,7 @@ PaddleDetection的网络模型模块所有代码逻辑在`ppdet/modeling/`中，
![](../images/models_figure.png) ![](../images/models_figure.png)
## 新增模型 ## 新增模型
我们以单阶段检测器YOLOv3为例，结合[yolov3_darknet.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/master/configs/yolov3_darknet.yml)配置文件，对建立模型过程进行详细描述， 我们以单阶段检测器YOLOv3为例，结合[yolov3_darknet.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/configs/yolov3_darknet.yml)配置文件，对建立模型过程进行详细描述，
按照此思路您可以快速搭建新的模型。 按照此思路您可以快速搭建新的模型。
搭建新模型的一般步骤是：Backbone编写、检测组件编写与模型组网这三个步骤，下面为您详细介绍： 搭建新模型的一般步骤是：Backbone编写、检测组件编写与模型组网这三个步骤，下面为您详细介绍：
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...@@ -392,7 +392,7 @@ EvalReader： ...@@ -392,7 +392,7 @@ EvalReader：
`DataLoader`的API详见[fluid.io.DataLoader](https://www.paddlepaddle.org.cn/documentation/docs/zh/develop/api_cn/io_cn/DataLoader_cn.html#dataloader)。 `DataLoader`的API详见[fluid.io.DataLoader](https://www.paddlepaddle.org.cn/documentation/docs/zh/develop/api_cn/io_cn/DataLoader_cn.html#dataloader)。
具体步骤如下： 具体步骤如下：
- 在[train.py](https://github.com/PaddlePaddle/PaddleDetection/blob/master/tools/train.py)、[eval.py](https://github.com/PaddlePaddle/PaddleDetection/blob/master/tools/eval.py)和[infer.py](https://github.com/PaddlePaddle/PaddleDetection/blob/master/tools/infer.py)里创建训练时的Reader： - 在[train.py](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/tools/train.py)、[eval.py](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/tools/eval.py)和[infer.py](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/tools/infer.py)里创建训练时的Reader：
```python ```python
# 创建DataLoader对象 # 创建DataLoader对象
inputs_def = cfg['TestReader']['inputs_def'] inputs_def = cfg['TestReader']['inputs_def']
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...@@ -11,7 +11,7 @@ In transfer learning, if different dataset and the number of classes is used, th ...@@ -11,7 +11,7 @@ In transfer learning, if different dataset and the number of classes is used, th
Transfer learning needs custom dataset and annotation in COCO-format and VOC-format is supported now. The script converts the annotation from voc, labelme or cityscape to COCO is provided in ```tools/x2coco.py```. More details please refer to [READER](READER.md). After data preparation, update the data parameters in configuration file. Transfer learning needs custom dataset and annotation in COCO-format and VOC-format is supported now. The script converts the annotation from voc, labelme or cityscape to COCO is provided in ```tools/x2coco.py```. More details please refer to [READER](READER.md). After data preparation, update the data parameters in configuration file.
1. COCO-format dataset, take [yolov3\_darknet.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/master/configs/yolov3_darknet.yml#L66) for example, modify the COCODataSet in yolov3\_reader: 1. COCO-format dataset, take [yolov3\_darknet.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/configs/yolov3_darknet.yml#L66) for example, modify the COCODataSet in yolov3\_reader:
```yml ```yml
dataset: dataset:
...@@ -22,7 +22,7 @@ Transfer learning needs custom dataset and annotation in COCO-format and VOC-for ...@@ -22,7 +22,7 @@ Transfer learning needs custom dataset and annotation in COCO-format and VOC-for
with_background: false with_background: false
``` ```
2. VOC-format dataset, take [yolov3\_darknet\_voc.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/master/configs/yolov3_darknet_voc.yml#L67) for example, modify the VOCDataSet in the configuration: 2. VOC-format dataset, take [yolov3\_darknet\_voc.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/configs/yolov3_darknet_voc.yml#L67) for example, modify the VOCDataSet in the configuration:
```yml ```yml
dataset: dataset:
...@@ -52,7 +52,7 @@ python -u tools/train.py -c configs/faster_rcnn_r50_1x.yml \ ...@@ -52,7 +52,7 @@ python -u tools/train.py -c configs/faster_rcnn_r50_1x.yml \
The parameters which need to ignore can be specified explicitly as well and arbitrary parameter names can be added to `finetune_exclude_pretrained_params`. For this purpose, several methods can be used as follwed: The parameters which need to ignore can be specified explicitly as well and arbitrary parameter names can be added to `finetune_exclude_pretrained_params`. For this purpose, several methods can be used as follwed:
- Set `finetune_exclude_pretrained_params` in YAML configuration files. Please refer to [configure file](https://github.com/PaddlePaddle/PaddleDetection/blob/master/configs/yolov3_mobilenet_v1_fruit.yml#L15) - Set `finetune_exclude_pretrained_params` in YAML configuration files. Please refer to [configure file](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/configs/yolov3_mobilenet_v1_fruit.yml#L15)
- Set `finetune_exclude_pretrained_params` in command line. For example: - Set `finetune_exclude_pretrained_params` in command line. For example:
```python ```python
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...@@ -9,7 +9,7 @@ ...@@ -9,7 +9,7 @@
迁移学习需要使用自己的数据集，目前已支持COCO和VOC的数据标注格式，在```tools/x2coco.py```中给出了voc、labelme和cityscape标注格式转换为COCO格式的脚本，具体使用方式可以参考[自定义数据源](READER.md)。数据准备完成后，在配置文件中配置数据路径，对应修改reader中的路径参数即可。 迁移学习需要使用自己的数据集，目前已支持COCO和VOC的数据标注格式，在```tools/x2coco.py```中给出了voc、labelme和cityscape标注格式转换为COCO格式的脚本，具体使用方式可以参考[自定义数据源](READER.md)。数据准备完成后，在配置文件中配置数据路径，对应修改reader中的路径参数即可。
1. COCO数据集需要修改COCODataSet中的参数，以[yolov3\_darknet.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/master/configs/yolov3_darknet.yml#L66)为例，修改yolov3\_reader中的配置： 1. COCO数据集需要修改COCODataSet中的参数，以[yolov3\_darknet.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/configs/yolov3_darknet.yml#L66)为例，修改yolov3\_reader中的配置：
```yml ```yml
dataset: dataset:
...@@ -20,7 +20,7 @@ ...@@ -20,7 +20,7 @@
with_background: false with_background: false
``` ```
2. VOC数据集需要修改VOCDataSet中的参数，以[yolov3\_darknet\_voc.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/master/configs/yolov3_darknet_voc.yml#L67)为例： 2. VOC数据集需要修改VOCDataSet中的参数，以[yolov3\_darknet\_voc.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/configs/yolov3_darknet_voc.yml#L67)为例：
```yml ```yml
dataset: dataset:
...@@ -56,7 +56,7 @@ python -u tools/train.py -c configs/faster_rcnn_r50_1x.yml \ ...@@ -56,7 +56,7 @@ python -u tools/train.py -c configs/faster_rcnn_r50_1x.yml \
可以显示的指定训练过程中忽略参数的名字，任何参数名均可加入`finetune_exclude_pretrained_params`中，为实现这一目的，可通过如下方式实现： 可以显示的指定训练过程中忽略参数的名字，任何参数名均可加入`finetune_exclude_pretrained_params`中，为实现这一目的，可通过如下方式实现：
1. 在 YMAL 配置文件中通过设置`finetune_exclude_pretrained_params`字段。可参考[配置文件](https://github.com/PaddlePaddle/PaddleDetection/blob/master/configs/yolov3_mobilenet_v1_fruit.yml#L15) 1. 在 YMAL 配置文件中通过设置`finetune_exclude_pretrained_params`字段。可参考[配置文件](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/configs/yolov3_mobilenet_v1_fruit.yml#L15)
2. 在 train.py的启动参数中设置`finetune_exclude_pretrained_params`。例如： 2. 在 train.py的启动参数中设置`finetune_exclude_pretrained_params`。例如：
```python ```python
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# Windows平台使用 Visual Studio 2015 编译指南 # Windows平台使用 Visual Studio 2015 编译指南
本文档步骤，我们同时在`Visual Studio 2015` 和 `Visual Studio 2019 Community` 两个版本进行了测试，我们推荐使用[`Visual Studio 2019`直接编译`CMake`项目](https://github.com/PaddlePaddle/PaddleDetection/blob/master/deploy/cpp/docs/windows_vs2019_build.md)。 本文档步骤，我们同时在`Visual Studio 2015` 和 `Visual Studio 2019 Community` 两个版本进行了测试，我们推荐使用[`Visual Studio 2019`直接编译`CMake`项目](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/deploy/cpp/docs/windows_vs2019_build.md)。
## 前置条件 ## 前置条件
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def url_resolver(url): def url_resolver(url):
if ".html" not in url: if ".html" not in url:
url = url.replace("../", "") url = url.replace("../", "")
return "https://github.com/PaddlePaddle/PaddleDetection/tree/master" + url return "https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static" + url
else: else:
if DEPLOY: if DEPLOY:
return "http://paddledetection.readthedocs.io/" + url return "http://paddledetection.readthedocs.io/" + url
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...@@ -5,8 +5,8 @@ We provide some models implemented by PaddlePaddle to detect objects in specific ...@@ -5,8 +5,8 @@ We provide some models implemented by PaddlePaddle to detect objects in specific
| Task | Algorithm | Box AP | Download | Configs | | Task | Algorithm | Box AP | Download | Configs |
|:---------------------|:---------:|:------:| :-------------------------------------------------------------------------------------: |:------:| |:---------------------|:---------:|:------:| :-------------------------------------------------------------------------------------: |:------:|
| Vehicle Detection | YOLOv3 | 54.5 | [model](https://paddlemodels.bj.bcebos.com/object_detection/vehicle_yolov3_darknet.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/contrib/VehicleDetection/vehicle_yolov3_darknet.yml) | | Vehicle Detection | YOLOv3 | 54.5 | [model](https://paddlemodels.bj.bcebos.com/object_detection/vehicle_yolov3_darknet.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/contrib/VehicleDetection/vehicle_yolov3_darknet.yml) |
| Pedestrian Detection | YOLOv3 | 51.8 | [model](https://paddlemodels.bj.bcebos.com/object_detection/pedestrian_yolov3_darknet.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/contrib/PedestrianDetection/pedestrian_yolov3_darknet.yml) | | Pedestrian Detection | YOLOv3 | 51.8 | [model](https://paddlemodels.bj.bcebos.com/object_detection/pedestrian_yolov3_darknet.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/contrib/PedestrianDetection/pedestrian_yolov3_darknet.yml) |
## Vehicle Detection ## Vehicle Detection
...@@ -18,7 +18,7 @@ The network for detecting vehicles is YOLOv3, the backbone of which is Dacknet53 ...@@ -18,7 +18,7 @@ The network for detecting vehicles is YOLOv3, the backbone of which is Dacknet53
### 2. Configuration for training ### 2. Configuration for training
PaddleDetection provides users with a configuration file [yolov3_darknet.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/master/configs/yolov3_darknet.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_darknet.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/configs/yolov3_darknet.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:
* max_iters: 120000 * max_iters: 120000
* num_classes: 6 * num_classes: 6
...@@ -67,7 +67,7 @@ The network for detecting vehicles is YOLOv3, the backbone of which is Dacknet53 ...@@ -67,7 +67,7 @@ The network for detecting vehicles is YOLOv3, the backbone of which is Dacknet53
### 2. Configuration for training ### 2. Configuration for training
PaddleDetection provides users with a configuration file [yolov3_darknet.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/master/configs/yolov3_darknet.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_darknet.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/configs/yolov3_darknet.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:
* max_iters: 200000 * max_iters: 200000
* num_classes: 1 * num_classes: 1
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...@@ -5,8 +5,8 @@ ...@@ -5,8 +5,8 @@
| 任务 | 算法 | 精度(Box AP) | 下载 | 配置文件 | | 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://paddlemodels.bj.bcebos.com/object_detection/vehicle_yolov3_darknet.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/contrib/VehicleDetection/vehicle_yolov3_darknet.yml) | | 车辆检测 | YOLOv3 | 54.5 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/vehicle_yolov3_darknet.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/contrib/VehicleDetection/vehicle_yolov3_darknet.yml) |
| 行人检测 | YOLOv3 | 51.8 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/pedestrian_yolov3_darknet.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/contrib/PedestrianDetection/pedestrian_yolov3_darknet.yml) | | 行人检测 | YOLOv3 | 51.8 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/pedestrian_yolov3_darknet.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/contrib/PedestrianDetection/pedestrian_yolov3_darknet.yml) |
## 车辆检测（Vehicle Detection） ## 车辆检测（Vehicle Detection）
...@@ -19,7 +19,7 @@ Backbone为Dacknet53的YOLOv3。 ...@@ -19,7 +19,7 @@ Backbone为Dacknet53的YOLOv3。
### 2. 训练参数配置 ### 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_darnet.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/master/configs/yolov3_darknet.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_darnet.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/configs/yolov3_darknet.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：
* max_iters: 120000 * max_iters: 120000
* num_classes: 6 * num_classes: 6
...@@ -69,7 +69,7 @@ Backbone为Dacknet53的YOLOv3。 ...@@ -69,7 +69,7 @@ Backbone为Dacknet53的YOLOv3。
### 2. 训练参数配置 ### 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_darknet.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/master/configs/yolov3_darknet.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_darknet.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/configs/yolov3_darknet.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：
* max_iters: 200000 * max_iters: 200000
* num_classes: 1 * num_classes: 1
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...@@ -34,16 +34,16 @@ FaceDetection的目标是提供高效、高速的人脸检测解决方案，包 ...@@ -34,16 +34,16 @@ FaceDetection的目标是提供高效、高速的人脸检测解决方案，包
| 网络结构 | 类型 | 输入尺寸 | 图片个数/GPU | 学习率策略 | Easy Set | Medium Set | Hard Set | 下载 | 配置文件 | | 网络结构 | 类型 | 输入尺寸 | 图片个数/GPU | 学习率策略 | Easy Set | Medium Set | Hard Set | 下载 | 配置文件 |
|:------------:|:--------:|:----:|:-------:|:-------:|:---------:|:----------:|:---------:|:--------:|:--------:| |:------------:|:--------:|:----:|:-------:|:-------:|:---------:|:----------:|:---------:|:--------:|:--------:|
| BlazeFace | 原始版本 | 640 | 8 | 32w | **0.915** | **0.892** | **0.797** | [模型](https://paddlemodels.bj.bcebos.com/object_detection/blazeface_original.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/face_detection/blazeface.yml) | | BlazeFace | 原始版本 | 640 | 8 | 32w | **0.915** | **0.892** | **0.797** | [模型](https://paddlemodels.bj.bcebos.com/object_detection/blazeface_original.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/face_detection/blazeface.yml) |
| BlazeFace | Lite版本 | 640 | 8 | 32w | 0.909 | 0.885 | 0.781 | [模型](https://paddlemodels.bj.bcebos.com/object_detection/blazeface_lite.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/face_detection/blazeface.yml) | | BlazeFace | Lite版本 | 640 | 8 | 32w | 0.909 | 0.885 | 0.781 | [模型](https://paddlemodels.bj.bcebos.com/object_detection/blazeface_lite.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/face_detection/blazeface.yml) |
| BlazeFace | NAS版本 | 640 | 8 | 32w | 0.837 | 0.807 | 0.658 | [模型](https://paddlemodels.bj.bcebos.com/object_detection/blazeface_nas.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/face_detection/blazeface_nas.yml) | | BlazeFace | NAS版本 | 640 | 8 | 32w | 0.837 | 0.807 | 0.658 | [模型](https://paddlemodels.bj.bcebos.com/object_detection/blazeface_nas.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/face_detection/blazeface_nas.yml) |
| BlazeFace | NAS_V2版本 | 640 | 8 | 32W | 0.870 | 0.837 | 0.685 | [模型](https://paddlemodels.bj.bcebos.com/object_detection/blazeface_nas2.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/face_detection/blazeface_nas_v2.yml) | | BlazeFace | NAS_V2版本 | 640 | 8 | 32W | 0.870 | 0.837 | 0.685 | [模型](https://paddlemodels.bj.bcebos.com/object_detection/blazeface_nas2.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/face_detection/blazeface_nas_v2.yml) |
| FaceBoxes | 原始版本 | 640 | 8 | 32w | 0.878 | 0.851 | 0.576 | [模型](https://paddlemodels.bj.bcebos.com/object_detection/faceboxes_original.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/face_detection/faceboxes.yml) | | FaceBoxes | 原始版本 | 640 | 8 | 32w | 0.878 | 0.851 | 0.576 | [模型](https://paddlemodels.bj.bcebos.com/object_detection/faceboxes_original.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/face_detection/faceboxes.yml) |
| FaceBoxes | Lite版本 | 640 | 8 | 32w | 0.901 | 0.875 | 0.760 | [模型](https://paddlemodels.bj.bcebos.com/object_detection/faceboxes_lite.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/face_detection/faceboxes_lite.yml) | | FaceBoxes | Lite版本 | 640 | 8 | 32w | 0.901 | 0.875 | 0.760 | [模型](https://paddlemodels.bj.bcebos.com/object_detection/faceboxes_lite.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/face_detection/faceboxes_lite.yml) |
**注意:** **注意:**
- 我们使用`tools/face_eval.py`中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)。 - 我们使用`tools/face_eval.py`中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)。
- BlazeFace-Lite的训练与测试使用 [blazeface.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/master/configs/face_detection/blazeface.yml)配置文件并且设置：`lite_edition: true`。 - BlazeFace-Lite的训练与测试使用 [blazeface.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/configs/face_detection/blazeface.yml)配置文件并且设置：`lite_edition: true`。
#### FDDB数据集上的mAP #### FDDB数据集上的mAP
...@@ -258,7 +258,7 @@ wget https://dataset.bj.bcebos.com/wider_face/wider_face_train_bbx_lmk_gt.txt ...@@ -258,7 +258,7 @@ wget https://dataset.bj.bcebos.com/wider_face/wider_face_train_bbx_lmk_gt.txt
| 网络结构 | 输入尺寸 | 图片个数/GPU | 学习率策略 | Easy Set | Medium Set | Hard Set | 下载 | 配置文件 | | 网络结构 | 输入尺寸 | 图片个数/GPU | 学习率策略 | Easy Set | Medium Set | Hard Set | 下载 | 配置文件 |
|:------------:|:----:|:-------:|:-------:|:---------:|:----------:|:---------:|:--------:|:--------:| |:------------:|:----:|:-------:|:-------:|:---------:|:----------:|:---------:|:--------:|:--------:|
| BlazeFace Keypoint | 640 | 16 | 16w | 0.852 | 0.816 | 0.662 | [模型](https://paddlemodels.bj.bcebos.com/object_detection/blazeface_keypoint.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/face_detection/blazeface_keypoint.yml) | | BlazeFace Keypoint | 640 | 16 | 16w | 0.852 | 0.816 | 0.662 | [模型](https://paddlemodels.bj.bcebos.com/object_detection/blazeface_keypoint.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/face_detection/blazeface_keypoint.yml) |
![](../images/12_Group_Group_12_Group_Group_12_84.jpg) ![](../images/12_Group_Group_12_Group_Group_12_84.jpg)
...@@ -292,7 +292,7 @@ wget https://dataset.bj.bcebos.com/wider_face/wider_face_train_bbx_lmk_gt.txt ...@@ -292,7 +292,7 @@ wget https://dataset.bj.bcebos.com/wider_face/wider_face_train_bbx_lmk_gt.txt
**版本信息:** **版本信息:**
- 原始版本: 参考原始论文进行修改； - 原始版本: 参考原始论文进行修改；
- Lite版本: 使用更少的网络层数和通道数，具体可参考[代码](https://github.com/PaddlePaddle/PaddleDetection/blob/master/ppdet/modeling/architectures/faceboxes.py)。 - Lite版本: 使用更少的网络层数和通道数，具体可参考[代码](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/ppdet/modeling/architectures/faceboxes.py)。
## 如何贡献代码 ## 如何贡献代码
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static/docs/featured_model/FACE_DETECTION_en.md
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...@@ -38,17 +38,17 @@ optimized network structure. ...@@ -38,17 +38,17 @@ optimized network structure.
| Architecture | Type | Size | Img/gpu | Lr schd | Easy Set | Medium Set | Hard Set | Download | Configs | | Architecture | Type | Size | Img/gpu | Lr schd | Easy Set | Medium Set | Hard Set | Download | Configs |
|:------------:|:--------:|:----:|:-------:|:-------:|:---------:|:----------:|:---------:|:--------:|:--------:| |:------------:|:--------:|:----:|:-------:|:-------:|:---------:|:----------:|:---------:|:--------:|:--------:|
| BlazeFace | Original | 640 | 8 | 32w | **0.915** | **0.892** | **0.797** | [model](https://paddlemodels.bj.bcebos.com/object_detection/blazeface_original.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/face_detection/blazeface.yml) | | BlazeFace | Original | 640 | 8 | 32w | **0.915** | **0.892** | **0.797** | [model](https://paddlemodels.bj.bcebos.com/object_detection/blazeface_original.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/face_detection/blazeface.yml) |
| BlazeFace | Lite | 640 | 8 | 32w | 0.909 | 0.885 | 0.781 | [model](https://paddlemodels.bj.bcebos.com/object_detection/blazeface_lite.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/face_detection/blazeface.yml) | | BlazeFace | Lite | 640 | 8 | 32w | 0.909 | 0.885 | 0.781 | [model](https://paddlemodels.bj.bcebos.com/object_detection/blazeface_lite.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/face_detection/blazeface.yml) |
| BlazeFace | NAS | 640 | 8 | 32w | 0.837 | 0.807 | 0.658 | [model](https://paddlemodels.bj.bcebos.com/object_detection/blazeface_nas.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/face_detection/blazeface_nas.yml) | | BlazeFace | NAS | 640 | 8 | 32w | 0.837 | 0.807 | 0.658 | [model](https://paddlemodels.bj.bcebos.com/object_detection/blazeface_nas.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/face_detection/blazeface_nas.yml) |
| BlazeFace | NAS_V2 | 640 | 8 | 32W | 0.870 | 0.837 | 0.685 | [model](https://paddlemodels.bj.bcebos.com/object_detection/blazeface_nas2.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/face_detection/blazeface_nas_v2.yml) | | BlazeFace | NAS_V2 | 640 | 8 | 32W | 0.870 | 0.837 | 0.685 | [model](https://paddlemodels.bj.bcebos.com/object_detection/blazeface_nas2.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/face_detection/blazeface_nas_v2.yml) |
| FaceBoxes | Original | 640 | 8 | 32w | 0.878 | 0.851 | 0.576 | [model](https://paddlemodels.bj.bcebos.com/object_detection/faceboxes_original.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/face_detection/faceboxes.yml) | | FaceBoxes | Original | 640 | 8 | 32w | 0.878 | 0.851 | 0.576 | [model](https://paddlemodels.bj.bcebos.com/object_detection/faceboxes_original.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/face_detection/faceboxes.yml) |
| FaceBoxes | Lite | 640 | 8 | 32w | 0.901 | 0.875 | 0.760 | [model](https://paddlemodels.bj.bcebos.com/object_detection/faceboxes_lite.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/face_detection/faceboxes_lite.yml) | | FaceBoxes | Lite | 640 | 8 | 32w | 0.901 | 0.875 | 0.760 | [model](https://paddlemodels.bj.bcebos.com/object_detection/faceboxes_lite.tar) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/face_detection/faceboxes_lite.yml) |
**NOTES:** **NOTES:**
- Get mAP in `Easy/Medium/Hard Set` by multi-scale evaluation in `tools/face_eval.py`. - Get mAP in `Easy/Medium/Hard Set` by multi-scale evaluation in `tools/face_eval.py`.
For details can refer to [Evaluation](#Evaluate-on-the-WIDER-FACE). For details can refer to [Evaluation](#Evaluate-on-the-WIDER-FACE).
- BlazeFace-Lite Training and Testing ues [blazeface.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/master/configs/face_detection/blazeface.yml) - BlazeFace-Lite Training and Testing ues [blazeface.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/configs/face_detection/blazeface.yml)
configs file and set `lite_edition: true`. configs file and set `lite_edition: true`.
#### mAP in FDDB #### mAP in FDDB
...@@ -274,7 +274,7 @@ wget https://dataset.bj.bcebos.com/wider_face/wider_face_train_bbx_lmk_gt.txt ...@@ -274,7 +274,7 @@ wget https://dataset.bj.bcebos.com/wider_face/wider_face_train_bbx_lmk_gt.txt
| Architecture | Size | Img/gpu | Lr schd | Easy Set | Medium Set | Hard Set | Download | Configs | | Architecture | Size | Img/gpu | Lr schd | Easy Set | Medium Set | Hard Set | Download | Configs |
|:------------:|:----:|:-------:|:-------:|:---------:|:----------:|:---------:|:--------:|:--------:| |:------------:|:----:|:-------:|:-------:|:---------:|:----------:|:---------:|:--------:|:--------:|
| BlazeFace Keypoint | 640 | 16 | 16w | 0.852 | 0.816 | 0.662 | [download](https://paddlemodels.bj.bcebos.com/object_detection/blazeface_keypoint.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/face_detection/blazeface_keypoint.yml) | | BlazeFace Keypoint | 640 | 16 | 16w | 0.852 | 0.816 | 0.662 | [download](https://paddlemodels.bj.bcebos.com/object_detection/blazeface_keypoint.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/face_detection/blazeface_keypoint.yml) |
![](../images/12_Group_Group_12_Group_Group_12_84.jpg) ![](../images/12_Group_Group_12_Group_Group_12_84.jpg)
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static/docs/featured_model/LARGE_SCALE_DET_MODEL.md
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...@@ -20,6 +20,6 @@ ...@@ -20,6 +20,6 @@
| 骨架网络 | 网络类型 | 下载 | 配置文件 | | 骨架网络 | 网络类型 | 下载 | 配置文件 |
| :---------------| :---------------| :---------------| :--------------- | :---------------| :---------------| :---------------| :---------------
| ResNet50-vd-FPN-Dcnv2 | Cascade Faster | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_r50_vd_fpn_gen_server_side.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/rcnn_enhance/generic/cascade_rcnn_dcn_r50_vd_fpn_gen_server_side.yml) | | ResNet50-vd-FPN-Dcnv2 | Cascade Faster | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_r50_vd_fpn_gen_server_side.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/rcnn_enhance/generic/cascade_rcnn_dcn_r50_vd_fpn_gen_server_side.yml) |
| ResNet101-vd-FPN-Dcnv2 | Cascade Faster | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_r101_vd_fpn_gen_server_side.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/rcnn_enhance/generic/cascade_rcnn_dcn_r101_vd_fpn_gen_server_side.yml) | | ResNet101-vd-FPN-Dcnv2 | Cascade Faster | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_r101_vd_fpn_gen_server_side.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/rcnn_enhance/generic/cascade_rcnn_dcn_r101_vd_fpn_gen_server_side.yml) |
| CBResNet101-vd-FPN | Cascade Faster | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_cbr101_vd_fpn_server_side.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/rcnn_enhance/generic/cascade_rcnn_cbr101_vd_fpn_server_side.yml) | | CBResNet101-vd-FPN | Cascade Faster | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_cbr101_vd_fpn_server_side.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/rcnn_enhance/generic/cascade_rcnn_cbr101_vd_fpn_server_side.yml) |
static/docs/featured_model/LARGE_SCALE_DET_MODEL_en.md
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...@@ -18,6 +18,6 @@ There are relatively not enough categories in the above dataset (compared to 100 ...@@ -18,6 +18,6 @@ There are relatively not enough categories in the above dataset (compared to 100
| Backbone | Type | Download | Configs | | Backbone | Type | Download | Configs |
| :---------------| :---------------| :---------------| :--------------- | :---------------| :---------------| :---------------| :---------------
| ResNet50-vd-FPN-Dcnv2 | Cascade Faster | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_r50_vd_fpn_gen_server_side.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/rcnn_enhance/generic/cascade_rcnn_dcn_r50_vd_fpn_gen_server_side.yml) | | ResNet50-vd-FPN-Dcnv2 | Cascade Faster | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_r50_vd_fpn_gen_server_side.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/rcnn_enhance/generic/cascade_rcnn_dcn_r50_vd_fpn_gen_server_side.yml) |
| ResNet101-vd-FPN-Dcnv2 | Cascade Faster | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_r101_vd_fpn_gen_server_side.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/rcnn_enhance/generic/cascade_rcnn_dcn_r101_vd_fpn_gen_server_side.yml) | | ResNet101-vd-FPN-Dcnv2 | Cascade Faster | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcn_r101_vd_fpn_gen_server_side.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/rcnn_enhance/generic/cascade_rcnn_dcn_r101_vd_fpn_gen_server_side.yml) |
| CBResNet101-vd-FPN | Cascade Faster | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_cbr101_vd_fpn_server_side.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/rcnn_enhance/generic/cascade_rcnn_cbr101_vd_fpn_server_side.yml) | | CBResNet101-vd-FPN | Cascade Faster | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_cbr101_vd_fpn_server_side.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/rcnn_enhance/generic/cascade_rcnn_cbr101_vd_fpn_server_side.yml) |
static/docs/featured_model/YOLOv3_ENHANCEMENT.md
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...@@ -43,12 +43,12 @@ python tools/train.py -c configs/dcn/yolov3_r50vd_dcn_db_iouloss_obj365_pretrain ...@@ -43,12 +43,12 @@ python tools/train.py -c configs/dcn/yolov3_r50vd_dcn_db_iouloss_obj365_pretrain
| 模型 | 预训练模型 | 验证集 mAP | V100 python 预测速度（FPS）<sup>[1](#1)</sup> | V100 paddle预测库速度（ms/image）<sup>[2](#2)</sup> | P4 paddle预测库速度(ms/image) <sup>[2](#2)</sup> | 下载 | 配置文件 | | 模型 | 预训练模型 | 验证集 mAP | V100 python 预测速度（FPS）<sup>[1](#1)</sup> | V100 paddle预测库速度（ms/image）<sup>[2](#2)</sup> | P4 paddle预测库速度(ms/image) <sup>[2](#2)</sup> | 下载 | 配置文件 |
| :--------------------------------------: | :----------------------------------------------------------: | :--------: | :--------: | :------------------------------------: | :----------------------------------------------------------: | :--------: | :--------: | | :--------------------------------------: | :----------------------------------------------------------: | :--------: | :--------: | :------------------------------------: | :----------------------------------------------------------: | :--------: | :--------: |
| YOLOv3 DarkNet | [DarkNet pretrain](https://paddle-imagenet-models-name.bj.bcebos.com/DarkNet53_pretrained.tar) | 38.9 | 48.55 | 原生：19.63<br>tensorRT-FP32: 18.01<br>tensorRT-FP16: 11.47 | 原生：54.10<br>tensorRT-FP32: 47.44 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/yolov3_darknet.yml) | | YOLOv3 DarkNet | [DarkNet pretrain](https://paddle-imagenet-models-name.bj.bcebos.com/DarkNet53_pretrained.tar) | 38.9 | 48.55 | 原生：19.63<br>tensorRT-FP32: 18.01<br>tensorRT-FP16: 11.47 | 原生：54.10<br>tensorRT-FP32: 47.44 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_darknet.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/yolov3_darknet.yml) |
| YOLOv3 ResNet50_vd DCN | [ImageNet pretrain](https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_vd_pretrained.tar) | 39.1 | 50.80 | 原生：17.04<br>tensorRT-FP32: 16.28<br>tensorRT-FP16: 11.16 | 原生：40.01<br>tensorRT-FP32: 36.66 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn_imagenet.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/yolov3_r50vd_dcn.yml) | | YOLOv3 ResNet50_vd DCN | [ImageNet pretrain](https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_vd_pretrained.tar) | 39.1 | 50.80 | 原生：17.04<br>tensorRT-FP32: 16.28<br>tensorRT-FP16: 11.16 | 原生：40.01<br>tensorRT-FP32: 36.66 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn_imagenet.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/dcn/yolov3_r50vd_dcn.yml) |
| YOLOv3 ResNet50_vd DCN | [Object365 pretrain](https://paddlemodels.bj.bcebos.com/object_detection/ResNet50_vd_dcn_db_obj365_pretrained.tar) | 42.5 | 50.41 | 原生：16.76<br>tensorRT-FP32: 16.04<br>tensorRT-FP16: 10.70 | 原生：39.64<br>tensorRT-FP32: 35.93 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn_obj365_v2.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/yolov3_r50vd_dcn_obj365_pretrained_coco.yml) | | YOLOv3 ResNet50_vd DCN | [Object365 pretrain](https://paddlemodels.bj.bcebos.com/object_detection/ResNet50_vd_dcn_db_obj365_pretrained.tar) | 42.5 | 50.41 | 原生：16.76<br>tensorRT-FP32: 16.04<br>tensorRT-FP16: 10.70 | 原生：39.64<br>tensorRT-FP32: 35.93 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn_obj365_v2.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/dcn/yolov3_r50vd_dcn_obj365_pretrained_coco.yml) |
| YOLOv3 ResNet50_vd DCN DropBlock | [Object365 pretrain](https://paddlemodels.bj.bcebos.com/object_detection/ResNet50_vd_dcn_db_obj365_pretrained.tar) | 42.8 | 49.97 | 原生：16.55<br>tensorRT-FP32: 16.07<br>tensorRT-FP16: 10.69 | 原生：39.72<br/>tensorRT-FP32: 35.98 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn_obj365_dropblock.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/yolov3_r50vd_dcn_db_obj365_pretrained_coco.yml) | | YOLOv3 ResNet50_vd DCN DropBlock | [Object365 pretrain](https://paddlemodels.bj.bcebos.com/object_detection/ResNet50_vd_dcn_db_obj365_pretrained.tar) | 42.8 | 49.97 | 原生：16.55<br>tensorRT-FP32: 16.07<br>tensorRT-FP16: 10.69 | 原生：39.72<br/>tensorRT-FP32: 35.98 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn_obj365_dropblock.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/dcn/yolov3_r50vd_dcn_db_obj365_pretrained_coco.yml) |
| YOLOv3 ResNet50_vd DCN DropBlock IoULoss | [Object365 pretrain](https://paddlemodels.bj.bcebos.com/object_detection/ResNet50_vd_dcn_db_obj365_pretrained.tar) | 43.2 | 49.91 | 原生：16.46<br>tensorRT-FP32: 15.83<br>tensorRT-FP16: 10.80 | 原生：39.58<br/>tensorRT-FP32: 35.61 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn_obj365_dropblock_iouloss.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/yolov3_r50vd_dcn_db_iouloss_obj365_pretrained_coco.yml) | | YOLOv3 ResNet50_vd DCN DropBlock IoULoss | [Object365 pretrain](https://paddlemodels.bj.bcebos.com/object_detection/ResNet50_vd_dcn_db_obj365_pretrained.tar) | 43.2 | 49.91 | 原生：16.46<br>tensorRT-FP32: 15.83<br>tensorRT-FP16: 10.80 | 原生：39.58<br/>tensorRT-FP32: 35.61 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn_obj365_dropblock_iouloss.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/dcn/yolov3_r50vd_dcn_db_iouloss_obj365_pretrained_coco.yml) |
| YOLOv3 ResNet50_vd DCN DropBlock IoU-Aware | [Object365 pretrain](https://paddlemodels.bj.bcebos.com/object_detection/ResNet50_vd_dcn_db_obj365_pretrained.tar) | 43.6 | 48.19 | 原生：17.74<br>tensorRT-FP32: 16.73<br>tensorRT-FP16: 11.74 | 原生：41.39<br/>tensorRT-FP32: 37.75 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn_db_iouaware_obj365_pretrained_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/yolov3_r50vd_dcn_db_iouaware_obj365_pretrained_coco.yml) | | YOLOv3 ResNet50_vd DCN DropBlock IoU-Aware | [Object365 pretrain](https://paddlemodels.bj.bcebos.com/object_detection/ResNet50_vd_dcn_db_obj365_pretrained.tar) | 43.6 | 48.19 | 原生：17.74<br>tensorRT-FP32: 16.73<br>tensorRT-FP16: 11.74 | 原生：41.39<br/>tensorRT-FP32: 37.75 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/yolov3_r50vd_dcn_db_iouaware_obj365_pretrained_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/dcn/yolov3_r50vd_dcn_db_iouaware_obj365_pretrained_coco.yml) |
<a name="1">[1]</a>V100 python 预测速度是在一张Tesla V100的GPU上通过```tools/eval.py```测试所有验证集得到，单位是fps(图片数/秒), cuDNN版本是7.5，包括数据加载、网络前向执行和后处理, batch size是1。 <a name="1">[1]</a>V100 python 预测速度是在一张Tesla V100的GPU上通过```tools/eval.py```测试所有验证集得到，单位是fps(图片数/秒), cuDNN版本是7.5，包括数据加载、网络前向执行和后处理, batch size是1。
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| 模型 | 验证集 mAP | 下载链接 | 配置文件 | | 模型 | 验证集 mAP | 下载链接 | 配置文件 |
| :-----------------: | :--------: | :----------------------------------------------------------: | :--------: | | :-----------------: | :--------: | :----------------------------------------------------------: | :--------: |
| CACascadeRCNN SE154 | 31.6 | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcnv2_se154_vd_fpn_gn_cas_obj365.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/obj365/cascade_rcnn_dcnv2_se154_vd_fpn_gn_cas.yml) | | CACascadeRCNN SE154 | 31.6 | [model](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_dcnv2_se154_vd_fpn_gn_cas_obj365.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/obj365/cascade_rcnn_dcnv2_se154_vd_fpn_gn_cas.yml) |
## 模型效果 ## 模型效果
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| 模型结构 | Public/Private Score | 下载链接 | 配置文件 | | 模型结构 | Public/Private Score | 下载链接 | 配置文件 |
| :-----------------: | :--------: | :----------------------------------------------------------: | :--------: | | :-----------------: | :--------: | :----------------------------------------------------------: | :--------: |
| CascadeCARCNN-FPN-Dcnv2-Nonlocal ResNet200-vd | 0.62690/0.59459 | [模型](https://paddlemodels.bj.bcebos.com/object_detection/oidv5_cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/oidv5/cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.yml) | | CascadeCARCNN-FPN-Dcnv2-Nonlocal ResNet200-vd | 0.62690/0.59459 | [模型](https://paddlemodels.bj.bcebos.com/object_detection/oidv5_cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/oidv5/cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.yml) |
此外，为验证模型的性能，PaddleDetection基于该模型结构，也训练了针对COCO2017和Objects365 Dataset的模型，模型和验证集指标如下表。 此外，为验证模型的性能，PaddleDetection基于该模型结构，也训练了针对COCO2017和Objects365 Dataset的模型，模型和验证集指标如下表。
| 模型结构 | 数据集 | 验证集mAP | 下载链接 | 配置文件 | | 模型结构 | 数据集 | 验证集mAP | 下载链接 | 配置文件 |
| :-----------------: | :--------: | :--------: | :----------------------------------------------------------: | :--------: | | :-----------------: | :--------: | :--------: | :----------------------------------------------------------: | :--------: |
| CascadeCARCNN-FPN-Dcnv2-Nonlocal ResNet200-vd | COCO2017 | 51.7% | [模型](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/dcn/cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.yml) | | CascadeCARCNN-FPN-Dcnv2-Nonlocal ResNet200-vd | COCO2017 | 51.7% | [模型](https://paddlemodels.bj.bcebos.com/object_detection/cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/dcn/cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.yml) |
| CascadeCARCNN-FPN-Dcnv2-Nonlocal ResNet200-vd | Objects365 | 34.5% | [模型](https://paddlemodels.bj.bcebos.com/object_detection/obj365_cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/obj365/cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.yml) | | CascadeCARCNN-FPN-Dcnv2-Nonlocal ResNet200-vd | Objects365 | 34.5% | [模型](https://paddlemodels.bj.bcebos.com/object_detection/obj365_cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs/obj365/cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.yml) |
COCO和Objects365 Dataset数据格式相同，目前只支持预测和评估。 COCO和Objects365 Dataset数据格式相同，目前只支持预测和评估。
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...@@ -16,7 +16,7 @@ English | [简体中文](INSTALL_cn.md) ...@@ -16,7 +16,7 @@ English | [简体中文](INSTALL_cn.md)
This document covers how to install PaddleDetection, its dependencies This document covers how to install PaddleDetection, its dependencies
(including PaddlePaddle), together with COCO and Pascal VOC dataset. (including PaddlePaddle), together with COCO and Pascal VOC dataset.
For general information about PaddleDetection, please see [README.md](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/). For general information about PaddleDetection, please see [README.md](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/).
## Install PaddlePaddle ## Install PaddlePaddle
...@@ -106,7 +106,7 @@ git clone https://github.com/PaddlePaddle/PaddleDetection.git ...@@ -106,7 +106,7 @@ git clone https://github.com/PaddlePaddle/PaddleDetection.git
**Install Python dependencies:** **Install Python dependencies:**
Required python packages are specified in [requirements.txt](https://github.com/PaddlePaddle/PaddleDetection/blob/master/requirements.txt), and can be installed with: Required python packages are specified in [requirements.txt](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/requirements.txt), and can be installed with:
``` ```
pip install -r requirements.txt pip install -r requirements.txt
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这份文档介绍了如何安装PaddleDetection及其依赖项(包括PaddlePaddle)。 这份文档介绍了如何安装PaddleDetection及其依赖项(包括PaddlePaddle)。
PaddleDetection的相关信息，请参考[README.md](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/README_cn.md). PaddleDetection的相关信息，请参考[README.md](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/README_cn.md).
## 安装PaddlePaddle ## 安装PaddlePaddle
...@@ -85,7 +85,7 @@ python -c "import paddle; print(paddle.__version__)" ...@@ -85,7 +85,7 @@ python -c "import paddle; print(paddle.__version__)"
**安装Python依赖库：** **安装Python依赖库：**
Python依赖库在[requirements.txt](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/requirements.txt) 中给出，可通过如下命令安装： Python依赖库在[requirements.txt](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/requirements.txt) 中给出，可通过如下命令安装：
``` ```
pip install -r requirements.txt pip install -r requirements.txt
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### 蒸馏通道剪裁模型 ### 蒸馏通道剪裁模型
可通过高精度模型蒸馏通道剪裁后模型的方式，训练方法及相关示例见[蒸馏通道剪裁模型](https://github.com/PaddlePaddle/PaddleDetection/blob/master/slim/extensions/distill_pruned_model/distill_pruned_model_demo.ipynb)。 可通过高精度模型蒸馏通道剪裁后模型的方式，训练方法及相关示例见[蒸馏通道剪裁模型](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/slim/extensions/distill_pruned_model/distill_pruned_model_demo.ipynb)。
COCO数据集上蒸馏通道剪裁模型库如下。 COCO数据集上蒸馏通道剪裁模型库如下。
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...@@ -10,7 +10,7 @@ ...@@ -10,7 +10,7 @@
- [检测库的常规训练方法](https://github.com/PaddlePaddle/PaddleDetection) - [检测库的常规训练方法](https://github.com/PaddlePaddle/PaddleDetection)
- [PaddleSlim蒸馏API文档](https://paddlepaddle.github.io/PaddleSlim/api/single_distiller_api/) - [PaddleSlim蒸馏API文档](https://paddlepaddle.github.io/PaddleSlim/api/single_distiller_api/)
已发布蒸馏模型见[压缩模型库](https://github.com/PaddlePaddle/PaddleDetection/blob/master/slim/README.md) 已发布蒸馏模型见[压缩模型库](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/slim/README.md)
## 安装PaddleSlim ## 安装PaddleSlim
可按照[PaddleSlim使用文档](https://paddlepaddle.github.io/PaddleSlim/)中的步骤安装PaddleSlim 可按照[PaddleSlim使用文档](https://paddlepaddle.github.io/PaddleSlim/)中的步骤安装PaddleSlim
...@@ -89,7 +89,7 @@ yolo_output_names = [ ...@@ -89,7 +89,7 @@ yolo_output_names = [
## 训练 ## 训练
根据[PaddleDetection/tools/train.py](https://github.com/PaddlePaddle/PaddleDetection/blob/master/tools/train.py)编写压缩脚本`distill.py`。 根据[PaddleDetection/tools/train.py](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/tools/train.py)编写压缩脚本`distill.py`。
在该脚本中定义了teacher_model和student_model，用teacher_model的输出指导student_model的训练 在该脚本中定义了teacher_model和student_model，用teacher_model的输出指导student_model的训练
### 执行示例 ### 执行示例
...@@ -178,7 +178,7 @@ python -u slim/distillation/distill.py \ ...@@ -178,7 +178,7 @@ python -u slim/distillation/distill.py \
## 评估 ## 评估
每隔`snap_shot_iter`步后会保存一个checkpoint模型可以用于评估，使用PaddleDetection目录下[tools/eval.py](https://github.com/PaddlePaddle/PaddleDetection/blob/master/tools/eval.py)评估脚本，并指定`weights`为训练得到的模型路径 每隔`snap_shot_iter`步后会保存一个checkpoint模型可以用于评估，使用PaddleDetection目录下[tools/eval.py](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/tools/eval.py)评估脚本，并指定`weights`为训练得到的模型路径
运行命令为： 运行命令为：
```bash ```bash
...@@ -197,7 +197,7 @@ python -u tools/eval.py -c configs/yolov3_mobilenet_v1.yml \ ...@@ -197,7 +197,7 @@ python -u tools/eval.py -c configs/yolov3_mobilenet_v1.yml \
## 预测 ## 预测
每隔`snap_shot_iter`步后保存的checkpoint模型也可以用于预测，使用PaddleDetection目录下[tools/infer.py](https://github.com/PaddlePaddle/PaddleDetection/blob/master/tools/infer.py)评估脚本，并指定`weights`为训练得到的模型路径 每隔`snap_shot_iter`步后保存的checkpoint模型也可以用于预测，使用PaddleDetection目录下[tools/infer.py](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/tools/infer.py)评估脚本，并指定`weights`为训练得到的模型路径
### Python预测 ### Python预测
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...@@ -41,7 +41,7 @@ double_blaze_filters = [ ...@@ -41,7 +41,7 @@ double_blaze_filters = [
[self.double_filter_num[tokens[2]], self.mid_filter_num[tokens[6]], self.double_filter_num[tokens[3]], 2], [self.double_filter_num[tokens[2]], self.mid_filter_num[tokens[6]], self.double_filter_num[tokens[3]], 2],
[self.double_filter_num[tokens[3]], self.mid_filter_num[tokens[7]], self.double_filter_num[tokens[3]]]] [self.double_filter_num[tokens[3]], self.mid_filter_num[tokens[7]], self.double_filter_num[tokens[3]]]]
``` ```
blaze_filters与double_blaze_filters字段请参考[blazenet.py](https://github.com/PaddlePaddle/PaddleDetection/blob/master/ppdet/modeling/backbones/blazenet.py)中定义。 blaze_filters与double_blaze_filters字段请参考[blazenet.py](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/ppdet/modeling/backbones/blazenet.py)中定义。
初始化tokens为：[2, 1, 3, 8, 2, 1, 2, 1, 1]。 初始化tokens为：[2, 1, 3, 8, 2, 1, 2, 1, 1]。
...@@ -84,10 +84,10 @@ BlazeNet: ...@@ -84,10 +84,10 @@ BlazeNet:
- （2）训练、评估与预测： - （2）训练、评估与预测：
启动完整的训练评估实验，可参考PaddleDetection的[训练、评估与预测流程](https://github.com/PaddlePaddle/PaddleDetection/blob/master/docs/tutorials/GETTING_STARTED_cn.md) 启动完整的训练评估实验，可参考PaddleDetection的[训练、评估与预测流程](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/docs/tutorials/GETTING_STARTED_cn.md)
## 实验结果 ## 实验结果
请参考[人脸检测模型库](https://github.com/PaddlePaddle/PaddleDetection/blob/master/docs/featured_model/FACE_DETECTION.md)中BlazeFace-NAS的实验结果。 请参考[人脸检测模型库](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/docs/featured_model/FACE_DETECTION.md)中BlazeFace-NAS的实验结果。
## FAQ ## FAQ
- 运行报错：`socket.error: [Errno 98] Address already in use`。 - 运行报错：`socket.error: [Errno 98] Address already in use`。
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# 卷积层通道剪裁教程 # 卷积层通道剪裁教程
请确保已正确[安装PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection/blob/master/docs/tutorials/INSTALL_cn.md)及其依赖。 请确保已正确[安装PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/docs/tutorials/INSTALL_cn.md)及其依赖。
该文档介绍如何使用[PaddleSlim](https://paddlepaddle.github.io/PaddleSlim)的卷积通道剪裁接口对检测库中的模型的卷积层的通道数进行剪裁。 该文档介绍如何使用[PaddleSlim](https://paddlepaddle.github.io/PaddleSlim)的卷积通道剪裁接口对检测库中的模型的卷积层的通道数进行剪裁。
...@@ -8,15 +8,15 @@ ...@@ -8,15 +8,15 @@
该教程中所示操作，如无特殊说明，均在`PaddleDetection/`路径下执行。 该教程中所示操作，如无特殊说明，均在`PaddleDetection/`路径下执行。
已发布裁剪模型见[压缩模型库](https://github.com/PaddlePaddle/PaddleDetection/blob/master/slim/README.md) 已发布裁剪模型见[压缩模型库](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/slim/README.md)
## 1. 数据准备 ## 1. 数据准备
请参考检测库[数据下载](https://github.com/PaddlePaddle/PaddleDetection/blob/master/docs/tutorials/INSTALL_cn.md)文档准备数据。 请参考检测库[数据下载](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/docs/tutorials/INSTALL_cn.md)文档准备数据。
## 2. 模型选择 ## 2. 模型选择
通过`-c`选项指定待裁剪模型的配置文件的相对路径，更多可选配置文件请参考: [检测库配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs) 通过`-c`选项指定待裁剪模型的配置文件的相对路径，更多可选配置文件请参考: [检测库配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.1/static/configs)
对于剪裁任务，原模型的权重不一定对剪裁后的模型训练的重训练有贡献，所以加载原模型的权重不是必需的步骤。 对于剪裁任务，原模型的权重不一定对剪裁后的模型训练的重训练有贡献，所以加载原模型的权重不是必需的步骤。
...@@ -32,7 +32,7 @@ ...@@ -32,7 +32,7 @@
-o weights=output/yolov3_mobilenet_v1_voc/model_final -o weights=output/yolov3_mobilenet_v1_voc/model_final
``` ```
官方已发布的模型请参考: [模型库](https://github.com/PaddlePaddle/PaddleDetection/blob/master/docs/MODEL_ZOO_cn.md) 官方已发布的模型请参考: [模型库](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/docs/MODEL_ZOO_cn.md)
## 3. 确定待分析参数 ## 3. 确定待分析参数
...@@ -49,7 +49,7 @@ python slim/prune/prune.py \ ...@@ -49,7 +49,7 @@ python slim/prune/prune.py \
## 4. 分析待剪裁参数敏感度 ## 4. 分析待剪裁参数敏感度
可通过敏感度分析脚本分析待剪裁参数敏感度得到合适的剪裁率，敏感度分析工具见[敏感度分析](https://github.com/PaddlePaddle/PaddleDetection/blob/master/slim/sensitive/README.md)。 可通过敏感度分析脚本分析待剪裁参数敏感度得到合适的剪裁率，敏感度分析工具见[敏感度分析](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/slim/sensitive/README.md)。
## 5. 启动剪裁任务 ## 5. 启动剪裁任务
...@@ -97,16 +97,16 @@ python slim/prune/export_model.py \ ...@@ -97,16 +97,16 @@ python slim/prune/export_model.py \
**当前PaddleSlim的剪裁功能不支持剪裁循环体或条件判断语句块内的卷积层，请避免剪裁循环和判断语句块前的一个卷积和语句块内部的卷积。** **当前PaddleSlim的剪裁功能不支持剪裁循环体或条件判断语句块内的卷积层，请避免剪裁循环和判断语句块前的一个卷积和语句块内部的卷积。**
对于[faster_rcnn_r50](https://github.com/PaddlePaddle/PaddleDetection/blob/master/configs/faster_rcnn_r50_1x.yml)或[mask_rcnn_r50](https://github.com/PaddlePaddle/PaddleDetection/blob/master/configs/mask_rcnn_r50_1x.yml)网络，请剪裁卷积`res4f_branch2c`之前的卷积。 对于[faster_rcnn_r50](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/configs/faster_rcnn_r50_1x.yml)或[mask_rcnn_r50](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/configs/mask_rcnn_r50_1x.yml)网络，请剪裁卷积`res4f_branch2c`之前的卷积。
对[faster_rcnn_r50](https://github.com/PaddlePaddle/PaddleDetection/blob/master/configs/faster_rcnn_r50_1x.yml)剪裁示例如下： 对[faster_rcnn_r50](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/configs/faster_rcnn_r50_1x.yml)剪裁示例如下：
``` ```
# demo for faster_rcnn_r50 # demo for faster_rcnn_r50
python slim/prune/prune.py -c ./configs/faster_rcnn_r50_1x.yml --pruned_params "res4f_branch2b_weights,res4f_branch2a_weights" --pruned_ratios="0.3,0.4" --eval python slim/prune/prune.py -c ./configs/faster_rcnn_r50_1x.yml --pruned_params "res4f_branch2b_weights,res4f_branch2a_weights" --pruned_ratios="0.3,0.4" --eval
``` ```
对[mask_rcnn_r50](https://github.com/PaddlePaddle/PaddleDetection/blob/master/configs/mask_rcnn_r50_1x.yml)剪裁示例如下： 对[mask_rcnn_r50](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/configs/mask_rcnn_r50_1x.yml)剪裁示例如下：
``` ```
# demo for mask_rcnn_r50 # demo for mask_rcnn_r50
......
static/slim/quantization/README.md
浏览文件 @ 99c7e3a7
...@@ -19,7 +19,7 @@ ...@@ -19,7 +19,7 @@
## 训练 ## 训练
根据 [tools/train.py](https://github.com/PaddlePaddle/PaddleDetection/blob/master/tools/train.py) 编写压缩脚本train.py。脚本中量化的步骤如下。 根据 [tools/train.py](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/tools/train.py) 编写压缩脚本train.py。脚本中量化的步骤如下。
### 定义量化配置 ### 定义量化配置
config = { config = {
......
static/slim/sensitive/README.md
浏览文件 @ 99c7e3a7
# 卷积层敏感度分析教程 # 卷积层敏感度分析教程
请确保已正确[安装PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection/blob/master/docs/tutorials/INSTALL_cn.md)及其依赖。 请确保已正确[安装PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/docs/tutorials/INSTALL_cn.md)及其依赖。
该文档介绍如何使用[PaddleSlim](https://paddlepaddle.github.io/PaddleSlim)的敏感度分析接口对检测库中的模型的卷积层进行敏感度分析。 该文档介绍如何使用[PaddleSlim](https://paddlepaddle.github.io/PaddleSlim)的敏感度分析接口对检测库中的模型的卷积层进行敏感度分析。
...@@ -10,11 +10,11 @@ ...@@ -10,11 +10,11 @@
## 数据准备 ## 数据准备
请参考检测库[数据模块](https://github.com/PaddlePaddle/PaddleDetection/blob/master/docs/tutorials/INSTALL_cn.md)文档准备数据。 请参考检测库[数据模块](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/docs/tutorials/INSTALL_cn.md)文档准备数据。
## 模型选择 ## 模型选择
通过`-c`选项指定待分析模型的配置文件的相对路径，更多可选配置文件请参考: [检测库配置文件](https://github.com/PaddlePaddle/PaddleDetection/blob/master/configs) 通过`-c`选项指定待分析模型的配置文件的相对路径，更多可选配置文件请参考: [检测库配置文件](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/configs)
通过`-o weights`指定模型的权重，可以指定url或本地文件系统的路径。如下所示： 通过`-o weights`指定模型的权重，可以指定url或本地文件系统的路径。如下所示：
...@@ -28,7 +28,7 @@ ...@@ -28,7 +28,7 @@
-o weights=output/yolov3_mobilenet_v1_voc/model_final -o weights=output/yolov3_mobilenet_v1_voc/model_final
``` ```
官方已发布的模型请参考: [模型库](https://github.com/PaddlePaddle/PaddleDetection/blob/master/docs/MODEL_ZOO_cn.md) 官方已发布的模型请参考: [模型库](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/static/docs/MODEL_ZOO_cn.md)
## 确定待分析参数 ## 确定待分析参数
......
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