diff --git a/configs/cascade_rcnn/README.md b/configs/cascade_rcnn/README.md
index e74641a3f726784034b63964288af5761cf1dbb7..e6a56ca880eac47a5f31a8a790a6fd144330c3e7 100644
--- a/configs/cascade_rcnn/README.md
+++ b/configs/cascade_rcnn/README.md
@@ -4,12 +4,12 @@
| 骨架网络 | 网络类型 | 每张GPU图片个数 | 学习率策略 |推理时间(fps) | Box AP | Mask AP | 下载 | 配置文件 |
| :------------------- | :------------- | :-----: | :-----: | :------------: | :-----: | :-----: | :-----------------------------------------------------: | :-----: |
-| ResNet50-FPN | Cascade Faster | 1 | 1x | ---- | 41.1 | - | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_rcnn_r50_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/cascade_rcnn/cascade_rcnn_r50_fpn_1x_coco.yml) |
-| ResNet50-FPN | Cascade Mask | 1 | 1x | ---- | 41.8 | 36.3 | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_mask_rcnn_r50_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/cascade_rcnn/cascade_mask_rcnn_r50_fpn_1x_coco.yml) |
-| ResNet50-vd-SSLDv2-FPN | Cascade Faster | 1 | 1x | ---- | 44.4 | - | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/cascade_rcnn/cascade_rcnn_r50_vd_fpn_ssld_1x_coco.yml) |
-| ResNet50-vd-SSLDv2-FPN | Cascade Faster | 1 | 2x | ---- | 45.0 | - | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/cascade_rcnn/cascade_rcnn_r50_vd_fpn_ssld_2x_coco.yml) |
-| ResNet50-vd-SSLDv2-FPN | Cascade Mask | 1 | 1x | ---- | 44.9 | 39.1 | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_mask_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/cascade_rcnn/cascade_mask_rcnn_r50_vd_fpn_ssld_1x_coco.yml) |
-| ResNet50-vd-SSLDv2-FPN | Cascade Mask | 1 | 2x | ---- | 45.7 | 39.7 | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_mask_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/cascade_rcnn/cascade_mask_rcnn_r50_vd_fpn_ssld_2x_coco.yml) |
+| ResNet50-FPN | Cascade Faster | 1 | 1x | ---- | 41.1 | - | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_rcnn_r50_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/cascade_rcnn/cascade_rcnn_r50_fpn_1x_coco.yml) |
+| ResNet50-FPN | Cascade Mask | 1 | 1x | ---- | 41.8 | 36.3 | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_mask_rcnn_r50_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/cascade_rcnn/cascade_mask_rcnn_r50_fpn_1x_coco.yml) |
+| ResNet50-vd-SSLDv2-FPN | Cascade Faster | 1 | 1x | ---- | 44.4 | - | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/cascade_rcnn/cascade_rcnn_r50_vd_fpn_ssld_1x_coco.yml) |
+| ResNet50-vd-SSLDv2-FPN | Cascade Faster | 1 | 2x | ---- | 45.0 | - | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/cascade_rcnn/cascade_rcnn_r50_vd_fpn_ssld_2x_coco.yml) |
+| ResNet50-vd-SSLDv2-FPN | Cascade Mask | 1 | 1x | ---- | 44.9 | 39.1 | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_mask_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/cascade_rcnn/cascade_mask_rcnn_r50_vd_fpn_ssld_1x_coco.yml) |
+| ResNet50-vd-SSLDv2-FPN | Cascade Mask | 1 | 2x | ---- | 45.7 | 39.7 | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_mask_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/cascade_rcnn/cascade_mask_rcnn_r50_vd_fpn_ssld_2x_coco.yml) |
**注意：** Cascade R-CNN模型精度依赖Paddle develop分支修改，精度复现须使用[每日版本](https://www.paddlepaddle.org.cn/documentation/docs/zh/install/Tables.html#whl-dev)或2.0.1版本(将于2021.03发布)，使用Paddle 2.0.0版本会有少量精度损失。
diff --git a/configs/dcn/README.md b/configs/dcn/README.md
index 3248a387c018c71b48d22c3aa20cd972db2defbb..78e8bf584d1da9e91f69a1d9636a63c05074653a 100644
--- a/configs/dcn/README.md
+++ b/configs/dcn/README.md
@@ -2,17 +2,17 @@
| 骨架网络 | 网络类型 | 卷积 | 每张GPU图片个数 | 学习率策略 |推理时间(fps)| Box AP | Mask AP | 下载 | 配置文件 |
| :------------------- | :------------- | :-----: |:--------: | :-----: | :-----------: |:----: | :-----: | :----------------------------------------------------------: | :----: |
-| ResNet50-FPN | Faster | c3-c5 | 1 | 1x | - | 42.1 | - | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_dcn_r50_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/dcn/faster_rcnn_dcn_r50_fpn_1x_coco.yml) |
-| ResNet50-vd-FPN | Faster | c3-c5 | 1 | 1x | - | 42.7 | - | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_dcn_r50_vd_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/dcn/faster_rcnn_dcn_r50_vd_fpn_1x_coco.yml) |
-| ResNet50-vd-FPN | Faster | c3-c5 | 1 | 2x | - | 43.7 | - | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_dcn_r50_vd_fpn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/dcn/faster_rcnn_dcn_r50_vd_fpn_2x_coco.yml) |
-| ResNet101-vd-FPN | Faster | c3-c5 | 1 | 1x | - | 45.1 | - | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_dcn_r101_vd_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/dcn/faster_rcnn_dcn_r101_vd_fpn_1x_coco.yml) |
-| ResNeXt101-vd-FPN | Faster | c3-c5 | 1 | 1x | - | 46.5 | - | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_dcn_x101_vd_64x4d_fpn_1x_coco.pdparams) |[配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/dcn/faster_rcnn_dcn_x101_vd_64x4d_fpn_1x_coco.yml) |
-| ResNet50-FPN | Mask | c3-c5 | 1 | 1x | - | 42.7 | 38.4 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_dcn_r50_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/dcn/mask_rcnn_dcn_r50_fpn_1x_coco.yml) |
-| ResNet50-vd-FPN | Mask | c3-c5 | 1 | 2x | - | 44.6 | 39.8 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_dcn_r50_vd_fpn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/dcn/mask_rcnn_dcn_r50_vd_fpn_2x_coco.yml) |
-| ResNet101-vd-FPN | Mask | c3-c5 | 1 | 1x | - | 45.6 | 40.6 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_dcn_r101_vd_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/dcn/mask_rcnn_dcn_r101_vd_fpn_1x_coco.yml) |
-| ResNeXt101-vd-FPN | Mask | c3-c5 | 1 | 1x | - | 47.3 | 42.0 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_dcn_x101_vd_64x4d_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/dcn/mask_rcnn_dcn_x101_vd_64x4d_fpn_1x_coco.yml) |
-| ResNet50-FPN | Cascade Faster | c3-c5 | 1 | 1x | - | 42.1 | - | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_rcnn_dcn_r50_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/dcn/cascade_rcnn_dcn_r50_fpn_1x_coco.yml) |
-| ResNeXt101-vd-FPN | Cascade Faster | c3-c5 | 1 | 1x | - | 48.8 | - | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_rcnn_dcn_x101_vd_64x4d_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/dcn/cascade_rcnn_dcn_x101_vd_64x4d_fpn_1x_coco.yml) |
+| ResNet50-FPN | Faster | c3-c5 | 1 | 1x | - | 42.1 | - | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_dcn_r50_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/dcn/faster_rcnn_dcn_r50_fpn_1x_coco.yml) |
+| ResNet50-vd-FPN | Faster | c3-c5 | 1 | 1x | - | 42.7 | - | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_dcn_r50_vd_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/dcn/faster_rcnn_dcn_r50_vd_fpn_1x_coco.yml) |
+| ResNet50-vd-FPN | Faster | c3-c5 | 1 | 2x | - | 43.7 | - | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_dcn_r50_vd_fpn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/dcn/faster_rcnn_dcn_r50_vd_fpn_2x_coco.yml) |
+| ResNet101-vd-FPN | Faster | c3-c5 | 1 | 1x | - | 45.1 | - | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_dcn_r101_vd_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/dcn/faster_rcnn_dcn_r101_vd_fpn_1x_coco.yml) |
+| ResNeXt101-vd-FPN | Faster | c3-c5 | 1 | 1x | - | 46.5 | - | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_dcn_x101_vd_64x4d_fpn_1x_coco.pdparams) |[配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/dcn/faster_rcnn_dcn_x101_vd_64x4d_fpn_1x_coco.yml) |
+| ResNet50-FPN | Mask | c3-c5 | 1 | 1x | - | 42.7 | 38.4 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_dcn_r50_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/dcn/mask_rcnn_dcn_r50_fpn_1x_coco.yml) |
+| ResNet50-vd-FPN | Mask | c3-c5 | 1 | 2x | - | 44.6 | 39.8 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_dcn_r50_vd_fpn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/dcn/mask_rcnn_dcn_r50_vd_fpn_2x_coco.yml) |
+| ResNet101-vd-FPN | Mask | c3-c5 | 1 | 1x | - | 45.6 | 40.6 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_dcn_r101_vd_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/dcn/mask_rcnn_dcn_r101_vd_fpn_1x_coco.yml) |
+| ResNeXt101-vd-FPN | Mask | c3-c5 | 1 | 1x | - | 47.3 | 42.0 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_dcn_x101_vd_64x4d_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/dcn/mask_rcnn_dcn_x101_vd_64x4d_fpn_1x_coco.yml) |
+| ResNet50-FPN | Cascade Faster | c3-c5 | 1 | 1x | - | 42.1 | - | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_rcnn_dcn_r50_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/dcn/cascade_rcnn_dcn_r50_fpn_1x_coco.yml) |
+| ResNeXt101-vd-FPN | Cascade Faster | c3-c5 | 1 | 1x | - | 48.8 | - | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_rcnn_dcn_x101_vd_64x4d_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/dcn/cascade_rcnn_dcn_x101_vd_64x4d_fpn_1x_coco.yml) |
**注意事项:**
diff --git a/configs/deformable_detr/README.md b/configs/deformable_detr/README.md
index 6b24c4ffab67073df5058c1d76f82bbdf835d1b0..b8a142824bfc59ca4df088bfa47d27e2fc4d109c 100644
--- a/configs/deformable_detr/README.md
+++ b/configs/deformable_detr/README.md
@@ -10,7 +10,7 @@ Deformable DETR is an object detection model based on DETR. We reproduced the mo
| Backbone | Model | Images/GPU | Inf time (fps) | Box AP | Config | Download |
|:------:|:--------:|:--------:|:--------------:|:------:|:------:|:--------:|
-| R-50 | Deformable DETR | 2 | --- | 44.1 | [config](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/deformable_detr/deformable_detr_r50_1x_coco.yml) | [model](https://paddledet.bj.bcebos.com/models/deformable_detr_r50_1x_coco.pdparams) |
+| R-50 | Deformable DETR | 2 | --- | 44.1 | [config](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.2/configs/deformable_detr/deformable_detr_r50_1x_coco.yml) | [model](https://paddledet.bj.bcebos.com/models/deformable_detr_r50_1x_coco.pdparams) |
**Notes:**
diff --git a/configs/detr/README.md b/configs/detr/README.md
index 26f83a3fd2f3dc20bd32310c9cb441da4ee278ff..47b7a1198e4b8b7704cfcb13fc2cbfaf8b5e895c 100644
--- a/configs/detr/README.md
+++ b/configs/detr/README.md
@@ -10,7 +10,7 @@ DETR is an object detection model based on transformer. We reproduced the model
| Backbone | Model | Images/GPU | Inf time (fps) | Box AP | Config | Download |
|:------:|:--------:|:--------:|:--------------:|:------:|:------:|:--------:|
-| R-50 | DETR | 4 | --- | 42.3 | [config](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/detr/detr_r50_1x_coco.yml) | [model](https://paddledet.bj.bcebos.com/models/detr_r50_1x_coco.pdparams) |
+| R-50 | DETR | 4 | --- | 42.3 | [config](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.2/configs/detr/detr_r50_1x_coco.yml) | [model](https://paddledet.bj.bcebos.com/models/detr_r50_1x_coco.pdparams) |
**Notes:**
diff --git a/configs/dota/README.md b/configs/dota/README.md
index 934e597f79056653db231298930384c99b2f0408..90c7bbd3ddd9a6c0fd7461f02a84d75d3eba85c3 100644
--- a/configs/dota/README.md
+++ b/configs/dota/README.md
@@ -9,7 +9,7 @@
## 简介
-[S2ANet](https://arxiv.org/pdf/2008.09397.pdf)是用于检测旋转框的模型，要求使用PaddlePaddle 2.0.1(可使用pip安装) 或适当的[develop版本](https://www.paddlepaddle.org.cn/documentation/docs/zh/develop/install/Tables.html#whl-release)。
+[S2ANet](https://arxiv.org/pdf/2008.09397.pdf)是用于检测旋转框的模型，要求使用PaddlePaddle 2.0.1(可使用pip安装)及以上版本
## 准备数据
@@ -131,7 +131,7 @@ python3.7 tools/infer.py -c configs/dota/s2anet_1x_dota.yml -o weights=./weights
| 模型 | GPU个数 | Conv类型 | mAP | 模型下载 | 配置文件 |
|:-----------:|:-------:|:----------:|:--------:| :----------:| :---------: |
-| S2ANet | 8 | Conv | 71.42 | [model](https://paddledet.bj.bcebos.com/models/s2anet_conv_1x_dota.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/dota/s2anet_conv_1x_dota.yml) |
+| S2ANet | 8 | Conv | 71.42 | [model](https://paddledet.bj.bcebos.com/models/s2anet_conv_1x_dota.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/dota/s2anet_conv_1x_dota.yml) |
**注意：**这里使用`multiclass_nms`，与原作者使用nms略有不同，精度相比原始论文中高0.15 (71.27-->71.42)。
diff --git a/configs/face_detection/README.md b/configs/face_detection/README.md
index 77c6710fe433ab61f7e527547acbb2ada89f3a81..8eed79fa49b2dfbdfc2c457db75c17031047b7b6 100644
--- a/configs/face_detection/README.md
+++ b/configs/face_detection/README.md
@@ -11,8 +11,8 @@
| 网络结构 | 输入尺寸 | 图片个数/GPU | 学习率策略 | Easy/Medium/Hard Set | 预测时延（SD855）| 模型大小(MB) | 下载 | 配置文件 |
|:------------:|:--------:|:----:|:-------:|:-------:|:---------:|:----------:|:---------:|:--------:|
-| BlazeFace | 640 | 8 | 1000e | 0.885 / 0.855 / 0.731 | - | 0.472 |[下载链接](https://paddledet.bj.bcebos.com/models/blazeface_1000e.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/develop/configs/face_detection/blazeface_1000e.yml) |
-| BlazeFace-FPN-SSH | 640 | 8 | 1000e | 0.907 / 0.883 / 0.793 | - | 0.479 |[下载链接](https://paddledet.bj.bcebos.com/models/blazeface_fpn_ssh_1000e.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/develop/configs/face_detection/blazeface_fpn_ssh_1000e.yml) |
+| BlazeFace | 640 | 8 | 1000e | 0.885 / 0.855 / 0.731 | - | 0.472 |[下载链接](https://paddledet.bj.bcebos.com/models/blazeface_1000e.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/release/2.2/configs/face_detection/blazeface_1000e.yml) |
+| BlazeFace-FPN-SSH | 640 | 8 | 1000e | 0.907 / 0.883 / 0.793 | - | 0.479 |[下载链接](https://paddledet.bj.bcebos.com/models/blazeface_fpn_ssh_1000e.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/release/2.2/configs/face_detection/blazeface_fpn_ssh_1000e.yml) |
**注意:**
- 我们使用多尺度评估策略得到`Easy/Medium/Hard Set`里的mAP。具体细节请参考[在WIDER-FACE数据集上评估](#在WIDER-FACE数据集上评估)。
diff --git a/configs/faster_rcnn/README.md b/configs/faster_rcnn/README.md
index 92a547ce4701e7aa20c269d2bc776e879d338654..1ce931a5d86f0fc8e9c77a950f265982599e7217 100644
--- a/configs/faster_rcnn/README.md
+++ b/configs/faster_rcnn/README.md
@@ -4,22 +4,22 @@
| 骨架网络 | 网络类型 | 每张GPU图片个数 | 学习率策略 |推理时间(fps) | Box AP | 下载 | 配置文件 |
| :------------------- | :------------- | :-----: | :-----: | :------------: | :-----: | :-----------------------------------------------------: | :-----: |
-| ResNet50 | Faster | 1 | 1x | ---- | 36.7 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/faster_rcnn/faster_rcnn_r50_1x_coco.yml) |
-| ResNet50-vd | Faster | 1 | 1x | ---- | 37.6 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/faster_rcnn/faster_rcnn_r50_vd_1x_coco.yml) |
-| ResNet101 | Faster | 1 | 1x | ---- | 39.0 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r101_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/faster_rcnn/faster_rcnn_r101_1x_coco.yml) |
-| ResNet34-FPN | Faster | 1 | 1x | ---- | 37.8 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r34_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/faster_rcnn/faster_rcnn_r34_fpn_1x_coco.yml) |
-| ResNet34-vd-FPN | Faster | 1 | 1x | ---- | 38.5 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r34_vd_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/faster_rcnn/faster_rcnn_r34_vd_fpn_1x_coco.yml) |
-| ResNet50-FPN | Faster | 1 | 1x | ---- | 38.4 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/faster_rcnn/faster_rcnn_r50_fpn_1x_coco.yml) |
-| ResNet50-FPN | Faster | 1 | 2x | ---- | 40.0 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_fpn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/faster_rcnn/faster_rcnn_r50_fpn_2x_coco.yml) |
-| ResNet50-vd-FPN | Faster | 1 | 1x | ---- | 39.5 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/faster_rcnn/faster_rcnn_r50_vd_fpn_1x_coco.yml) |
-| ResNet50-vd-FPN | Faster | 1 | 2x | ---- | 40.8 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_fpn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/faster_rcnn/faster_rcnn_r50_vd_fpn_2x_coco.yml) |
-| ResNet101-FPN | Faster | 1 | 2x | ---- | 41.4 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r101_fpn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/faster_rcnn/faster_rcnn_r101_fpn_2x_coco.yml) |
-| ResNet101-vd-FPN | Faster | 1 | 1x | ---- | 42.0 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r101_vd_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/faster_rcnn/faster_rcnn_r101_vd_fpn_1x_coco.yml) |
-| ResNet101-vd-FPN | Faster | 1 | 2x | ---- | 43.0 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r101_vd_fpn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/faster_rcnn/faster_rcnn_r101_vd_fpn_2x_coco.yml) |
-| ResNeXt101-vd-FPN | Faster | 1 | 1x | ---- | 43.4 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_x101_vd_64x4d_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/faster_rcnn/faster_rcnn_x101_vd_64x4d_fpn_1x_coco.yml) |
-| ResNeXt101-vd-FPN | Faster | 1 | 2x | ---- | 44.0 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_x101_vd_64x4d_fpn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/faster_rcnn/faster_rcnn_x101_vd_64x4d_fpn_2x_coco.yml) |
-| ResNet50-vd-SSLDv2-FPN | Faster | 1 | 1x | ---- | 41.4 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/faster_rcnn/faster_rcnn_r50_vd_fpn_ssld_1x_coco.yml) |
-| ResNet50-vd-SSLDv2-FPN | Faster | 1 | 2x | ---- | 42.3 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_ssld_fpn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/faster_rcnn/faster_rcnn_r50_vd_ssld_fpn_2x_coco.yml) |
+| ResNet50 | Faster | 1 | 1x | ---- | 36.7 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/faster_rcnn/faster_rcnn_r50_1x_coco.yml) |
+| ResNet50-vd | Faster | 1 | 1x | ---- | 37.6 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/faster_rcnn/faster_rcnn_r50_vd_1x_coco.yml) |
+| ResNet101 | Faster | 1 | 1x | ---- | 39.0 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r101_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/faster_rcnn/faster_rcnn_r101_1x_coco.yml) |
+| ResNet34-FPN | Faster | 1 | 1x | ---- | 37.8 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r34_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/faster_rcnn/faster_rcnn_r34_fpn_1x_coco.yml) |
+| ResNet34-vd-FPN | Faster | 1 | 1x | ---- | 38.5 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r34_vd_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/faster_rcnn/faster_rcnn_r34_vd_fpn_1x_coco.yml) |
+| ResNet50-FPN | Faster | 1 | 1x | ---- | 38.4 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/faster_rcnn/faster_rcnn_r50_fpn_1x_coco.yml) |
+| ResNet50-FPN | Faster | 1 | 2x | ---- | 40.0 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_fpn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/faster_rcnn/faster_rcnn_r50_fpn_2x_coco.yml) |
+| ResNet50-vd-FPN | Faster | 1 | 1x | ---- | 39.5 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/faster_rcnn/faster_rcnn_r50_vd_fpn_1x_coco.yml) |
+| ResNet50-vd-FPN | Faster | 1 | 2x | ---- | 40.8 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_fpn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/faster_rcnn/faster_rcnn_r50_vd_fpn_2x_coco.yml) |
+| ResNet101-FPN | Faster | 1 | 2x | ---- | 41.4 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r101_fpn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/faster_rcnn/faster_rcnn_r101_fpn_2x_coco.yml) |
+| ResNet101-vd-FPN | Faster | 1 | 1x | ---- | 42.0 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r101_vd_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/faster_rcnn/faster_rcnn_r101_vd_fpn_1x_coco.yml) |
+| ResNet101-vd-FPN | Faster | 1 | 2x | ---- | 43.0 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r101_vd_fpn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/faster_rcnn/faster_rcnn_r101_vd_fpn_2x_coco.yml) |
+| ResNeXt101-vd-FPN | Faster | 1 | 1x | ---- | 43.4 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_x101_vd_64x4d_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/faster_rcnn/faster_rcnn_x101_vd_64x4d_fpn_1x_coco.yml) |
+| ResNeXt101-vd-FPN | Faster | 1 | 2x | ---- | 44.0 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_x101_vd_64x4d_fpn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/faster_rcnn/faster_rcnn_x101_vd_64x4d_fpn_2x_coco.yml) |
+| ResNet50-vd-SSLDv2-FPN | Faster | 1 | 1x | ---- | 41.4 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/faster_rcnn/faster_rcnn_r50_vd_fpn_ssld_1x_coco.yml) |
+| ResNet50-vd-SSLDv2-FPN | Faster | 1 | 2x | ---- | 42.3 | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_ssld_fpn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/faster_rcnn/faster_rcnn_r50_vd_ssld_fpn_2x_coco.yml) |
## Citations
diff --git a/configs/fcos/README.md b/configs/fcos/README.md
index cdd4334235a30283ac9b8c9902098fdc94364c11..15110f0080b5d2f5b3dce5195879413320ab4b9c 100644
--- a/configs/fcos/README.md
+++ b/configs/fcos/README.md
@@ -12,9 +12,9 @@ FCOS (Fully Convolutional One-Stage Object Detection) is a fast anchor-free obje
| Backbone | Model | images/GPU | lr schedule |FPS | Box AP | download | config |
| :-------------- | :------------- | :-----: | :-----: | :------------: | :-----: | :-----------------------------------------------------: | :-----: |
-| ResNet50-FPN | FCOS | 2 | 1x | ---- | 39.6 | [download](https://paddledet.bj.bcebos.com/models/fcos_r50_fpn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/fcos/fcos_r50_fpn_1x_coco.yml) |
-| ResNet50-FPN | FCOS+DCN | 2 | 1x | ---- | 44.3 | [download](https://paddledet.bj.bcebos.com/models/fcos_dcn_r50_fpn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/fcos/fcos_dcn_r50_fpn_1x_coco.yml) |
-| ResNet50-FPN | FCOS+multiscale_train | 2 | 2x | ---- | 41.8 | [download](https://paddledet.bj.bcebos.com/models/fcos_r50_fpn_multiscale_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/fcos/fcos_r50_fpn_multiscale_2x_coco.yml) |
+| ResNet50-FPN | FCOS | 2 | 1x | ---- | 39.6 | [download](https://paddledet.bj.bcebos.com/models/fcos_r50_fpn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/fcos/fcos_r50_fpn_1x_coco.yml) |
+| ResNet50-FPN | FCOS+DCN | 2 | 1x | ---- | 44.3 | [download](https://paddledet.bj.bcebos.com/models/fcos_dcn_r50_fpn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/fcos/fcos_dcn_r50_fpn_1x_coco.yml) |
+| ResNet50-FPN | FCOS+multiscale_train | 2 | 2x | ---- | 41.8 | [download](https://paddledet.bj.bcebos.com/models/fcos_r50_fpn_multiscale_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/fcos/fcos_r50_fpn_multiscale_2x_coco.yml) |
**Notes:**
diff --git a/configs/gn/README.md b/configs/gn/README.md
index ec10831f9e9383d1a16ffc4c3088e283da492ba9..1941787a8ab053d467f6ce8312432818b21ca778 100644
--- a/configs/gn/README.md
+++ b/configs/gn/README.md
@@ -4,10 +4,10 @@
| 骨架网络 | 网络类型 | 每张GPU图片个数 | 学习率策略 |推理时间(fps)| Box AP | Mask AP | 下载 | 配置文件 |
| :------------- | :------------- | :-----------: | :------: | :--------: |:-----: | :-----: | :----: | :----: |
-| ResNet50-FPN | Faster | 1 | 2x | - | 41.9 | - | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_fpn_gn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/gn/faster_rcnn_r50_fpn_gn_2x_coco.yml) |
-| ResNet50-FPN | Mask | 1 | 2x | - | 42.3 | 38.4 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_fpn_gn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/gn/mask_rcnn_r50_fpn_gn_2x_coco.yml) |
-| ResNet50-FPN | Cascade Faster | 1 | 2x | - | 44.6 | - | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_rcnn_r50_fpn_gn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/gn/cascade_rcnn_r50_fpn_gn_2x_coco.yml) |
-| ResNet50-FPN | Cacade Mask | 1 | 2x | - | 45.0 | 39.3 | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_mask_rcnn_r50_fpn_gn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/gn/cascade_mask_rcnn_r50_fpn_gn_2x_coco.yml) |
+| ResNet50-FPN | Faster | 1 | 2x | - | 41.9 | - | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_fpn_gn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/gn/faster_rcnn_r50_fpn_gn_2x_coco.yml) |
+| ResNet50-FPN | Mask | 1 | 2x | - | 42.3 | 38.4 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_fpn_gn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/gn/mask_rcnn_r50_fpn_gn_2x_coco.yml) |
+| ResNet50-FPN | Cascade Faster | 1 | 2x | - | 44.6 | - | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_rcnn_r50_fpn_gn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/gn/cascade_rcnn_r50_fpn_gn_2x_coco.yml) |
+| ResNet50-FPN | Cacade Mask | 1 | 2x | - | 45.0 | 39.3 | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_mask_rcnn_r50_fpn_gn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/gn/cascade_mask_rcnn_r50_fpn_gn_2x_coco.yml) |
**注意：** Faster R-CNN baseline仅使用 `2fc` head，而此处使用[`4conv1fc` head](https://arxiv.org/abs/1803.08494)（4层conv之间使用GN），并且FPN也使用GN，而对于Mask R-CNN是在mask head的4层conv之间也使用GN。
diff --git a/configs/hrnet/README.md b/configs/hrnet/README.md
index 1c6fec7bd7c2f498f0a6d38db47b4c091df08820..2f2f2ebe172265195829c3369a21fa9cf981620d 100644
--- a/configs/hrnet/README.md
+++ b/configs/hrnet/README.md
@@ -30,5 +30,5 @@
| Backbone | Type | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download | Configs |
| :---------------------- | :------------- | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: | :-----: |
-| HRNetV2p_W18 | Faster | 1 | 1x | - | 36.8 | - | [model](https://paddledet.bj.bcebos.com/models/faster_rcnn_hrnetv2p_w18_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/hrnet/faster_rcnn_hrnetv2p_w18_1x_coco.yml) |
-| HRNetV2p_W18 | Faster | 1 | 2x | - | 39.0 | - | [model](https://paddledet.bj.bcebos.com/models/faster_rcnn_hrnetv2p_w18_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/hrnet/faster_rcnn_hrnetv2p_w18_2x_coco.yml) |
+| HRNetV2p_W18 | Faster | 1 | 1x | - | 36.8 | - | [model](https://paddledet.bj.bcebos.com/models/faster_rcnn_hrnetv2p_w18_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/hrnet/faster_rcnn_hrnetv2p_w18_1x_coco.yml) |
+| HRNetV2p_W18 | Faster | 1 | 2x | - | 39.0 | - | [model](https://paddledet.bj.bcebos.com/models/faster_rcnn_hrnetv2p_w18_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/hrnet/faster_rcnn_hrnetv2p_w18_2x_coco.yml) |
diff --git a/configs/keypoint/README.md b/configs/keypoint/README.md
index 3a3cb3720f6a48ad18e44836f988a0b53c0e0843..e61550e1c660047c6831ae289a8e0476c949551a 100644
--- a/configs/keypoint/README.md
+++ b/configs/keypoint/README.md
@@ -35,7 +35,7 @@ MPII数据集
### 1、环境安装
- 请参考PaddleDetection [安装文档](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/docs/tutorials/INSTALL_cn.md)正确安装PaddlePaddle和PaddleDetection即可。
+ 请参考PaddleDetection [安装文档](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.2/docs/tutorials/INSTALL_cn.md)正确安装PaddlePaddle和PaddleDetection即可。
### 2、数据准备
diff --git a/configs/mask_rcnn/README.md b/configs/mask_rcnn/README.md
index 020fe99f78e5d1c84c47929381090c6311694529..02f3f2ff449b03d9822f9038c9be939aebdbe3bf 100644
--- a/configs/mask_rcnn/README.md
+++ b/configs/mask_rcnn/README.md
@@ -4,18 +4,18 @@
| 骨架网络 | 网络类型 | 每张GPU图片个数 | 学习率策略 |推理时间(fps) | Box AP | Mask AP | 下载 | 配置文件 |
| :------------------- | :------------| :-----: | :-----: | :------------: | :-----: | :-----: | :-----------------------------------------------------: | :-----: |
-| ResNet50 | Mask | 1 | 1x | ---- | 37.4 | 32.8 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_r50_1x_coco.yml) |
-| ResNet50 | Mask | 1 | 2x | ---- | 39.7 | 34.5 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_r50_2x_coco.yml) |
-| ResNet50-FPN | Mask | 1 | 1x | ---- | 39.2 | 35.6 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_r50_fpn_1x_coco.yml) |
-| ResNet50-FPN | Mask | 1 | 2x | ---- | 40.5 | 36.7 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_fpn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_r50_fpn_2x_coco.yml) |
-| ResNet50-vd-FPN | Mask | 1 | 1x | ---- | 40.3 | 36.4 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_vd_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_r50_vd_fpn_1x_coco.yml) |
-| ResNet50-vd-FPN | Mask | 1 | 2x | ---- | 41.4 | 37.5 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_vd_fpn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_r50_vd_fpn_2x_coco.yml) |
-| ResNet101-FPN | Mask | 1 | 1x | ---- | 40.6 | 36.6 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r101_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_r101_fpn_1x_coco.yml) |
-| ResNet101-vd-FPN | Mask | 1 | 1x | ---- | 42.4 | 38.1 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r101_vd_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_r101_vd_fpn_1x_coco.yml) |
-| ResNeXt101-vd-FPN | Mask | 1 | 1x | ---- | 44.0 | 39.5 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_x101_vd_64x4d_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_x101_vd_64x4d_fpn_1x_coco.yml) |
-| ResNeXt101-vd-FPN | Mask | 1 | 2x | ---- | 44.6 | 39.8 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_x101_vd_64x4d_fpn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_x101_vd_64x4d_fpn_2x_coco.yml) |
-| ResNet50-vd-SSLDv2-FPN | Mask | 1 | 1x | ---- | 42.0 | 38.2 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_r50_vd_fpn_ssld_1x_coco.yml) |
-| ResNet50-vd-SSLDv2-FPN | Mask | 1 | 2x | ---- | 42.7 | 38.9 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_r50_vd_fpn_ssld_2x_coco.yml) |
+| ResNet50 | Mask | 1 | 1x | ---- | 37.4 | 32.8 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mask_rcnn/mask_rcnn_r50_1x_coco.yml) |
+| ResNet50 | Mask | 1 | 2x | ---- | 39.7 | 34.5 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mask_rcnn/mask_rcnn_r50_2x_coco.yml) |
+| ResNet50-FPN | Mask | 1 | 1x | ---- | 39.2 | 35.6 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mask_rcnn/mask_rcnn_r50_fpn_1x_coco.yml) |
+| ResNet50-FPN | Mask | 1 | 2x | ---- | 40.5 | 36.7 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_fpn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mask_rcnn/mask_rcnn_r50_fpn_2x_coco.yml) |
+| ResNet50-vd-FPN | Mask | 1 | 1x | ---- | 40.3 | 36.4 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_vd_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mask_rcnn/mask_rcnn_r50_vd_fpn_1x_coco.yml) |
+| ResNet50-vd-FPN | Mask | 1 | 2x | ---- | 41.4 | 37.5 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_vd_fpn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mask_rcnn/mask_rcnn_r50_vd_fpn_2x_coco.yml) |
+| ResNet101-FPN | Mask | 1 | 1x | ---- | 40.6 | 36.6 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r101_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mask_rcnn/mask_rcnn_r101_fpn_1x_coco.yml) |
+| ResNet101-vd-FPN | Mask | 1 | 1x | ---- | 42.4 | 38.1 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r101_vd_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mask_rcnn/mask_rcnn_r101_vd_fpn_1x_coco.yml) |
+| ResNeXt101-vd-FPN | Mask | 1 | 1x | ---- | 44.0 | 39.5 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_x101_vd_64x4d_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mask_rcnn/mask_rcnn_x101_vd_64x4d_fpn_1x_coco.yml) |
+| ResNeXt101-vd-FPN | Mask | 1 | 2x | ---- | 44.6 | 39.8 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_x101_vd_64x4d_fpn_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mask_rcnn/mask_rcnn_x101_vd_64x4d_fpn_2x_coco.yml) |
+| ResNet50-vd-SSLDv2-FPN | Mask | 1 | 1x | ---- | 42.0 | 38.2 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mask_rcnn/mask_rcnn_r50_vd_fpn_ssld_1x_coco.yml) |
+| ResNet50-vd-SSLDv2-FPN | Mask | 1 | 2x | ---- | 42.7 | 38.9 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mask_rcnn/mask_rcnn_r50_vd_fpn_ssld_2x_coco.yml) |
## Citations
diff --git a/configs/mot/README.md b/configs/mot/README.md
index b33c3d7adf38f08094683baf31f439630b72178d..06c077dc1c9b841b5c88ac7d187334a94526244f 100644
--- a/configs/mot/README.md
+++ b/configs/mot/README.md
@@ -49,15 +49,15 @@ pip install -r requirements.txt
| backbone | input shape | MOTA | IDF1 | IDS | FP | FN | FPS | det result/model |ReID model| config |
| :---------| :------- | :----: | :----: | :--: | :----: | :---: | :---: | :---: | :---: | :---: |
-| ResNet-101 | 1088x608 | 72.2 | 60.5 | 998 | 8054 | 21644 | - | [det result](https://dataset.bj.bcebos.com/mot/det_results_dir.zip) |[ReID model](https://paddledet.bj.bcebos.com/models/mot/deepsort_pcb_pyramid_r101.pdparams)|[config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/deepsort/deepsort_pcb_pyramid_r101.yml) |
-| ResNet-101 | 1088x608 | 68.3 | 56.5 | 1722 | 17337 | 15890 | - | [det model](https://paddledet.bj.bcebos.com/models/mot/jde_yolov3_darknet53_30e_1088x608.pdparams) |[ReID model](https://paddledet.bj.bcebos.com/models/mot/deepsort_pcb_pyramid_r101.pdparams)|[config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/deepsort/deepsort_pcb_pyramid_r101.yml) |
+| ResNet-101 | 1088x608 | 72.2 | 60.5 | 998 | 8054 | 21644 | - | [det result](https://dataset.bj.bcebos.com/mot/det_results_dir.zip) |[ReID model](https://paddledet.bj.bcebos.com/models/mot/deepsort_pcb_pyramid_r101.pdparams)|[config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/deepsort/deepsort_pcb_pyramid_r101.yml) |
+| ResNet-101 | 1088x608 | 68.3 | 56.5 | 1722 | 17337 | 15890 | - | [det model](https://paddledet.bj.bcebos.com/models/mot/jde_yolov3_darknet53_30e_1088x608.pdparams) |[ReID model](https://paddledet.bj.bcebos.com/models/mot/deepsort_pcb_pyramid_r101.pdparams)|[config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/deepsort/deepsort_pcb_pyramid_r101.yml) |
### DeepSORT Results on MOT-16 Test Set
| backbone | input shape | MOTA | IDF1 | IDS | FP | FN | FPS | det result/model |ReID model| config |
| :---------| :------- | :----: | :----: | :--: | :----: | :---: | :---: | :---: | :---: | :---: |
-| ResNet-101 | 1088x608 | 64.1 | 53.0 | 1024 | 12457 | 51919 | - |[det result](https://dataset.bj.bcebos.com/mot/det_results_dir.zip) |[ReID model](https://paddledet.bj.bcebos.com/models/mot/deepsort_pcb_pyramid_r101.pdparams)|[config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/deepsort/deepsort_pcb_pyramid_r101.yml) |
-| ResNet-101 | 1088x608 | 61.2 | 48.5 | 1799 | 25796 | 43232 | - | [det model](https://paddledet.bj.bcebos.com/models/mot/jde_yolov3_darknet53_30e_1088x608.pdparams) |[ReID model](https://paddledet.bj.bcebos.com/models/mot/deepsort_pcb_pyramid_r101.pdparams)|[config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/deepsort/deepsort_pcb_pyramid_r101.yml) |
+| ResNet-101 | 1088x608 | 64.1 | 53.0 | 1024 | 12457 | 51919 | - |[det result](https://dataset.bj.bcebos.com/mot/det_results_dir.zip) |[ReID model](https://paddledet.bj.bcebos.com/models/mot/deepsort_pcb_pyramid_r101.pdparams)|[config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/deepsort/deepsort_pcb_pyramid_r101.yml) |
+| ResNet-101 | 1088x608 | 61.2 | 48.5 | 1799 | 25796 | 43232 | - | [det model](https://paddledet.bj.bcebos.com/models/mot/jde_yolov3_darknet53_30e_1088x608.pdparams) |[ReID model](https://paddledet.bj.bcebos.com/models/mot/deepsort_pcb_pyramid_r101.pdparams)|[config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/deepsort/deepsort_pcb_pyramid_r101.yml) |
**Notes:**
DeepSORT does not need to train on MOT dataset, only used for evaluation. Now it supports two evaluation methods.
@@ -94,19 +94,19 @@ If you use a stronger detection model, you can get better results. Each txt is t
| backbone | input shape | MOTA | IDF1 | IDS | FP | FN | FPS | download | config |
| :----------------- | :------- | :----: | :----: | :---: | :----: | :---: | :---: | :---: | :---: |
-| DarkNet53 | 1088x608 | 72.0 | 66.9 | 1397 | 7274 | 22209 | - |[model](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_1088x608.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/jde/jde_darknet53_30e_1088x608.yml) |
-| DarkNet53 | 864x480 | 69.1 | 64.7 | 1539 | 7544 | 25046 | - |[model](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_864x480.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/jde/jde_darknet53_30e_864x480.yml) |
-| DarkNet53 | 576x320 | 63.7 | 64.4 | 1310 | 6782 | 31964 | - |[model](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_576x320.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/jde/jde_darknet53_30e_576x320.yml) |
+| DarkNet53 | 1088x608 | 72.0 | 66.9 | 1397 | 7274 | 22209 | - |[model](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_1088x608.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/jde/jde_darknet53_30e_1088x608.yml) |
+| DarkNet53 | 864x480 | 69.1 | 64.7 | 1539 | 7544 | 25046 | - |[model](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_864x480.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/jde/jde_darknet53_30e_864x480.yml) |
+| DarkNet53 | 576x320 | 63.7 | 64.4 | 1310 | 6782 | 31964 | - |[model](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_576x320.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/jde/jde_darknet53_30e_576x320.yml) |
### JDE Results on MOT-16 Test Set
| backbone | input shape | MOTA | IDF1 | IDS | FP | FN | FPS | download | config |
| :----------------- | :------- | :----: | :----: | :---: | :----: | :---: | :---: | :---: | :---: |
| DarkNet53(paper) | 1088x608 | 64.4 | 55.8 | 1544 | - | - | - | - | - |
-| DarkNet53 | 1088x608 | 64.6 | 58.5 | 1864 | 10550 | 52088 | - |[model](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_1088x608.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/jde/jde_darknet53_30e_1088x608.yml) |
+| DarkNet53 | 1088x608 | 64.6 | 58.5 | 1864 | 10550 | 52088 | - |[model](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_1088x608.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/jde/jde_darknet53_30e_1088x608.yml) |
| DarkNet53(paper) | 864x480 | 62.1 | 56.9 | 1608 | - | - | - | - | - |
-| DarkNet53 | 864x480 | 63.2 | 57.7 | 1966 | 10070 | 55081 | - |[model](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_864x480.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/jde/jde_darknet53_30e_864x480.yml) |
-| DarkNet53 | 576x320 | 59.1 | 56.4 | 1911 | 10923 | 61789 | - |[model](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_576x320.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/jde/jde_darknet53_30e_576x320.yml) |
+| DarkNet53 | 864x480 | 63.2 | 57.7 | 1966 | 10070 | 55081 | - |[model](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_864x480.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/jde/jde_darknet53_30e_864x480.yml) |
+| DarkNet53 | 576x320 | 59.1 | 56.4 | 1911 | 10923 | 61789 | - |[model](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_576x320.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/jde/jde_darknet53_30e_576x320.yml) |
**Notes:**
JDE used 8 GPUs for training and mini-batch size as 4 on each GPU, and trained for 30 epoches.
@@ -117,7 +117,7 @@ If you use a stronger detection model, you can get better results. Each txt is t
| backbone | input shape | MOTA | IDF1 | IDS | FP | FN | FPS | download | config |
| :--------------| :------- | :----: | :----: | :----: | :----: | :----: | :------: | :----: |:-----: |
| DLA-34(paper) | 1088x608 | 83.3 | 81.9 | 544 | 3822 | 14095 | - | - | - |
-| DLA-34 | 1088x608 | 83.7 | 83.3 | 435 | 3829 | 13764 | - | [model](https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/fairmot/fairmot_dla34_30e_1088x608.yml) |
+| DLA-34 | 1088x608 | 83.7 | 83.3 | 435 | 3829 | 13764 | - | [model](https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/fairmot/fairmot_dla34_30e_1088x608.yml) |
### FairMOT Results on MOT-16 Test Set
@@ -125,7 +125,7 @@ If you use a stronger detection model, you can get better results. Each txt is t
| backbone | input shape | MOTA | IDF1 | IDS | FP | FN | FPS | download | config |
| :--------------| :------- | :----: | :----: | :----: | :----: | :----: | :------: | :----: |:-----: |
| DLA-34(paper) | 1088x608 | 74.9 | 72.8 | 1074 | - | - | 25.9 | - | - |
-| DLA-34 | 1088x608 | 74.8 | 74.4 | 930 | 7038 | 37994 | - | [model](https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/fairmot/fairmot_dla34_30e_1088x608.yml) |
+| DLA-34 | 1088x608 | 74.8 | 74.4 | 930 | 7038 | 37994 | - | [model](https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/fairmot/fairmot_dla34_30e_1088x608.yml) |
**Notes:**
FairMOT used 8 GPUs for training and mini-batch size as 6 on each GPU, and trained for 30 epoches.
diff --git a/configs/mot/README_cn.md b/configs/mot/README_cn.md
index b5ab66c073d4297909dc3e699d35049298de7838..167f589e89c56532ee941f4383dea5aa9b333a96 100644
--- a/configs/mot/README_cn.md
+++ b/configs/mot/README_cn.md
@@ -48,15 +48,15 @@ pip install -r requirements.txt
| 骨干网络 | 输入尺寸 | MOTA | IDF1 | IDS | FP | FN | FPS | 检测结果或模型 | ReID模型 |配置文件 |
| :---------| :------- | :----: | :----: | :--: | :----: | :---: | :---: | :-----:| :-----: | :-----: |
-| ResNet-101 | 1088x608 | 72.2 | 60.5 | 998 | 8054 | 21644 | - | [检测结果](https://dataset.bj.bcebos.com/mot/det_results_dir.zip) |[ReID模型](https://paddledet.bj.bcebos.com/models/mot/deepsort_pcb_pyramid_r101.pdparams)|[配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/deepsort/deepsort_pcb_pyramid_r101.yml) |
-| ResNet-101 | 1088x608 | 68.3 | 56.5 | 1722 | 17337 | 15890 | - | [检测模型](https://paddledet.bj.bcebos.com/models/mot/jde_yolov3_darknet53_30e_1088x608.pdparams) |[ReID模型](https://paddledet.bj.bcebos.com/models/mot/deepsort_pcb_pyramid_r101.pdparams)|[配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/deepsort/deepsort_pcb_pyramid_r101.yml) |
+| ResNet-101 | 1088x608 | 72.2 | 60.5 | 998 | 8054 | 21644 | - | [检测结果](https://dataset.bj.bcebos.com/mot/det_results_dir.zip) |[ReID模型](https://paddledet.bj.bcebos.com/models/mot/deepsort_pcb_pyramid_r101.pdparams)|[配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/deepsort/deepsort_pcb_pyramid_r101.yml) |
+| ResNet-101 | 1088x608 | 68.3 | 56.5 | 1722 | 17337 | 15890 | - | [检测模型](https://paddledet.bj.bcebos.com/models/mot/jde_yolov3_darknet53_30e_1088x608.pdparams) |[ReID模型](https://paddledet.bj.bcebos.com/models/mot/deepsort_pcb_pyramid_r101.pdparams)|[配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/deepsort/deepsort_pcb_pyramid_r101.yml) |
### DeepSORT在MOT-16 Test Set上结果
| 骨干网络 | 输入尺寸 | MOTA | IDF1 | IDS | FP | FN | FPS | 检测结果或模型 | ReID模型 |配置文件 |
| :---------| :------- | :----: | :----: | :--: | :----: | :---: | :---: | :-----: | :-----: |:-----: |
-| ResNet-101 | 1088x608 | 64.1 | 53.0 | 1024 | 12457 | 51919 | - | [检测结果](https://dataset.bj.bcebos.com/mot/det_results_dir.zip) | [ReID模型](https://paddledet.bj.bcebos.com/models/mot/deepsort_pcb_pyramid_r101.pdparams)|[配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/deepsort/deepsort_pcb_pyramid_r101.yml) |
-| ResNet-101 | 1088x608 | 61.2 | 48.5 | 1799 | 25796 | 43232 | - | [检测模型](https://paddledet.bj.bcebos.com/models/mot/jde_yolov3_darknet53_30e_1088x608.pdparams) |[ReID模型](https://paddledet.bj.bcebos.com/models/mot/deepsort_pcb_pyramid_r101.pdparams)|[配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/deepsort/deepsort_pcb_pyramid_r101.yml) |
+| ResNet-101 | 1088x608 | 64.1 | 53.0 | 1024 | 12457 | 51919 | - | [检测结果](https://dataset.bj.bcebos.com/mot/det_results_dir.zip) | [ReID模型](https://paddledet.bj.bcebos.com/models/mot/deepsort_pcb_pyramid_r101.pdparams)|[配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/deepsort/deepsort_pcb_pyramid_r101.yml) |
+| ResNet-101 | 1088x608 | 61.2 | 48.5 | 1799 | 25796 | 43232 | - | [检测模型](https://paddledet.bj.bcebos.com/models/mot/jde_yolov3_darknet53_30e_1088x608.pdparams) |[ReID模型](https://paddledet.bj.bcebos.com/models/mot/deepsort_pcb_pyramid_r101.pdparams)|[配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/deepsort/deepsort_pcb_pyramid_r101.yml) |
**注意:**
@@ -94,9 +94,9 @@ wget https://dataset.bj.bcebos.com/mot/det_results_dir.zip
| 骨干网络 | 输入尺寸 | MOTA | IDF1 | IDS | FP | FN | FPS | 下载链接 | 配置文件 |
| :----------------- | :------- | :----: | :----: | :---: | :----: | :---: | :---: | :---: | :---: |
-| DarkNet53 | 1088x608 | 72.0 | 66.9 | 1397 | 7274 | 22209 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_1088x608.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/jde/jde_darknet53_30e_1088x608.yml) |
-| DarkNet53 | 864x480 | 69.1 | 64.7 | 1539 | 7544 | 25046 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_864x480.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/jde/jde_darknet53_30e_864x480.yml) |
-| DarkNet53 | 576x320 | 63.7 | 64.4 | 1310 | 6782 | 31964 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_576x320.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/jde/jde_darknet53_30e_576x320.yml) |
+| DarkNet53 | 1088x608 | 72.0 | 66.9 | 1397 | 7274 | 22209 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_1088x608.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/jde/jde_darknet53_30e_1088x608.yml) |
+| DarkNet53 | 864x480 | 69.1 | 64.7 | 1539 | 7544 | 25046 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_864x480.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/jde/jde_darknet53_30e_864x480.yml) |
+| DarkNet53 | 576x320 | 63.7 | 64.4 | 1310 | 6782 | 31964 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_576x320.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/jde/jde_darknet53_30e_576x320.yml) |
### JDE在MOT-16 Test Set上结果
@@ -104,10 +104,10 @@ wget https://dataset.bj.bcebos.com/mot/det_results_dir.zip
| 骨干网络 | 输入尺寸 | MOTA | IDF1 | IDS | FP | FN | FPS | 下载链接 | 配置文件 |
| :----------------- | :------- | :----: | :----: | :---: | :----: | :---: | :---: | :---: | :---: |
| DarkNet53(paper) | 1088x608 | 64.4 | 55.8 | 1544 | - | - | - | - | - |
-| DarkNet53 | 1088x608 | 64.6 | 58.5 | 1864 | 10550 | 52088 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_1088x608.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/jde/jde_darknet53_30e_1088x608.yml) |
+| DarkNet53 | 1088x608 | 64.6 | 58.5 | 1864 | 10550 | 52088 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_1088x608.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/jde/jde_darknet53_30e_1088x608.yml) |
| DarkNet53(paper) | 864x480 | 62.1 | 56.9 | 1608 | - | - | - | - | - |
-| DarkNet53 | 864x480 | 63.2 | 57.7 | 1966 | 10070 | 55081 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_864x480.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/jde/jde_darknet53_30e_864x480.yml) |
-| DarkNet53 | 576x320 | 59.1 | 56.4 | 1911 | 10923 | 61789 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_576x320.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/jde/jde_darknet53_30e_576x320.yml) |
+| DarkNet53 | 864x480 | 63.2 | 57.7 | 1966 | 10070 | 55081 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_864x480.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/jde/jde_darknet53_30e_864x480.yml) |
+| DarkNet53 | 576x320 | 59.1 | 56.4 | 1911 | 10923 | 61789 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_576x320.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/jde/jde_darknet53_30e_576x320.yml) |
**注意:**
JDE使用8个GPU进行训练，每个GPU上batch size为4，训练了30个epoch。
@@ -118,14 +118,14 @@ wget https://dataset.bj.bcebos.com/mot/det_results_dir.zip
| 骨干网络 | 输入尺寸 | MOTA | IDF1 | IDS | FP | FN | FPS | 下载链接 | 配置文件 |
| :--------------| :------- | :----: | :----: | :---: | :----: | :---: | :------: | :----: |:----: |
| DLA-34(paper) | 1088x608 | 83.3 | 81.9 | 544 | 3822 | 14095 | - | - | - |
-| DLA-34 | 1088x608 | 83.7 | 83.3 | 435 | 3829 | 13764 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/fairmot/fairmot_dla34_30e_1088x608.yml) |
+| DLA-34 | 1088x608 | 83.7 | 83.3 | 435 | 3829 | 13764 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/fairmot/fairmot_dla34_30e_1088x608.yml) |
### FairMOT在MOT-16 Test Set上结果
| 骨干网络 | 输入尺寸 | MOTA | IDF1 | IDS | FP | FN | FPS | 下载链接 | 配置文件 |
| :--------------| :------- | :----: | :----: | :----: | :----: | :----: |:-------: | :----: | :----: |
| DLA-34(paper) | 1088x608 | 74.9 | 72.8 | 1074 | - | - | 25.9 | - | - |
-| DLA-34 | 1088x608 | 74.8 | 74.4 | 930 | 7038 | 37994 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/fairmot/fairmot_dla34_30e_1088x608.yml) |
+| DLA-34 | 1088x608 | 74.8 | 74.4 | 930 | 7038 | 37994 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/fairmot/fairmot_dla34_30e_1088x608.yml) |
**注意:**
FairMOT使用8个GPU进行训练，每个GPU上batch size为6，训练30个epoch。
diff --git a/configs/mot/deepsort/README.md b/configs/mot/deepsort/README.md
index b479849387094fb24052d3ac08ac09f4013ec0fa..ea040bce35f3c57f8f9707e2a4fd995078ce28af 100644
--- a/configs/mot/deepsort/README.md
+++ b/configs/mot/deepsort/README.md
@@ -17,15 +17,15 @@ English | [简体中文](README_cn.md)
| backbone | input shape | MOTA | IDF1 | IDS | FP | FN | FPS | det result/model |ReID model| config |
| :---------| :------- | :----: | :----: | :--: | :----: | :---: | :---: | :---: | :---: | :---: |
-| ResNet-101 | 1088x608 | 72.2 | 60.5 | 998 | 8054 | 21644 | - | [det result](https://dataset.bj.bcebos.com/mot/det_results_dir.zip) |[ReID model](https://paddledet.bj.bcebos.com/models/mot/deepsort_pcb_pyramid_r101.pdparams)|[config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/deepsort/deepsort_pcb_pyramid_r101.yml) |
-| ResNet-101 | 1088x608 | 68.3 | 56.5 | 1722 | 17337 | 15890 | - | [det model](https://paddledet.bj.bcebos.com/models/mot/jde_yolov3_darknet53_30e_1088x608.pdparams) |[ReID model](https://paddledet.bj.bcebos.com/models/mot/deepsort_pcb_pyramid_r101.pdparams)|[config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/deepsort/deepsort_pcb_pyramid_r101.yml) |
+| ResNet-101 | 1088x608 | 72.2 | 60.5 | 998 | 8054 | 21644 | - | [det result](https://dataset.bj.bcebos.com/mot/det_results_dir.zip) |[ReID model](https://paddledet.bj.bcebos.com/models/mot/deepsort_pcb_pyramid_r101.pdparams)|[config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/deepsort/deepsort_pcb_pyramid_r101.yml) |
+| ResNet-101 | 1088x608 | 68.3 | 56.5 | 1722 | 17337 | 15890 | - | [det model](https://paddledet.bj.bcebos.com/models/mot/jde_yolov3_darknet53_30e_1088x608.pdparams) |[ReID model](https://paddledet.bj.bcebos.com/models/mot/deepsort_pcb_pyramid_r101.pdparams)|[config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/deepsort/deepsort_pcb_pyramid_r101.yml) |
### DeepSORT Results on MOT-16 Test Set
| backbone | input shape | MOTA | IDF1 | IDS | FP | FN | FPS | det result/model |ReID model| config |
| :---------| :------- | :----: | :----: | :--: | :----: | :---: | :---: | :---: | :---: | :---: |
-| ResNet-101 | 1088x608 | 64.1 | 53.0 | 1024 | 12457 | 51919 | - |[det result](https://dataset.bj.bcebos.com/mot/det_results_dir.zip) |[ReID model](https://paddledet.bj.bcebos.com/models/mot/deepsort_pcb_pyramid_r101.pdparams)|[config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/deepsort/deepsort_pcb_pyramid_r101.yml) |
-| ResNet-101 | 1088x608 | 61.2 | 48.5 | 1799 | 25796 | 43232 | - | [det model](https://paddledet.bj.bcebos.com/models/mot/jde_yolov3_darknet53_30e_1088x608.pdparams) |[ReID model](https://paddledet.bj.bcebos.com/models/mot/deepsort_pcb_pyramid_r101.pdparams)|[config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/deepsort/deepsort_pcb_pyramid_r101.yml) |
+| ResNet-101 | 1088x608 | 64.1 | 53.0 | 1024 | 12457 | 51919 | - |[det result](https://dataset.bj.bcebos.com/mot/det_results_dir.zip) |[ReID model](https://paddledet.bj.bcebos.com/models/mot/deepsort_pcb_pyramid_r101.pdparams)|[config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/deepsort/deepsort_pcb_pyramid_r101.yml) |
+| ResNet-101 | 1088x608 | 61.2 | 48.5 | 1799 | 25796 | 43232 | - | [det model](https://paddledet.bj.bcebos.com/models/mot/jde_yolov3_darknet53_30e_1088x608.pdparams) |[ReID model](https://paddledet.bj.bcebos.com/models/mot/deepsort_pcb_pyramid_r101.pdparams)|[config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/deepsort/deepsort_pcb_pyramid_r101.yml) |
**Notes:**
DeepSORT does not need to train on MOT dataset, only used for evaluation. Now it supports two evaluation methods.
diff --git a/configs/mot/deepsort/README_cn.md b/configs/mot/deepsort/README_cn.md
index 82e128471f2df7355232c00136e05d9868545e05..899acf8f1e489b55bf99931a1944811d96390ba5 100644
--- a/configs/mot/deepsort/README_cn.md
+++ b/configs/mot/deepsort/README_cn.md
@@ -17,15 +17,15 @@
| 骨干网络 | 输入尺寸 | MOTA | IDF1 | IDS | FP | FN | FPS | 检测结果或模型 | ReID模型 |配置文件 |
| :---------| :------- | :----: | :----: | :--: | :----: | :---: | :---: | :-----:| :-----: | :-----: |
-| ResNet-101 | 1088x608 | 72.2 | 60.5 | 998 | 8054 | 21644 | - | [检测结果](https://dataset.bj.bcebos.com/mot/det_results_dir.zip) |[ReID模型](https://paddledet.bj.bcebos.com/models/mot/deepsort_pcb_pyramid_r101.pdparams)|[配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/deepsort/deepsort_pcb_pyramid_r101.yml) |
-| ResNet-101 | 1088x608 | 68.3 | 56.5 | 1722 | 17337 | 15890 | - | [检测模型](https://paddledet.bj.bcebos.com/models/mot/jde_yolov3_darknet53_30e_1088x608.pdparams) |[ReID模型](https://paddledet.bj.bcebos.com/models/mot/deepsort_pcb_pyramid_r101.pdparams)|[配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/deepsort/deepsort_pcb_pyramid_r101.yml) |
+| ResNet-101 | 1088x608 | 72.2 | 60.5 | 998 | 8054 | 21644 | - | [检测结果](https://dataset.bj.bcebos.com/mot/det_results_dir.zip) |[ReID模型](https://paddledet.bj.bcebos.com/models/mot/deepsort_pcb_pyramid_r101.pdparams)|[配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/deepsort/deepsort_pcb_pyramid_r101.yml) |
+| ResNet-101 | 1088x608 | 68.3 | 56.5 | 1722 | 17337 | 15890 | - | [检测模型](https://paddledet.bj.bcebos.com/models/mot/jde_yolov3_darknet53_30e_1088x608.pdparams) |[ReID模型](https://paddledet.bj.bcebos.com/models/mot/deepsort_pcb_pyramid_r101.pdparams)|[配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/deepsort/deepsort_pcb_pyramid_r101.yml) |
### DeepSORT在MOT-16 Test Set上结果
| 骨干网络 | 输入尺寸 | MOTA | IDF1 | IDS | FP | FN | FPS | 检测结果或模型 | ReID模型 |配置文件 |
| :---------| :------- | :----: | :----: | :--: | :----: | :---: | :---: | :-----: | :-----: |:-----: |
-| ResNet-101 | 1088x608 | 64.1 | 53.0 | 1024 | 12457 | 51919 | - | [检测结果](https://dataset.bj.bcebos.com/mot/det_results_dir.zip) | [ReID模型](https://paddledet.bj.bcebos.com/models/mot/deepsort_pcb_pyramid_r101.pdparams)|[配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/deepsort/deepsort_pcb_pyramid_r101.yml) |
-| ResNet-101 | 1088x608 | 61.2 | 48.5 | 1799 | 25796 | 43232 | - | [检测模型](https://paddledet.bj.bcebos.com/models/mot/jde_yolov3_darknet53_30e_1088x608.pdparams) |[ReID模型](https://paddledet.bj.bcebos.com/models/mot/deepsort_pcb_pyramid_r101.pdparams)|[配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/deepsort/deepsort_pcb_pyramid_r101.yml) |
+| ResNet-101 | 1088x608 | 64.1 | 53.0 | 1024 | 12457 | 51919 | - | [检测结果](https://dataset.bj.bcebos.com/mot/det_results_dir.zip) | [ReID模型](https://paddledet.bj.bcebos.com/models/mot/deepsort_pcb_pyramid_r101.pdparams)|[配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/deepsort/deepsort_pcb_pyramid_r101.yml) |
+| ResNet-101 | 1088x608 | 61.2 | 48.5 | 1799 | 25796 | 43232 | - | [检测模型](https://paddledet.bj.bcebos.com/models/mot/jde_yolov3_darknet53_30e_1088x608.pdparams) |[ReID模型](https://paddledet.bj.bcebos.com/models/mot/deepsort_pcb_pyramid_r101.pdparams)|[配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/deepsort/deepsort_pcb_pyramid_r101.yml) |
**注意:**
diff --git a/configs/mot/fairmot/README.md b/configs/mot/fairmot/README.md
index 4f139d8c484aaa26f3da13e4a5a09419fedf24d4..651e969f2c44392f148f36d19c1ebc235ba30499 100644
--- a/configs/mot/fairmot/README.md
+++ b/configs/mot/fairmot/README.md
@@ -19,7 +19,7 @@ English | [简体中文](README_cn.md)
| backbone | input shape | MOTA | IDF1 | IDS | FP | FN | FPS | download | config |
| :--------------| :------- | :----: | :----: | :----: | :----: | :----: | :------: | :----: |:-----: |
| DLA-34(paper) | 1088x608 | 83.3 | 81.9 | 544 | 3822 | 14095 | - | - | - |
-| DLA-34 | 1088x608 | 83.7 | 83.3 | 435 | 3829 | 13764 | - | [model](https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/fairmot/fairmot_dla34_30e_1088x608.yml) |
+| DLA-34 | 1088x608 | 83.7 | 83.3 | 435 | 3829 | 13764 | - | [model](https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/fairmot/fairmot_dla34_30e_1088x608.yml) |
### FairMOT Results on MOT-16 Test Set
@@ -27,7 +27,7 @@ English | [简体中文](README_cn.md)
| backbone | input shape | MOTA | IDF1 | IDS | FP | FN | FPS | download | config |
| :--------------| :------- | :----: | :----: | :----: | :----: | :----: | :------: | :----: |:-----: |
| DLA-34(paper) | 1088x608 | 74.9 | 72.8 | 1074 | - | - | 25.9 | - | - |
-| DLA-34 | 1088x608 | 74.8 | 74.4 | 930 | 7038 | 37994 | - | [model](https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/fairmot/fairmot_dla34_30e_1088x608.yml) |
+| DLA-34 | 1088x608 | 74.8 | 74.4 | 930 | 7038 | 37994 | - | [model](https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/fairmot/fairmot_dla34_30e_1088x608.yml) |
**Notes:**
FairMOT used 8 GPUs for training and mini-batch size as 6 on each GPU, and trained for 30 epoches.
diff --git a/configs/mot/fairmot/README_cn.md b/configs/mot/fairmot/README_cn.md
index ae4b98a226f8b851b8229ff938cac7ff63426257..5e0d808848236ac5de66a9e772b073a009e02640 100644
--- a/configs/mot/fairmot/README_cn.md
+++ b/configs/mot/fairmot/README_cn.md
@@ -19,14 +19,14 @@
| 骨干网络 | 输入尺寸 | MOTA | IDF1 | IDS | FP | FN | FPS | 下载链接 | 配置文件 |
| :--------------| :------- | :----: | :----: | :---: | :----: | :---: | :------: | :----: |:----: |
| DLA-34(paper) | 1088x608 | 83.3 | 81.9 | 544 | 3822 | 14095 | - | - | - |
-| DLA-34 | 1088x608 | 83.7 | 83.3 | 435 | 3829 | 13764 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/fairmot/fairmot_dla34_30e_1088x608.yml) |
+| DLA-34 | 1088x608 | 83.7 | 83.3 | 435 | 3829 | 13764 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/fairmot/fairmot_dla34_30e_1088x608.yml) |
### FairMOT在MOT-16 Test Set上结果
| 骨干网络 | 输入尺寸 | MOTA | IDF1 | IDS | FP | FN | FPS | 下载链接 | 配置文件 |
| :--------------| :------- | :----: | :----: | :----: | :----: | :----: |:-------: | :----: | :----: |
| DLA-34(paper) | 1088x608 | 74.9 | 72.8 | 1074 | - | - | 25.9 | - | - |
-| DLA-34 | 1088x608 | 74.8 | 74.4 | 930 | 7038 | 37994 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/fairmot/fairmot_dla34_30e_1088x608.yml) |
+| DLA-34 | 1088x608 | 74.8 | 74.4 | 930 | 7038 | 37994 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/fairmot/fairmot_dla34_30e_1088x608.yml) |
**注意:**
FairMOT使用8个GPU进行训练，每个GPU上batch size为6，训练30个epoch。
diff --git a/configs/mot/fairmot/headtracking21/README_cn.md b/configs/mot/fairmot/headtracking21/README_cn.md
index 65007f8bc83c8eb0d8bf003fa38f5368876069f7..4a82832e1ad0a846b58ccd2c7dadf7e34aa8c2ec 100644
--- a/configs/mot/fairmot/headtracking21/README_cn.md
+++ b/configs/mot/fairmot/headtracking21/README_cn.md
@@ -22,14 +22,14 @@
| 骨干网络 | 输入尺寸 | MOTA | IDF1 | IDS | FP | FN | FPS | 下载链接 | 配置文件 |
| :--------------| :------- | :----: | :----: | :---: | :----: | :---: | :------: | :----: |:----: |
-| DLA-34 | 1088x608 | 67.2 | 70.4 | 9403 | 124840 | 255007 | - | [下载链接](https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608_headtracking21.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/fairmot/headtracking21/fairmot_dla34_30e_1088x608_headtracking21.yml) |
+| DLA-34 | 1088x608 | 67.2 | 70.4 | 9403 | 124840 | 255007 | - | [下载链接](https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608_headtracking21.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/fairmot/headtracking21/fairmot_dla34_30e_1088x608_headtracking21.yml) |
### FairMOT在HT-21 Test Set上结果
| 骨干网络 | 输入尺寸 | MOTA | IDF1 | IDS | FP | FN | FPS | 下载链接 | 配置文件 |
| :--------------| :------- | :----: | :----: | :----: | :----: | :----: |:-------: | :----: | :----: |
-| DLA-34 | 1088x608 | 58.2 | 61.3 | 13166 | 141872 | 197074 | - | [下载链接](https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608_headtracking21.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/fairmot/headtracking21/fairmot_dla34_30e_1088x608_headtracking21.yml) |
+| DLA-34 | 1088x608 | 58.2 | 61.3 | 13166 | 141872 | 197074 | - | [下载链接](https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608_headtracking21.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/fairmot/headtracking21/fairmot_dla34_30e_1088x608_headtracking21.yml) |
**注意:**
FairMOT使用8个GPU进行训练，每个GPU上batch size为6，训练30个epoch。
diff --git a/configs/mot/jde/README.md b/configs/mot/jde/README.md
index f71ece8ee919b0367a65d4dc974a69c13efc7ac5..94b82b31ad8f38cbd7d608a3a6a385cc72870b06 100644
--- a/configs/mot/jde/README.md
+++ b/configs/mot/jde/README.md
@@ -22,19 +22,19 @@ English | [简体中文](README_cn.md)
| backbone | input shape | MOTA | IDF1 | IDS | FP | FN | FPS | download | config |
| :----------------- | :------- | :----: | :----: | :---: | :----: | :---: | :---: | :---: | :---: |
-| DarkNet53 | 1088x608 | 72.0 | 66.9 | 1397 | 7274 | 22209 | - |[model](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_1088x608.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/jde/jde_darknet53_30e_1088x608.yml) |
-| DarkNet53 | 864x480 | 69.1 | 64.7 | 1539 | 7544 | 25046 | - |[model](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_864x480.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/jde/jde_darknet53_30e_864x480.yml) |
-| DarkNet53 | 576x320 | 63.7 | 64.4 | 1310 | 6782 | 31964 | - |[model](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_576x320.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/jde/jde_darknet53_30e_576x320.yml) |
+| DarkNet53 | 1088x608 | 72.0 | 66.9 | 1397 | 7274 | 22209 | - |[model](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_1088x608.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/jde/jde_darknet53_30e_1088x608.yml) |
+| DarkNet53 | 864x480 | 69.1 | 64.7 | 1539 | 7544 | 25046 | - |[model](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_864x480.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/jde/jde_darknet53_30e_864x480.yml) |
+| DarkNet53 | 576x320 | 63.7 | 64.4 | 1310 | 6782 | 31964 | - |[model](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_576x320.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/jde/jde_darknet53_30e_576x320.yml) |
### JDE Results on MOT-16 Test Set
| backbone | input shape | MOTA | IDF1 | IDS | FP | FN | FPS | download | config |
| :----------------- | :------- | :----: | :----: | :---: | :----: | :---: | :---: | :---: | :---: |
| DarkNet53(paper) | 1088x608 | 64.4 | 55.8 | 1544 | - | - | - | - | - |
-| DarkNet53 | 1088x608 | 64.6 | 58.5 | 1864 | 10550 | 52088 | - |[model](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_1088x608.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/jde/jde_darknet53_30e_1088x608.yml) |
+| DarkNet53 | 1088x608 | 64.6 | 58.5 | 1864 | 10550 | 52088 | - |[model](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_1088x608.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/jde/jde_darknet53_30e_1088x608.yml) |
| DarkNet53(paper) | 864x480 | 62.1 | 56.9 | 1608 | - | - | - | - | - |
-| DarkNet53 | 864x480 | 63.2 | 57.7 | 1966 | 10070 | 55081 | - |[model](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_864x480.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/jde/jde_darknet53_30e_864x480.yml) |
-| DarkNet53 | 576x320 | 59.1 | 56.4 | 1911 | 10923 | 61789 | - |[model](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_576x320.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/jde/jde_darknet53_30e_576x320.yml) |
+| DarkNet53 | 864x480 | 63.2 | 57.7 | 1966 | 10070 | 55081 | - |[model](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_864x480.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/jde/jde_darknet53_30e_864x480.yml) |
+| DarkNet53 | 576x320 | 59.1 | 56.4 | 1911 | 10923 | 61789 | - |[model](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_576x320.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/jde/jde_darknet53_30e_576x320.yml) |
**Notes:**
JDE used 8 GPUs for training and mini-batch size as 4 on each GPU, and trained for 30 epoches.
diff --git a/configs/mot/jde/README_cn.md b/configs/mot/jde/README_cn.md
index 1aa2d383064158888470bb494ed273c34b1e1bf9..30aaa20f48eb39167168d531cad975f59ee99036 100644
--- a/configs/mot/jde/README_cn.md
+++ b/configs/mot/jde/README_cn.md
@@ -22,9 +22,9 @@
| 骨干网络 | 输入尺寸 | MOTA | IDF1 | IDS | FP | FN | FPS | 下载链接 | 配置文件 |
| :----------------- | :------- | :----: | :----: | :---: | :----: | :---: | :---: | :---: | :---: |
-| DarkNet53 | 1088x608 | 72.0 | 66.9 | 1397 | 7274 | 22209 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_1088x608.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/jde/jde_darknet53_30e_1088x608.yml) |
-| DarkNet53 | 864x480 | 69.1 | 64.7 | 1539 | 7544 | 25046 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_864x480.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/jde/jde_darknet53_30e_864x480.yml) |
-| DarkNet53 | 576x320 | 63.7 | 64.4 | 1310 | 6782 | 31964 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_576x320.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/jde/jde_darknet53_30e_576x320.yml) |
+| DarkNet53 | 1088x608 | 72.0 | 66.9 | 1397 | 7274 | 22209 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_1088x608.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/jde/jde_darknet53_30e_1088x608.yml) |
+| DarkNet53 | 864x480 | 69.1 | 64.7 | 1539 | 7544 | 25046 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_864x480.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/jde/jde_darknet53_30e_864x480.yml) |
+| DarkNet53 | 576x320 | 63.7 | 64.4 | 1310 | 6782 | 31964 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_576x320.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/jde/jde_darknet53_30e_576x320.yml) |
### JDE在MOT-16 Test Set上结果
@@ -32,10 +32,10 @@
| 骨干网络 | 输入尺寸 | MOTA | IDF1 | IDS | FP | FN | FPS | 下载链接 | 配置文件 |
| :----------------- | :------- | :----: | :----: | :---: | :----: | :---: | :---: | :---: | :---: |
| DarkNet53(paper) | 1088x608 | 64.4 | 55.8 | 1544 | - | - | - | - | - |
-| DarkNet53 | 1088x608 | 64.6 | 58.5 | 1864 | 10550 | 52088 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_1088x608.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/jde/jde_darknet53_30e_1088x608.yml) |
+| DarkNet53 | 1088x608 | 64.6 | 58.5 | 1864 | 10550 | 52088 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_1088x608.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/jde/jde_darknet53_30e_1088x608.yml) |
| DarkNet53(paper) | 864x480 | 62.1 | 56.9 | 1608 | - | - | - | - | - |
-| DarkNet53 | 864x480 | 63.2 | 57.7 | 1966 | 10070 | 55081 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_864x480.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/jde/jde_darknet53_30e_864x480.yml) |
-| DarkNet53 | 576x320 | 59.1 | 56.4 | 1911 | 10923 | 61789 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_576x320.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mot/jde/jde_darknet53_30e_576x320.yml) |
+| DarkNet53 | 864x480 | 63.2 | 57.7 | 1966 | 10070 | 55081 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_864x480.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/jde/jde_darknet53_30e_864x480.yml) |
+| DarkNet53 | 576x320 | 59.1 | 56.4 | 1911 | 10923 | 61789 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/jde_darknet53_30e_576x320.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/jde/jde_darknet53_30e_576x320.yml) |
**注意:**
JDE使用8个GPU进行训练，每个GPU上batch size为4，训练了30个epoch。
diff --git a/configs/pedestrian/README.md b/configs/pedestrian/README.md
index f9ba42a1985cb3dcad00d6a3b621d24f37e338ac..56416c164705ee4cdcfd8feabf29d6e2260f31a3 100644
--- a/configs/pedestrian/README.md
+++ b/configs/pedestrian/README.md
@@ -5,7 +5,7 @@ We provide some models implemented by PaddlePaddle to detect objects in specific
| Task | Algorithm | Box AP | Download | Configs |
|:---------------------|:---------:|:------:| :-------------------------------------------------------------------------------------: |:------:|
-| Pedestrian Detection | YOLOv3 | 51.8 | [model](https://paddledet.bj.bcebos.com/models/pedestrian_yolov3_darknet.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/pedestrian/pedestrian_yolov3_darknet.yml) |
+| Pedestrian Detection | YOLOv3 | 51.8 | [model](https://paddledet.bj.bcebos.com/models/pedestrian_yolov3_darknet.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/pedestrian/pedestrian_yolov3_darknet.yml) |
## Pedestrian Detection
@@ -17,7 +17,7 @@ The network for detecting vehicles is YOLOv3, the backbone of which is Dacknet53
### 2. Configuration for training
-PaddleDetection provides users with a configuration file [yolov3_darknet53_270e_coco.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/yolov3/yolov3_darknet53_270e_coco.yml) to train YOLOv3 on the COCO dataset, compared with this file, we modify some parameters as followed to conduct the training for pedestrian detection:
+PaddleDetection provides users with a configuration file [yolov3_darknet53_270e_coco.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.2/configs/yolov3/yolov3_darknet53_270e_coco.yml) to train YOLOv3 on the COCO dataset, compared with this file, we modify some parameters as followed to conduct the training for pedestrian detection:
* num_classes: 1
* dataset_dir: dataset/pedestrian
diff --git a/configs/pedestrian/README_cn.md b/configs/pedestrian/README_cn.md
index a1d8b86dbf941427ec4a56e2b99b6fb7cc6a2004..c3019c6a2ad7fa1b316bda3c441b5abbd62ed99a 100644
--- a/configs/pedestrian/README_cn.md
+++ b/configs/pedestrian/README_cn.md
@@ -5,7 +5,7 @@
| 任务 | 算法 | 精度(Box AP) | 下载 | 配置文件 |
|:---------------------|:---------:|:------:| :---------------------------------------------------------------------------------: | :------:|
-| 行人检测 | YOLOv3 | 51.8 | [下载链接](https://paddledet.bj.bcebos.com/models/pedestrian_yolov3_darknet.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/pedestrian/pedestrian_yolov3_darknet.yml) |
+| 行人检测 | YOLOv3 | 51.8 | [下载链接](https://paddledet.bj.bcebos.com/models/pedestrian_yolov3_darknet.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/pedestrian/pedestrian_yolov3_darknet.yml) |
## 行人检测（Pedestrian Detection）
@@ -18,7 +18,7 @@ Backbone为Dacknet53的YOLOv3。
### 2. 训练参数配置
-PaddleDetection提供了使用COCO数据集对YOLOv3进行训练的参数配置文件[yolov3_darknet53_270e_coco.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/yolov3/yolov3_darknet53_270e_coco.yml)，与之相比，在进行行人检测的模型训练时，我们对以下参数进行了修改：
+PaddleDetection提供了使用COCO数据集对YOLOv3进行训练的参数配置文件[yolov3_darknet53_270e_coco.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.2/configs/yolov3/yolov3_darknet53_270e_coco.yml)，与之相比，在进行行人检测的模型训练时，我们对以下参数进行了修改：
* num_classes: 1
* dataset_dir: dataset/pedestrian
diff --git a/configs/ppyolo/README.md b/configs/ppyolo/README.md
index 6701cf124bb112f79d6ff3a2e05bd992e2c775a2..01aa8b170cf31d132b322006712f6d4334ad3a14 100644
--- a/configs/ppyolo/README.md
+++ b/configs/ppyolo/README.md
@@ -38,25 +38,25 @@ PP-YOLO improved performance and speed of YOLOv3 with following methods:
| Model | GPU number | images/GPU | backbone | input shape | Box APval | Box APtest | V100 FP32(FPS) | V100 TensorRT FP16(FPS) | download | config |
|:------------------------:|:-------:|:-------------:|:----------:| :-------:| :------------------: | :-------------------: | :------------: | :---------------------: | :------: | :------: |
-| PP-YOLO | 8 | 24 | ResNet50vd | 608 | 44.8 | 45.2 | 72.9 | 155.6 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) |
-| PP-YOLO | 8 | 24 | ResNet50vd | 512 | 43.9 | 44.4 | 89.9 | 188.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) |
-| PP-YOLO | 8 | 24 | ResNet50vd | 416 | 42.1 | 42.5 | 109.1 | 215.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) |
-| PP-YOLO | 8 | 24 | ResNet50vd | 320 | 38.9 | 39.3 | 132.2 | 242.2 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) |
-| PP-YOLO_2x | 8 | 24 | ResNet50vd | 608 | 45.3 | 45.9 | 72.9 | 155.6 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_2x_coco.yml) |
-| PP-YOLO_2x | 8 | 24 | ResNet50vd | 512 | 44.4 | 45.0 | 89.9 | 188.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_2x_coco.yml) |
-| PP-YOLO_2x | 8 | 24 | ResNet50vd | 416 | 42.7 | 43.2 | 109.1 | 215.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_2x_coco.yml) |
-| PP-YOLO_2x | 8 | 24 | ResNet50vd | 320 | 39.5 | 40.1 | 132.2 | 242.2 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_2x_coco.yml) |
-| PP-YOLO | 4 | 32 | ResNet18vd | 512 | 29.2 | 29.5 | 357.1 | 657.9 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r18vd_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r18vd_coco.yml) |
-| PP-YOLO | 4 | 32 | ResNet18vd | 416 | 28.6 | 28.9 | 409.8 | 719.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r18vd_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r18vd_coco.yml) |
-| PP-YOLO | 4 | 32 | ResNet18vd | 320 | 26.2 | 26.4 | 480.7 | 763.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r18vd_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r18vd_coco.yml) |
-| PP-YOLOv2 | 8 | 12 | ResNet50vd | 640 | 49.1 | 49.5 | 68.9 | 106.5 | [model](https://paddledet.bj.bcebos.com/models/ppyolov2_r50vd_dcn_365e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolov2_r50vd_dcn_365e_coco.yml) |
-| PP-YOLOv2 | 8 | 12 | ResNet101vd | 640 | 49.7 | 50.3 | 49.5 | 87.0 | [model](https://paddledet.bj.bcebos.com/models/ppyolov2_r101vd_dcn_365e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolov2_r101vd_dcn_365e_coco.yml) |
+| PP-YOLO | 8 | 24 | ResNet50vd | 608 | 44.8 | 45.2 | 72.9 | 155.6 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) |
+| PP-YOLO | 8 | 24 | ResNet50vd | 512 | 43.9 | 44.4 | 89.9 | 188.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) |
+| PP-YOLO | 8 | 24 | ResNet50vd | 416 | 42.1 | 42.5 | 109.1 | 215.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) |
+| PP-YOLO | 8 | 24 | ResNet50vd | 320 | 38.9 | 39.3 | 132.2 | 242.2 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) |
+| PP-YOLO_2x | 8 | 24 | ResNet50vd | 608 | 45.3 | 45.9 | 72.9 | 155.6 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_r50vd_dcn_2x_coco.yml) |
+| PP-YOLO_2x | 8 | 24 | ResNet50vd | 512 | 44.4 | 45.0 | 89.9 | 188.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_r50vd_dcn_2x_coco.yml) |
+| PP-YOLO_2x | 8 | 24 | ResNet50vd | 416 | 42.7 | 43.2 | 109.1 | 215.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_r50vd_dcn_2x_coco.yml) |
+| PP-YOLO_2x | 8 | 24 | ResNet50vd | 320 | 39.5 | 40.1 | 132.2 | 242.2 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_r50vd_dcn_2x_coco.yml) |
+| PP-YOLO | 4 | 32 | ResNet18vd | 512 | 29.2 | 29.5 | 357.1 | 657.9 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r18vd_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_r18vd_coco.yml) |
+| PP-YOLO | 4 | 32 | ResNet18vd | 416 | 28.6 | 28.9 | 409.8 | 719.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r18vd_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_r18vd_coco.yml) |
+| PP-YOLO | 4 | 32 | ResNet18vd | 320 | 26.2 | 26.4 | 480.7 | 763.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r18vd_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_r18vd_coco.yml) |
+| PP-YOLOv2 | 8 | 12 | ResNet50vd | 640 | 49.1 | 49.5 | 68.9 | 106.5 | [model](https://paddledet.bj.bcebos.com/models/ppyolov2_r50vd_dcn_365e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolov2_r50vd_dcn_365e_coco.yml) |
+| PP-YOLOv2 | 8 | 12 | ResNet101vd | 640 | 49.7 | 50.3 | 49.5 | 87.0 | [model](https://paddledet.bj.bcebos.com/models/ppyolov2_r101vd_dcn_365e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolov2_r101vd_dcn_365e_coco.yml) |
**Notes:**
- PP-YOLO is trained on COCO train2017 dataset and evaluated on val2017 & test-dev2017 dataset，Box APtest is evaluation results of `mAP(IoU=0.5:0.95)`.
-- PP-YOLO used 8 GPUs for training and mini-batch size as 24 on each GPU, if GPU number and mini-batch size is changed, learning rate and iteration times should be adjusted according [FAQ](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/docs/tutorials/FAQ.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/2.2/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 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)
@@ -66,26 +66,26 @@ PP-YOLO improved performance and speed of YOLOv3 with following methods:
| Model | GPU number | images/GPU | Model Size | input shape | Box APval | Box AP50val | Kirin 990 1xCore(FPS) | download | config |
|:----------------------------:|:-------:|:-------------:|:----------:| :-------:| :------------------: | :--------------------: | :--------------------: | :------: | :------: |
-| PP-YOLO_MobileNetV3_large | 4 | 32 | 28MB | 320 | 23.2 | 42.6 | 14.1 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_large_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_mbv3_large_coco.yml) |
-| PP-YOLO_MobileNetV3_small | 4 | 32 | 16MB | 320 | 17.2 | 33.8 | 21.5 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_small_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_mbv3_small_coco.yml) |
+| PP-YOLO_MobileNetV3_large | 4 | 32 | 28MB | 320 | 23.2 | 42.6 | 14.1 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_large_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_mbv3_large_coco.yml) |
+| PP-YOLO_MobileNetV3_small | 4 | 32 | 16MB | 320 | 17.2 | 33.8 | 21.5 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_small_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_mbv3_small_coco.yml) |
**Notes:**
- PP-YOLO_MobileNetV3 is trained on COCO train2017 datast and evaluated on val2017 dataset，Box APval is evaluation results of `mAP(IoU=0.5:0.95)`, Box APval is evaluation results of `mAP(IoU=0.5)`.
-- PP-YOLO_MobileNetV3 used 4 GPUs for training and mini-batch size as 32 on each GPU, if GPU number and mini-batch size is changed, learning rate and iteration times should be adjusted according [FAQ](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/docs/tutorials/FAQ.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/2.2/docs/tutorials/FAQ.md).
- PP-YOLO_MobileNetV3 inference speed is tested on Kirin 990 with 1 thread.
### PP-YOLO tiny
| Model | GPU number | images/GPU | Model Size | Post Quant Model Size | input shape | Box APval | Kirin 990 4xCore(FPS) | download | config | post quant model |
|:----------------------------:|:-------:|:-------------:|:----------:| :-------------------: | :---------: | :------------------: | :-------------------: | :------: | :----: | :--------------: |
-| PP-YOLO tiny | 8 | 32 | 4.2MB | **1.3M** | 320 | 20.6 | 92.3 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_tiny_650e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_tiny_650e_coco.yml) | [inference model](https://paddledet.bj.bcebos.com/models/ppyolo_tiny_quant.tar) |
-| PP-YOLO tiny | 8 | 32 | 4.2MB | **1.3M** | 416 | 22.7 | 65.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_tiny_650e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_tiny_650e_coco.yml) | [inference model](https://paddledet.bj.bcebos.com/models/ppyolo_tiny_quant.tar) |
+| PP-YOLO tiny | 8 | 32 | 4.2MB | **1.3M** | 320 | 20.6 | 92.3 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_tiny_650e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_tiny_650e_coco.yml) | [inference model](https://paddledet.bj.bcebos.com/models/ppyolo_tiny_quant.tar) |
+| PP-YOLO tiny | 8 | 32 | 4.2MB | **1.3M** | 416 | 22.7 | 65.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_tiny_650e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_tiny_650e_coco.yml) | [inference model](https://paddledet.bj.bcebos.com/models/ppyolo_tiny_quant.tar) |
**Notes:**
- PP-YOLO-tiny is trained on COCO train2017 datast and evaluated on val2017 dataset，Box APval is evaluation results of `mAP(IoU=0.5:0.95)`, Box APval is evaluation results of `mAP(IoU=0.5)`.
-- PP-YOLO-tiny used 8 GPUs for training and mini-batch size as 32 on each GPU, if GPU number and mini-batch size is changed, learning rate and iteration times should be adjusted according [FAQ](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/docs/tutorials/FAQ.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/2.2/docs/tutorials/FAQ.md).
- PP-YOLO-tiny inference speed is tested on Kirin 990 with 4 threads by arm8
- we alse provide PP-YOLO-tiny post quant inference model, which can compress model to **1.3MB** with nearly no inference on inference speed and performance
@@ -95,9 +95,9 @@ PP-YOLO trained on Pascal VOC dataset as follows:
| Model | GPU number | images/GPU | backbone | input shape | Box AP50val | download | config |
|:------------------:|:----------:|:----------:|:----------:| :----------:| :--------------------: | :------: | :-----: |
-| PP-YOLO | 8 | 12 | ResNet50vd | 608 | 84.9 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_voc.yml) |
-| PP-YOLO | 8 | 12 | ResNet50vd | 416 | 84.3 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_voc.yml) |
-| PP-YOLO | 8 | 12 | ResNet50vd | 320 | 82.2 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_voc.yml) |
+| PP-YOLO | 8 | 12 | ResNet50vd | 608 | 84.9 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_r50vd_dcn_voc.yml) |
+| PP-YOLO | 8 | 12 | ResNet50vd | 416 | 84.3 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_r50vd_dcn_voc.yml) |
+| PP-YOLO | 8 | 12 | ResNet50vd | 320 | 82.2 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_r50vd_dcn_voc.yml) |
## Getting Start
@@ -214,7 +214,7 @@ Optimizing method and ablation experiments of PP-YOLO compared with YOLOv3.
- Performance and inference spedd are measure with input shape as 608
- All models are trained on COCO train2017 datast and evaluated on val2017 & test-dev2017 dataset，`Box AP` is evaluation results as `mAP(IoU=0.5:0.95)`.
- Inference speed is tested on single Tesla V100 with batch size as 1 following test method and environment configuration in benchmark above.
-- [YOLOv3-DarkNet53](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_darknet53_270e_coco.yml) with mAP as 39.0 is optimized YOLOv3 model in PaddleDetection，see [YOLOv3](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/yolov3/README.md) for details.
+- [YOLOv3-DarkNet53](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_darknet53_270e_coco.yml) with mAP as 39.0 is optimized YOLOv3 model in PaddleDetection，see [YOLOv3](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.2/configs/yolov3/README.md) for details.
## Citation
diff --git a/configs/ppyolo/README_cn.md b/configs/ppyolo/README_cn.md
index b13ca3497c896cc53b7f81a33444c68ad6a6db0f..78bce9756b62fd55a42db51897e1b4e48b51f5ec 100644
--- a/configs/ppyolo/README_cn.md
+++ b/configs/ppyolo/README_cn.md
@@ -38,24 +38,24 @@ 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 APval | Box APtest | V100 FP32(FPS) | V100 TensorRT FP16(FPS) | 模型下载 | 配置文件 |
|:------------------------:|:-------:|:-------------:|:----------:| :-------:| :------------------: | :-------------------: | :------------: | :---------------------: | :------: | :------: |
-| PP-YOLO | 8 | 24 | ResNet50vd | 608 | 44.8 | 45.2 | 72.9 | 155.6 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) |
-| PP-YOLO | 8 | 24 | ResNet50vd | 512 | 43.9 | 44.4 | 89.9 | 188.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) |
-| PP-YOLO | 8 | 24 | ResNet50vd | 416 | 42.1 | 42.5 | 109.1 | 215.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) |
-| PP-YOLO | 8 | 24 | ResNet50vd | 320 | 38.9 | 39.3 | 132.2 | 242.2 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) |
-| PP-YOLO_2x | 8 | 24 | ResNet50vd | 608 | 45.3 | 45.9 | 72.9 | 155.6 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_2x_coco.yml) |
-| PP-YOLO_2x | 8 | 24 | ResNet50vd | 512 | 44.4 | 45.0 | 89.9 | 188.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_2x_coco.yml) |
-| PP-YOLO_2x | 8 | 24 | ResNet50vd | 416 | 42.7 | 43.2 | 109.1 | 215.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_2x_coco.yml) |
-| PP-YOLO_2x | 8 | 24 | ResNet50vd | 320 | 39.5 | 40.1 | 132.2 | 242.2 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_2x_coco.yml) |
-| PP-YOLO | 4 | 32 | ResNet18vd | 512 | 29.2 | 29.5 | 357.1 | 657.9 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r18vd_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r18vd_coco.yml) |
-| PP-YOLO | 4 | 32 | ResNet18vd | 416 | 28.6 | 28.9 | 409.8 | 719.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r18vd_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r18vd_coco.yml) |
-| PP-YOLO | 4 | 32 | ResNet18vd | 320 | 26.2 | 26.4 | 480.7 | 763.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r18vd_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r18vd_coco.yml) |
-| PP-YOLOv2 | 8 | 12 | ResNet50vd | 640 | 49.1 | 49.5 | 68.9 | 106.5 | [model](https://paddledet.bj.bcebos.com/models/ppyolov2_r50vd_dcn_365e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolov2_r50vd_dcn_365e_coco.yml) |
-| PP-YOLOv2 | 8 | 12 | ResNet101vd | 640 | 49.7 | 50.3 | 49.5 | 87.0 | [model](https://paddledet.bj.bcebos.com/models/ppyolov2_r101vd_dcn_365e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolov2_r101vd_dcn_365e_coco.yml) |
+| PP-YOLO | 8 | 24 | ResNet50vd | 608 | 44.8 | 45.2 | 72.9 | 155.6 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) |
+| PP-YOLO | 8 | 24 | ResNet50vd | 512 | 43.9 | 44.4 | 89.9 | 188.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) |
+| PP-YOLO | 8 | 24 | ResNet50vd | 416 | 42.1 | 42.5 | 109.1 | 215.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) |
+| PP-YOLO | 8 | 24 | ResNet50vd | 320 | 38.9 | 39.3 | 132.2 | 242.2 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) |
+| PP-YOLO_2x | 8 | 24 | ResNet50vd | 608 | 45.3 | 45.9 | 72.9 | 155.6 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_r50vd_dcn_2x_coco.yml) |
+| PP-YOLO_2x | 8 | 24 | ResNet50vd | 512 | 44.4 | 45.0 | 89.9 | 188.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_r50vd_dcn_2x_coco.yml) |
+| PP-YOLO_2x | 8 | 24 | ResNet50vd | 416 | 42.7 | 43.2 | 109.1 | 215.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_r50vd_dcn_2x_coco.yml) |
+| PP-YOLO_2x | 8 | 24 | ResNet50vd | 320 | 39.5 | 40.1 | 132.2 | 242.2 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_r50vd_dcn_2x_coco.yml) |
+| PP-YOLO | 4 | 32 | ResNet18vd | 512 | 29.2 | 29.5 | 357.1 | 657.9 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r18vd_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_r18vd_coco.yml) |
+| PP-YOLO | 4 | 32 | ResNet18vd | 416 | 28.6 | 28.9 | 409.8 | 719.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r18vd_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_r18vd_coco.yml) |
+| PP-YOLO | 4 | 32 | ResNet18vd | 320 | 26.2 | 26.4 | 480.7 | 763.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r18vd_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_r18vd_coco.yml) |
+| PP-YOLOv2 | 8 | 12 | ResNet50vd | 640 | 49.1 | 49.5 | 68.9 | 106.5 | [model](https://paddledet.bj.bcebos.com/models/ppyolov2_r50vd_dcn_365e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolov2_r50vd_dcn_365e_coco.yml) |
+| PP-YOLOv2 | 8 | 12 | ResNet101vd | 640 | 49.7 | 50.3 | 49.5 | 87.0 | [model](https://paddledet.bj.bcebos.com/models/ppyolov2_r101vd_dcn_365e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolov2_r101vd_dcn_365e_coco.yml) |
**注意:**
- PP-YOLO模型使用COCO数据集中train2017作为训练集，使用val2017和test-dev2017作为测试集，Box APtest为`mAP(IoU=0.5:0.95)`评估结果。
-- PP-YOLO模型训练过程中使用8 GPUs，每GPU batch size为24进行训练，如训练GPU数和batch size不使用上述配置，须参考[FAQ](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/docs/tutorials/FAQ.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/2.2/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)。
@@ -64,22 +64,22 @@ 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 APval | Box AP50val | Kirin 990 1xCore (FPS) | 模型下载 | 配置文件 |
|:----------------------------:|:-------:|:-------------:|:----------:| :-------:| :------------------: | :--------------------: | :--------------------: | :------: | :------: |
-| PP-YOLO_MobileNetV3_large | 4 | 32 | 28MB | 320 | 23.2 | 42.6 | 14.1 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_large_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_mbv3_large_coco.yml) |
-| PP-YOLO_MobileNetV3_small | 4 | 32 | 16MB | 320 | 17.2 | 33.8 | 21.5 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_small_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_mbv3_small_coco.yml) |
+| PP-YOLO_MobileNetV3_large | 4 | 32 | 28MB | 320 | 23.2 | 42.6 | 14.1 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_large_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_mbv3_large_coco.yml) |
+| PP-YOLO_MobileNetV3_small | 4 | 32 | 16MB | 320 | 17.2 | 33.8 | 21.5 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_small_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_mbv3_small_coco.yml) |
- PP-YOLO_MobileNetV3 模型使用COCO数据集中train2017作为训练集，使用val2017作为测试集，Box APval为`mAP(IoU=0.5:0.95)`评估结果, Box AP50val为`mAP(IoU=0.5)`评估结果。
-- PP-YOLO_MobileNetV3 模型训练过程中使用4GPU，每GPU batch size为32进行训练，如训练GPU数和batch size不使用上述配置，须参考[FAQ](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/docs/tutorials/FAQ.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/2.2/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 tiny模型
| 模型 | GPU 个数 | 每GPU图片个数 | 模型体积 | 后量化模型体积 | 输入尺寸 | Box APval | Kirin 990 1xCore (FPS) | 模型下载 | 配置文件 | 量化后模型 |
|:----------------------------:|:----------:|:-------------:| :--------: | :------------: | :----------:| :------------------: | :--------------------: | :------: | :------: | :--------: |
-| PP-YOLO tiny | 8 | 32 | 4.2MB | **1.3M** | 320 | 20.6 | 92.3 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_tiny_650e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_tiny_650e_coco.yml) | [预测模型](https://paddledet.bj.bcebos.com/models/ppyolo_tiny_quant.tar) |
-| PP-YOLO tiny | 8 | 32 | 4.2MB | **1.3M** | 416 | 22.7 | 65.4 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_tiny_650e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_tiny_650e_coco.yml) | [预测模型](https://paddledet.bj.bcebos.com/models/ppyolo_tiny_quant.tar) |
+| PP-YOLO tiny | 8 | 32 | 4.2MB | **1.3M** | 320 | 20.6 | 92.3 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_tiny_650e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/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/2.2/configs/ppyolo/ppyolo_tiny_650e_coco.yml) | [预测模型](https://paddledet.bj.bcebos.com/models/ppyolo_tiny_quant.tar) |
- PP-YOLO-tiny 模型使用COCO数据集中train2017作为训练集，使用val2017作为测试集，Box APval为`mAP(IoU=0.5:0.95)`评估结果, Box AP50val为`mAP(IoU=0.5)`评估结果。
-- PP-YOLO-tiny 模型训练过程中使用8GPU，每GPU batch size为32进行训练，如训练GPU数和batch size不使用上述配置，须参考[FAQ](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/docs/tutorials/FAQ.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/2.2/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。
- 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
@@ -89,9 +89,9 @@ PP-YOLO在Pascal VOC数据集上训练模型如下:
| 模型 | GPU个数 | 每GPU图片个数 | 骨干网络 | 输入尺寸 | Box AP50val | 模型下载 | 配置文件 |
|:------------------:|:-------:|:-------------:|:----------:| :----------:| :--------------------: | :------: | :-----: |
-| PP-YOLO | 8 | 12 | ResNet50vd | 608 | 84.9 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_voc.yml) |
-| PP-YOLO | 8 | 12 | ResNet50vd | 416 | 84.3 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_voc.yml) |
-| PP-YOLO | 8 | 12 | ResNet50vd | 320 | 82.2 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_voc.yml) |
+| PP-YOLO | 8 | 12 | ResNet50vd | 608 | 84.9 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_r50vd_dcn_voc.yml) |
+| PP-YOLO | 8 | 12 | ResNet50vd | 416 | 84.3 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_r50vd_dcn_voc.yml) |
+| PP-YOLO | 8 | 12 | ResNet50vd | 320 | 82.2 | [model](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_r50vd_dcn_voc.yml) |
## 使用说明
@@ -207,7 +207,7 @@ PP-YOLO模型相对于YOLOv3模型优化项消融实验数据如下表所示。
- 精度与推理速度数据均为使用输入图像尺寸为608的测试结果
- Box AP为在COCO train2017数据集训练，val2017和test-dev2017数据集上评估`mAP(IoU=0.5:0.95)`数据
- 推理速度为单卡V100上，batch size=1, 使用上述benchmark测试方法的测试结果，测试环境配置为CUDA 10.2，CUDNN 7.5.1
-- [YOLOv3-DarkNet53](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_darknet53_270e_coco.yml)精度38.9为PaddleDetection优化后的YOLOv3模型，可参见[YOLOv3](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/yolov3/README.md)
+- [YOLOv3-DarkNet53](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_darknet53_270e_coco.yml)精度38.9为PaddleDetection优化后的YOLOv3模型，可参见[YOLOv3](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.2/configs/yolov3/README.md)
## 引用
diff --git a/configs/rcnn_enhance/README.md b/configs/rcnn_enhance/README.md
index 6e2c0917b53ecc2f07836f54bb6400d40d04548c..de872197345711ce661eea1a5b7cc09e9e5a8a82 100644
--- a/configs/rcnn_enhance/README.md
+++ b/configs/rcnn_enhance/README.md
@@ -9,4 +9,4 @@
| 骨架网络 | 网络类型 | 每张GPU图片个数 | 学习率策略 |推理时间(fps) | Box AP | Mask AP | 下载 | 配置文件 |
| :---------------------- | :-------------: | :-------: | :-----: | :------------: | :----: | :-----: | :-------------: | :-----: |
-| ResNet50-vd-FPN-Dcnv2 | Faster | 2 | 3x | 61.425 | 41.5 | - | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_enhance_3x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/rcnn_enhance/faster_rcnn_enhance_3x_coco.yml) |
+| ResNet50-vd-FPN-Dcnv2 | Faster | 2 | 3x | 61.425 | 41.5 | - | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_enhance_3x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/rcnn_enhance/faster_rcnn_enhance_3x_coco.yml) |
diff --git a/configs/res2net/README.md b/configs/res2net/README.md
index 7f03c240fef60329057685b1923393cec17c694b..117fc9b18c22ab69a24d572ed6da04a7bab22fb8 100644
--- a/configs/res2net/README.md
+++ b/configs/res2net/README.md
@@ -30,8 +30,8 @@
| Backbone | Type | Image/gpu | Lr schd | Inf time (fps) | Box AP | Mask AP | Download | Configs |
| :---------------------- | :------------- | :-------: | :-----: | :------------: | :----: | :-----: | :----------------------------------------------------------: | :-----: |
-| Res2Net50-FPN | Faster | 2 | 1x | - | 40.6 | - | [model](https://paddledet.bj.bcebos.com/models/faster_rcnn_res2net50_vb_26w_4s_fpn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/res2net/faster_rcnn_res2net50_vb_26w_4s_fpn_1x_coco.yml) |
-| Res2Net50-FPN | Mask | 2 | 2x | - | 42.4 | 38.1 | [model](https://paddledet.bj.bcebos.com/models/mask_rcnn_res2net50_vb_26w_4s_fpn_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/res2net/mask_rcnn_res2net50_vb_26w_4s_fpn_2x_coco.yml) |
-| Res2Net50-vd-FPN | Mask | 2 | 2x | - | 42.6 | 38.1 | [model](https://paddledet.bj.bcebos.com/models/mask_rcnn_res2net50_vd_26w_4s_fpn_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/res2net/mask_rcnn_res2net50_vd_26w_4s_fpn_2x_coco.yml) |
+| Res2Net50-FPN | Faster | 2 | 1x | - | 40.6 | - | [model](https://paddledet.bj.bcebos.com/models/faster_rcnn_res2net50_vb_26w_4s_fpn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.2/configs/res2net/faster_rcnn_res2net50_vb_26w_4s_fpn_1x_coco.yml) |
+| Res2Net50-FPN | Mask | 2 | 2x | - | 42.4 | 38.1 | [model](https://paddledet.bj.bcebos.com/models/mask_rcnn_res2net50_vb_26w_4s_fpn_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.2/configs/res2net/mask_rcnn_res2net50_vb_26w_4s_fpn_2x_coco.yml) |
+| Res2Net50-vd-FPN | Mask | 2 | 2x | - | 42.6 | 38.1 | [model](https://paddledet.bj.bcebos.com/models/mask_rcnn_res2net50_vd_26w_4s_fpn_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.2/configs/res2net/mask_rcnn_res2net50_vd_26w_4s_fpn_2x_coco.yml) |
Note: all the above models are trained with 8 gpus.
diff --git a/configs/slim/README.md b/configs/slim/README.md
index b175266f8188237446ed8dcfb1e99cb13e789cf7..905b121c3536ebceafa6ee9c760cbabbf6cc2249 100755
--- a/configs/slim/README.md
+++ b/configs/slim/README.md
@@ -101,18 +101,18 @@ python tools/export_model.py -c configs/{MODEL.yml} --slim_config configs/slim/{
| 模型 | 压缩策略 | GFLOPs | 模型体积(MB) | 输入尺寸 | 预测时延(SD855) | Box AP | 下载 | 模型配置文件 | 压缩算法配置文件 |
| :---------: | :-------: | :------------: |:-------------: | :------: | :-------------: | :------: | :-----------------------------------------------------: |:-------------: | :------: |
-| YOLOv3-MobileNetV1 | baseline | 24.13 | 93 | 608 | 332.0ms | 75.1 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_voc.yml) | - |
-| YOLOv3-MobileNetV1 | 剪裁-l1_norm(sensity) | 15.78(-34.49%) | 66(-29%) | 608 | - | 78.4(+3.3) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_voc_prune_l1_norm.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_voc.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/prune/yolov3_prune_l1_norm.yml) |
+| YOLOv3-MobileNetV1 | baseline | 24.13 | 93 | 608 | 332.0ms | 75.1 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v1_270e_voc.yml) | - |
+| YOLOv3-MobileNetV1 | 剪裁-l1_norm(sensity) | 15.78(-34.49%) | 66(-29%) | 608 | - | 78.4(+3.3) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_voc_prune_l1_norm.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v1_270e_voc.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/slim/prune/yolov3_prune_l1_norm.yml) |
#### COCO上benchmark
| 模型 | 压缩策略 | GFLOPs | 模型体积(MB) | 输入尺寸 | 预测时延(SD855) | Box AP | 下载 | 模型配置文件 | 压缩算法配置文件 |
| :---------: | :-------: | :------------: |:-------------: | :------: | :-------------: | :------: | :-----------------------------------------------------: |:-------------: | :------: |
-| PP-YOLO-MobileNetV3_large | baseline | -- | 18.5 | 608 | 25.1ms | 23.2 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_large_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_mbv3_large_coco.yml) | - |
-| PP-YOLO-MobileNetV3_large | 剪裁-FPGM | -37% | 12.6 | 608 | - | 22.3 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolo_mbv3_large_prune_fpgm.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_mbv3_large_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/prune/ppyolo_mbv3_large_prune_fpgm.yml) |
-| YOLOv3-DarkNet53 | baseline | -- | 238.2 | 608 | - | 39.0 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_large_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_darknet53_270e_coco.yml) | - |
-| YOLOv3-DarkNet53 | 剪裁-FPGM | -24% | - | 608 | - | 37.6 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_darknet_prune_fpgm.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_darknet53_270e_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/prune/yolov3_darknet_prune_fpgm.yml) |
-| PP-YOLO_R50vd | baseline | -- | 183.3 | 608 | - | 44.8 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | - |
-| PP-YOLO_R50vd | 剪裁-FPGM | -35% | - | 608 | - | 42.1 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolo_r50vd_prune_fpgm.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/prune/ppyolo_r50vd_prune_fpgm.yml) |
+| PP-YOLO-MobileNetV3_large | baseline | -- | 18.5 | 608 | 25.1ms | 23.2 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_large_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_mbv3_large_coco.yml) | - |
+| PP-YOLO-MobileNetV3_large | 剪裁-FPGM | -37% | 12.6 | 608 | - | 22.3 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolo_mbv3_large_prune_fpgm.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_mbv3_large_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/slim/prune/ppyolo_mbv3_large_prune_fpgm.yml) |
+| YOLOv3-DarkNet53 | baseline | -- | 238.2 | 608 | - | 39.0 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_large_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_darknet53_270e_coco.yml) | - |
+| YOLOv3-DarkNet53 | 剪裁-FPGM | -24% | - | 608 | - | 37.6 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_darknet_prune_fpgm.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_darknet53_270e_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/slim/prune/yolov3_darknet_prune_fpgm.yml) |
+| PP-YOLO_R50vd | baseline | -- | 183.3 | 608 | - | 44.8 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | - |
+| PP-YOLO_R50vd | 剪裁-FPGM | -35% | - | 608 | - | 42.1 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolo_r50vd_prune_fpgm.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/slim/prune/ppyolo_r50vd_prune_fpgm.yml) |
说明：
- 目前剪裁除RCNN系列模型外，其余模型均已支持。
@@ -124,22 +124,22 @@ python tools/export_model.py -c configs/{MODEL.yml} --slim_config configs/slim/{
| 模型 | 压缩策略 | 输入尺寸 | 模型体积(MB) | 预测时延(V100) | 预测时延(SD855) | Box AP | 下载 | Inference模型下载 | 模型配置文件 | 压缩算法配置文件 |
| ------------------ | ------------ | -------- | :---------: | :---------: |:---------: | :---------: | :----------------------------------------------: | :----------------------------------------------: |:------------------------------------------: | :------------------------------------: |
-| PP-YOLOv2_R50vd | baseline | 640 | 208.6 | 19.1ms | -- | 49.1 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyolov2_r50vd_dcn_365e_coco.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolov2_r50vd_dcn_365e_coco.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | - |
-| PP-YOLOv2_R50vd | PACT在线量化 | 640 | -- | 17.3ms | -- | 48.1 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolov2_r50vd_dcn_qat.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolov2_r50vd_dcn_qat.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/quant/ppyolov2_r50vd_dcn_qat.yml) |
-| PP-YOLO_R50vd | baseline | 608 | 183.3 | 17.4ms | -- | 44.8 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolo_r50vd_dcn_1x_coco.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | - |
-| PP-YOLO_R50vd | PACT在线量化 | 608 | 67.3 | 13.8ms | -- | 44.3 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolo_r50vd_qat_pact.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolo_r50vd_qat_pact.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/quant/ppyolo_r50vd_qat_pact.yml) |
-| PP-YOLO-MobileNetV3_large | baseline | 320 | 18.5 | 2.7ms | 27.9ms | 23.2 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_large_coco.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolo_mbv3_large_coco.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_mbv3_large_coco.yml) | - |
-| PP-YOLO-MobileNetV3_large | 普通在线量化 | 320 | 5.6 | -- | 25.1ms | 24.3 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolo_mbv3_large_qat.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolo_mbv3_large_qat.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/ppyolo_mbv3_large_coco.yml) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/quant/ppyolo_mbv3_large_qat.yml) |
-| YOLOv3-MobileNetV1 | baseline | 608 | 94.2 | 8.9ms | 332ms | 29.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_270e_coco.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | - |
-| YOLOv3-MobileNetV1 | 普通在线量化 | 608 | 25.4 | 6.6ms | 248ms | 30.5 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_coco_qat.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_coco_qat.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/quant/yolov3_mobilenet_v1_qat.yml) |
-| YOLOv3-MobileNetV3 | baseline | 608 | 90.3 | 9.4ms | 367.2ms | 31.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_coco.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v3_large_270e_coco.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_270e_coco.yml) | - |
-| YOLOv3-MobileNetV3 | PACT在线量化 | 608 | 24.4 | 8.0ms | 280.0ms | 31.1 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v3_coco_qat.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v3_coco_qat.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_270e_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/quant/yolov3_mobilenet_v3_qat.yml) |
-| YOLOv3-DarkNet53 | baseline | 608 | 238.2 | 16.0ms | -- | 39.0 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_darknet53_270e_coco.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_darknet53_270e_coco.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_darknet53_270e_coco.yml) | - |
-| YOLOv3-DarkNet53 | 普通在线量化 | 608 | 78.8 | 12.4ms | -- | 38.8 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_darknet_coco_qat.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_darknet_coco_qat.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_darknet53_270e_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/quant/yolov3_darknet_qat.yml) |
-| SSD-MobileNet_v1 | baseline | 300 | 22.5 | 4.4ms | 26.6ms | 73.8 | [下载链接](https://paddledet.bj.bcebos.com/models/ssd_mobilenet_v1_300_120e_voc.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ssd_mobilenet_v1_300_120e_voc.tar) |[配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ssd/ssd_mobilenet_v1_300_120e_voc.yml) | - |
-| SSD-MobileNet_v1 | 普通在线量化 | 300 | 7.1 | -- | 21.5ms | 72.9 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ssd_mobilenet_v1_300_voc_qat.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ssd_mobilenet_v1_300_voc_qat.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ssd/ssd_mobilenet_v1_300_120e_voc.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/quant/ssd_mobilenet_v1_qat.yml) |
-| Mask-ResNet50-FPN | baseline | (800, 1333) | 174.1 | 359.5ms | -- | 39.2/35.6 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_fpn_1x_coco.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/mask_rcnn_r50_fpn_1x_coco.tar) |[配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_r50_fpn_1x_coco.yml) | - |
-| Mask-ResNet50-FPN | 普通在线量化 | (800, 1333) | -- | -- | -- | 39.7(+0.5)/35.9(+0.3) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/mask_rcnn_r50_fpn_1x_qat.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/mask_rcnn_r50_fpn_1x_qat.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_r50_fpn_1x_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/quant/mask_rcnn_r50_fpn_1x_qat.yml) |
+| PP-YOLOv2_R50vd | baseline | 640 | 208.6 | 19.1ms | -- | 49.1 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyolov2_r50vd_dcn_365e_coco.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolov2_r50vd_dcn_365e_coco.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | - |
+| PP-YOLOv2_R50vd | PACT在线量化 | 640 | -- | 17.3ms | -- | 48.1 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolov2_r50vd_dcn_qat.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolov2_r50vd_dcn_qat.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/slim/quant/ppyolov2_r50vd_dcn_qat.yml) |
+| PP-YOLO_R50vd | baseline | 608 | 183.3 | 17.4ms | -- | 44.8 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolo_r50vd_dcn_1x_coco.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | - |
+| PP-YOLO_R50vd | PACT在线量化 | 608 | 67.3 | 13.8ms | -- | 44.3 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolo_r50vd_qat_pact.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolo_r50vd_qat_pact.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/slim/quant/ppyolo_r50vd_qat_pact.yml) |
+| PP-YOLO-MobileNetV3_large | baseline | 320 | 18.5 | 2.7ms | 27.9ms | 23.2 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_large_coco.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolo_mbv3_large_coco.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_mbv3_large_coco.yml) | - |
+| PP-YOLO-MobileNetV3_large | 普通在线量化 | 320 | 5.6 | -- | 25.1ms | 24.3 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolo_mbv3_large_qat.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ppyolo_mbv3_large_qat.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/ppyolo_mbv3_large_coco.yml) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/slim/quant/ppyolo_mbv3_large_qat.yml) |
+| YOLOv3-MobileNetV1 | baseline | 608 | 94.2 | 8.9ms | 332ms | 29.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_270e_coco.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | - |
+| YOLOv3-MobileNetV1 | 普通在线量化 | 608 | 25.4 | 6.6ms | 248ms | 30.5 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_coco_qat.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_coco_qat.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/slim/quant/yolov3_mobilenet_v1_qat.yml) |
+| YOLOv3-MobileNetV3 | baseline | 608 | 90.3 | 9.4ms | 367.2ms | 31.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_coco.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v3_large_270e_coco.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v3_large_270e_coco.yml) | - |
+| YOLOv3-MobileNetV3 | PACT在线量化 | 608 | 24.4 | 8.0ms | 280.0ms | 31.1 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v3_coco_qat.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v3_coco_qat.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v3_large_270e_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/slim/quant/yolov3_mobilenet_v3_qat.yml) |
+| YOLOv3-DarkNet53 | baseline | 608 | 238.2 | 16.0ms | -- | 39.0 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_darknet53_270e_coco.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_darknet53_270e_coco.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_darknet53_270e_coco.yml) | - |
+| YOLOv3-DarkNet53 | 普通在线量化 | 608 | 78.8 | 12.4ms | -- | 38.8 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_darknet_coco_qat.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_darknet_coco_qat.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_darknet53_270e_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/slim/quant/yolov3_darknet_qat.yml) |
+| SSD-MobileNet_v1 | baseline | 300 | 22.5 | 4.4ms | 26.6ms | 73.8 | [下载链接](https://paddledet.bj.bcebos.com/models/ssd_mobilenet_v1_300_120e_voc.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ssd_mobilenet_v1_300_120e_voc.tar) |[配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ssd/ssd_mobilenet_v1_300_120e_voc.yml) | - |
+| SSD-MobileNet_v1 | 普通在线量化 | 300 | 7.1 | -- | 21.5ms | 72.9 | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ssd_mobilenet_v1_300_voc_qat.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ssd_mobilenet_v1_300_voc_qat.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ssd/ssd_mobilenet_v1_300_120e_voc.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/slim/quant/ssd_mobilenet_v1_qat.yml) |
+| Mask-ResNet50-FPN | baseline | (800, 1333) | 174.1 | 359.5ms | -- | 39.2/35.6 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_fpn_1x_coco.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/mask_rcnn_r50_fpn_1x_coco.tar) |[配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mask_rcnn/mask_rcnn_r50_fpn_1x_coco.yml) | - |
+| Mask-ResNet50-FPN | 普通在线量化 | (800, 1333) | -- | -- | -- | 39.7(+0.5)/35.9(+0.3) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/mask_rcnn_r50_fpn_1x_qat.pdparams) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/mask_rcnn_r50_fpn_1x_qat.tar) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mask_rcnn/mask_rcnn_r50_fpn_1x_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/slim/quant/mask_rcnn_r50_fpn_1x_qat.yml) |
说明：
- 上述V100预测时延非量化模型均是使用TensorRT-FP32测试，量化模型均使用TensorRT-INT8测试，并且都包含NMS耗时。
@@ -151,8 +151,8 @@ python tools/export_model.py -c configs/{MODEL.yml} --slim_config configs/slim/{
| 模型 | 压缩策略 | 输入尺寸 | Box AP | 下载 | 模型配置文件 | 压缩算法配置文件 |
| ------------------ | ------------ | -------- | :---------: | :----------------------------------------------------------: | :----------------------------------------------------------: | :----------------------------------------------------------: |
-| YOLOv3-MobileNetV1 | baseline | 608 | 29.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | - |
-| YOLOv3-MobileNetV1 | 蒸馏 | 608 | 31.0(+1.6) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_coco_distill.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/distill/yolov3_mobilenet_v1_coco_distill.yml) |
+| YOLOv3-MobileNetV1 | baseline | 608 | 29.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | - |
+| YOLOv3-MobileNetV1 | 蒸馏 | 608 | 31.0(+1.6) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_coco_distill.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/slim/distill/yolov3_mobilenet_v1_coco_distill.yml) |
- 具体蒸馏方法请参考[蒸馏策略文档](distill/README.md)
@@ -162,5 +162,5 @@ python tools/export_model.py -c configs/{MODEL.yml} --slim_config configs/slim/{
| 模型 | 压缩策略 | 输入尺寸 | GFLOPs | 模型体积(MB) | 预测时延(SD855) | Box AP | 下载 | 模型配置文件 | 压缩算法配置文件 |
| ------------------ | ------------ | -------- | :---------: |:---------: |:---------: | :---------: |:----------------------------------------------------------: | :----------------------------------------------------------: | :----------------------------------------------------------: |
-| YOLOv3-MobileNetV1 | baseline | 608 | 24.65 | 94.2 | 332.0ms | 29.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | - |
-| YOLOv3-MobileNetV1 | 蒸馏+剪裁 | 608 | 7.54(-69.4%) | 30.9(-67.2%) | 166.1ms | 28.4(-1.0) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_coco_distill_prune.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/slim/extensions/yolov3_mobilenet_v1_coco_distill_prune.yml) |
+| YOLOv3-MobileNetV1 | baseline | 608 | 24.65 | 94.2 | 332.0ms | 29.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | - |
+| YOLOv3-MobileNetV1 | 蒸馏+剪裁 | 608 | 7.54(-69.4%) | 30.9(-67.2%) | 166.1ms | 28.4(-1.0) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_coco_distill_prune.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) | [slim配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/slim/extensions/yolov3_mobilenet_v1_coco_distill_prune.yml) |
diff --git a/configs/slim/distill/README.md b/configs/slim/distill/README.md
index da5795764cec02ea384f8e063f918b56b4f2b9bb..44b7bcae70e6b0f237383e72ce5ff7c0c8bc3e5b 100644
--- a/configs/slim/distill/README.md
+++ b/configs/slim/distill/README.md
@@ -3,7 +3,7 @@
## YOLOv3模型蒸馏
以YOLOv3-MobileNetV1为例，使用YOLOv3-ResNet34作为蒸馏训练的teacher网络, 对YOLOv3-MobileNetV1结构的student网络进行蒸馏。
COCO数据集作为目标检测任务的训练目标难度更大，意味着teacher网络会预测出更多的背景bbox，如果直接用teacher的预测输出作为student学习的`soft label`会有严重的类别不均衡问题。解决这个问题需要引入新的方法，详细背景请参考论文:[Object detection at 200 Frames Per Second](https://arxiv.org/abs/1805.06361)。
-为了确定蒸馏的对象，我们首先需要找到student和teacher网络得到的`x,y,w,h,cls,objness`等Tensor，用teacher得到的结果指导student训练。具体实现可参考[代码](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/ppdet/slim/distill.py)
+为了确定蒸馏的对象，我们首先需要找到student和teacher网络得到的`x,y,w,h,cls,objness`等Tensor，用teacher得到的结果指导student训练。具体实现可参考[代码](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/ppdet/slim/distill.py)
## Citations
```
diff --git a/configs/solov2/README.md b/configs/solov2/README.md
index 037b2f96ce9f04087eed386abe58390857d59c4d..5c2009800e05278a1852eeff717cdfb125ebf03b 100644
--- a/configs/solov2/README.md
+++ b/configs/solov2/README.md
@@ -19,9 +19,9 @@ SOLOv2 (Segmenting Objects by Locations) is a fast instance segmentation framewo
| BlendMask | R50-FPN | True | 3x | 37.8 | 13.5 | V100 | - | - |
| SOLOv2 (Paper) | R50-FPN | False | 1x | 34.8 | 18.5 | V100 | - | - |
| SOLOv2 (Paper) | X101-DCN-FPN | True | 3x | 42.4 | 5.9 | V100 | - | - |
-| SOLOv2 | R50-FPN | False | 1x | 35.5 | 21.9 | V100 | [model](https://paddledet.bj.bcebos.com/models/solov2_r50_fpn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/solov2/solov2_r50_fpn_1x_coco.yml) |
-| SOLOv2 | R50-FPN | True | 3x | 38.0 | 21.9 | V100 | [model](https://paddledet.bj.bcebos.com/models/solov2_r50_fpn_3x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/solov2/solov2_r50_fpn_3x_coco.yml) |
-| SOLOv2 | R101vd-FPN | True | 3x | 42.7 | 12.1 | V100 | [model](https://paddledet.bj.bcebos.com/models/solov2_r101_vd_fpn_3x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/solov2/solov2_r101_vd_fpn_3x_coco.yml) |
+| SOLOv2 | R50-FPN | False | 1x | 35.5 | 21.9 | V100 | [model](https://paddledet.bj.bcebos.com/models/solov2_r50_fpn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/solov2/solov2_r50_fpn_1x_coco.yml) |
+| SOLOv2 | R50-FPN | True | 3x | 38.0 | 21.9 | V100 | [model](https://paddledet.bj.bcebos.com/models/solov2_r50_fpn_3x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/solov2/solov2_r50_fpn_3x_coco.yml) |
+| SOLOv2 | R101vd-FPN | True | 3x | 42.7 | 12.1 | V100 | [model](https://paddledet.bj.bcebos.com/models/solov2_r101_vd_fpn_3x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/solov2/solov2_r101_vd_fpn_3x_coco.yml) |
**Notes:**
@@ -30,7 +30,7 @@ SOLOv2 (Segmenting Objects by Locations) is a fast instance segmentation framewo
## Enhanced model
| Backbone | Input size | Lr schd | V100 FP32(FPS) | Mask APval | Download | Configs |
| :---------------------: | :-------------------: | :-----: | :------------: | :-----: | :---------: | :------------------------: |
-| Light-R50-VD-DCN-FPN | 512 | 3x | 38.6 | 39.0 | [model](https://paddledet.bj.bcebos.com/models/solov2_r50_enhance_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/solov2/solov2_r50_enhance_coco.yml) |
+| Light-R50-VD-DCN-FPN | 512 | 3x | 38.6 | 39.0 | [model](https://paddledet.bj.bcebos.com/models/solov2_r50_enhance_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/solov2/solov2_r50_enhance_coco.yml) |
**Optimizing method of enhanced model:**
- Better backbone network: ResNet50vd-DCN
diff --git a/configs/ssd/README.md b/configs/ssd/README.md
index 1ebc458669cfbc60216440c412aa1df7ac62602c..e8e1f206cc7442399536fda95b4abd8e0ef8ca31 100644
--- a/configs/ssd/README.md
+++ b/configs/ssd/README.md
@@ -6,8 +6,8 @@
| 骨架网络 | 网络类型 | 每张GPU图片个数 | 学习率策略 |推理时间(fps) | Box AP | 下载 | 配置文件 |
| :-------------- | :------------- | :-----: | :-----: | :------------: | :-----: | :-----------------------------------------------------: | :-----: |
-| VGG | SSD | 8 | 240e | ---- | 77.8 | [下载链接](https://paddledet.bj.bcebos.com/models/ssd_vgg16_300_240e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ssd/ssd_vgg16_300_240e_voc.yml) |
-| MobileNet v1 | SSD | 32 | 120e | ---- | 73.8 | [下载链接](https://paddledet.bj.bcebos.com/models/ssd_mobilenet_v1_300_120e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ssd/ssd_mobilenet_v1_300_120e_voc.yml) |
+| VGG | SSD | 8 | 240e | ---- | 77.8 | [下载链接](https://paddledet.bj.bcebos.com/models/ssd_vgg16_300_240e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ssd/ssd_vgg16_300_240e_voc.yml) |
+| MobileNet v1 | SSD | 32 | 120e | ---- | 73.8 | [下载链接](https://paddledet.bj.bcebos.com/models/ssd_mobilenet_v1_300_120e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ssd/ssd_mobilenet_v1_300_120e_voc.yml) |
**注意：** SSD-VGG使用4GPU在总batch size为32下训练240个epoch。SSD-MobileNetv1使用2GPU在总batch size为64下训练120周期。
diff --git a/configs/ttfnet/README.md b/configs/ttfnet/README.md
index 6f5a73e0ce8e1ce8430160a1cbdd6ae41d7accdf..267e9b61f5385ad98c4e033c067a52cfffb553aa 100644
--- a/configs/ttfnet/README.md
+++ b/configs/ttfnet/README.md
@@ -13,7 +13,7 @@ TTFNet是一种用于实时目标检测且对训练时间友好的网络，对Ce
| 骨架网络 | 网络类型 | 每张GPU图片个数 | 学习率策略 |推理时间(fps) | Box AP | 下载 | 配置文件 |
| :-------------- | :------------- | :-----: | :-----: | :------------: | :-----: | :-----------------------------------------------------: | :-----: |
-| DarkNet53 | TTFNet | 12 | 1x | ---- | 33.5 | [下载链接](https://paddledet.bj.bcebos.com/models/ttfnet_darknet53_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ttfnet/ttfnet_darknet53_1x_coco.yml) |
+| DarkNet53 | TTFNet | 12 | 1x | ---- | 33.5 | [下载链接](https://paddledet.bj.bcebos.com/models/ttfnet_darknet53_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ttfnet/ttfnet_darknet53_1x_coco.yml) |
@@ -40,7 +40,7 @@ PAFNet系列模型从如下方面优化TTFNet模型：
| 骨架网络 | 网络类型 | 每张GPU图片个数 | 学习率策略 |推理时间(fps) | Box AP | 下载 | 配置文件 |
| :-------------- | :------------- | :-----: | :-----: | :------------: | :-----: | :-----------------------------------------------------: | :-----: |
-| ResNet50vd | PAFNet | 18 | 10x | ---- | 39.8 | [下载链接](https://paddledet.bj.bcebos.com/models/pafnet_10x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ttfnet/pafnet_10x_coco.yml) |
+| ResNet50vd | PAFNet | 18 | 10x | ---- | 39.8 | [下载链接](https://paddledet.bj.bcebos.com/models/pafnet_10x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ttfnet/pafnet_10x_coco.yml) |
@@ -48,7 +48,7 @@ PAFNet系列模型从如下方面优化TTFNet模型：
| 骨架网络 | 网络类型 | 每张GPU图片个数 | 学习率策略 | Box AP | 麒麟990延时（ms） | 体积（M） | 下载 | 配置文件 |
| :-------------- | :------------- | :-----: | :-----: | :-----: | :------------: | :-----: | :-----------------------------------------------------: | :-----: |
-| MobileNetv3 | PAFNet-Lite | 12 | 20x | 23.9 | 26.00 | 14 | [下载链接](https://paddledet.bj.bcebos.com/models/pafnet_lite_mobilenet_v3_20x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ttfnet/pafnet_lite_mobilenet_v3_20x_coco.yml) |
+| MobileNetv3 | PAFNet-Lite | 12 | 20x | 23.9 | 26.00 | 14 | [下载链接](https://paddledet.bj.bcebos.com/models/pafnet_lite_mobilenet_v3_20x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ttfnet/pafnet_lite_mobilenet_v3_20x_coco.yml) |
**注意：** 由于动态图框架整体升级，PAFNet的PaddleDetection发布的权重模型评估时需要添加--bias字段, 例如
diff --git a/configs/vehicle/README.md b/configs/vehicle/README.md
index 5e20c6ffa86dcbc6e7d9fa8fbf57a9ae98eccb74..572e8422e0628ea6c2870a695392b5d07049c3ea 100644
--- a/configs/vehicle/README.md
+++ b/configs/vehicle/README.md
@@ -5,7 +5,7 @@ We provide some models implemented by PaddlePaddle to detect objects in specific
| Task | Algorithm | Box AP | Download | Configs |
|:---------------------|:---------:|:------:| :-------------------------------------------------------------------------------------: |:------:|
-| Vehicle Detection | YOLOv3 | 54.5 | [model](https://paddledet.bj.bcebos.com/models/vehicle_yolov3_darknet.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/vehicle/vehicle_yolov3_darknet.yml) |
+| Vehicle Detection | YOLOv3 | 54.5 | [model](https://paddledet.bj.bcebos.com/models/vehicle_yolov3_darknet.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/vehicle/vehicle_yolov3_darknet.yml) |
## Vehicle Detection
@@ -17,7 +17,7 @@ The network for detecting vehicles is YOLOv3, the backbone of which is Dacknet53
### 2. Configuration for training
-PaddleDetection provides users with a configuration file [yolov3_darknet53_270e_coco.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/yolov3/yolov3_darknet53_270e_coco.yml) to train YOLOv3 on the COCO dataset, compared with this file, we modify some parameters as followed to conduct the training for vehicle detection:
+PaddleDetection provides users with a configuration file [yolov3_darknet53_270e_coco.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.2/configs/yolov3/yolov3_darknet53_270e_coco.yml) to train YOLOv3 on the COCO dataset, compared with this file, we modify some parameters as followed to conduct the training for vehicle detection:
* num_classes: 6
* anchors: [[8, 9], [10, 23], [19, 15], [23, 33], [40, 25], [54, 50], [101, 80], [139, 145], [253, 224]]
diff --git a/configs/vehicle/README_cn.md b/configs/vehicle/README_cn.md
index 2bd09bb10bb4ab6e56f15fb4411ecd012249b677..ef3f88aea57e8a7d4b309974e16f2e5a84edcb96 100644
--- a/configs/vehicle/README_cn.md
+++ b/configs/vehicle/README_cn.md
@@ -5,7 +5,7 @@
| 任务 | 算法 | 精度(Box AP) | 下载 | 配置文件 |
|:---------------------|:---------:|:------:| :---------------------------------------------------------------------------------: | :------:|
-| 车辆检测 | YOLOv3 | 54.5 | [下载链接](https://paddledet.bj.bcebos.com/models/vehicle_yolov3_darknet.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/vehicle/vehicle_yolov3_darknet.yml) |
+| 车辆检测 | YOLOv3 | 54.5 | [下载链接](https://paddledet.bj.bcebos.com/models/vehicle_yolov3_darknet.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/vehicle/vehicle_yolov3_darknet.yml) |
## 车辆检测（Vehicle Detection）
@@ -18,7 +18,7 @@ Backbone为Dacknet53的YOLOv3。
### 2. 训练参数配置
-PaddleDetection提供了使用COCO数据集对YOLOv3进行训练的参数配置文件[yolov3_darknet53_270e_coco.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/yolov3/yolov3_darknet53_270e_coco.yml)，与之相比，在进行车辆检测的模型训练时，我们对以下参数进行了修改：
+PaddleDetection提供了使用COCO数据集对YOLOv3进行训练的参数配置文件[yolov3_darknet53_270e_coco.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.2/configs/yolov3/yolov3_darknet53_270e_coco.yml)，与之相比，在进行车辆检测的模型训练时，我们对以下参数进行了修改：
* num_classes: 6
* anchors: [[8, 9], [10, 23], [19, 15], [23, 33], [40, 25], [54, 50], [101, 80], [139, 145], [253, 224]]
diff --git a/configs/yolov3/README.md b/configs/yolov3/README.md
index af4d07ce13d8e2ac6bf81d40ac4d25f5ab2061b3..d67f71cb3c2bc1a03c04272b4e11d0af822f09f7 100644
--- a/configs/yolov3/README.md
+++ b/configs/yolov3/README.md
@@ -9,41 +9,41 @@
| DarkNet53(paper) | 608 | 8 | 270e | ---- | 33.0 | - | - |
| DarkNet53(paper) | 416 | 8 | 270e | ---- | 31.0 | - | - |
| DarkNet53(paper) | 320 | 8 | 270e | ---- | 28.2 | - | - |
-| DarkNet53 | 608 | 8 | 270e | ---- | 39.0 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_darknet53_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_darknet53_270e_coco.yml) |
-| DarkNet53 | 416 | 8 | 270e | ---- | 37.5 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_darknet53_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_darknet53_270e_coco.yml) |
-| DarkNet53 | 320 | 8 | 270e | ---- | 34.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_darknet53_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_darknet53_270e_coco.yml) |
-| ResNet50_vd | 608 | 8 | 270e | ---- | 39.1 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_r50vd_dcn_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_r50vd_dcn_270e_coco.yml) |
-| ResNet50_vd | 416 | 8 | 270e | ---- | 36.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_r50vd_dcn_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_r50vd_dcn_270e_coco.yml) |
-| ResNet50_vd | 320 | 8 | 270e | ---- | 33.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_r50vd_dcn_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_r50vd_dcn_270e_coco.yml) |
-| ResNet34 | 608 | 8 | 270e | ---- | 36.2 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_r34_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_r34_270e_coco.yml) |
-| ResNet34 | 416 | 8 | 270e | ---- | 34.3 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_r34_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_r34_270e_coco.yml) |
-| ResNet34 | 320 | 8 | 270e | ---- | 31.2 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_r34_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_r34_270e_coco.yml) |
-| MobileNet-V1 | 608 | 8 | 270e | ---- | 29.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) |
-| MobileNet-V1 | 416 | 8 | 270e | ---- | 29.3 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) |
-| MobileNet-V1 | 320 | 8 | 270e | ---- | 27.2 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) |
-| MobileNet-V3 | 608 | 8 | 270e | ---- | 31.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_270e_coco.yml) |
-| MobileNet-V3 | 416 | 8 | 270e | ---- | 29.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_270e_coco.yml) |
-| MobileNet-V3 | 320 | 8 | 270e | ---- | 27.1 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_270e_coco.yml) |
-| MobileNet-V1-SSLD | 608 | 8 | 270e | ---- | 31.0 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_coco.yml) |
-| MobileNet-V1-SSLD | 416 | 8 | 270e | ---- | 30.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_coco.yml) |
-| MobileNet-V1-SSLD | 320 | 8 | 270e | ---- | 28.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_coco.yml) |
+| DarkNet53 | 608 | 8 | 270e | ---- | 39.0 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_darknet53_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_darknet53_270e_coco.yml) |
+| DarkNet53 | 416 | 8 | 270e | ---- | 37.5 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_darknet53_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_darknet53_270e_coco.yml) |
+| DarkNet53 | 320 | 8 | 270e | ---- | 34.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_darknet53_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_darknet53_270e_coco.yml) |
+| ResNet50_vd | 608 | 8 | 270e | ---- | 39.1 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_r50vd_dcn_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_r50vd_dcn_270e_coco.yml) |
+| ResNet50_vd | 416 | 8 | 270e | ---- | 36.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_r50vd_dcn_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_r50vd_dcn_270e_coco.yml) |
+| ResNet50_vd | 320 | 8 | 270e | ---- | 33.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_r50vd_dcn_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_r50vd_dcn_270e_coco.yml) |
+| ResNet34 | 608 | 8 | 270e | ---- | 36.2 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_r34_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_r34_270e_coco.yml) |
+| ResNet34 | 416 | 8 | 270e | ---- | 34.3 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_r34_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_r34_270e_coco.yml) |
+| ResNet34 | 320 | 8 | 270e | ---- | 31.2 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_r34_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_r34_270e_coco.yml) |
+| MobileNet-V1 | 608 | 8 | 270e | ---- | 29.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) |
+| MobileNet-V1 | 416 | 8 | 270e | ---- | 29.3 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) |
+| MobileNet-V1 | 320 | 8 | 270e | ---- | 27.2 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml) |
+| MobileNet-V3 | 608 | 8 | 270e | ---- | 31.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v3_large_270e_coco.yml) |
+| MobileNet-V3 | 416 | 8 | 270e | ---- | 29.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v3_large_270e_coco.yml) |
+| MobileNet-V3 | 320 | 8 | 270e | ---- | 27.1 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v3_large_270e_coco.yml) |
+| MobileNet-V1-SSLD | 608 | 8 | 270e | ---- | 31.0 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_coco.yml) |
+| MobileNet-V1-SSLD | 416 | 8 | 270e | ---- | 30.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_coco.yml) |
+| MobileNet-V1-SSLD | 320 | 8 | 270e | ---- | 28.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_coco.yml) |
### YOLOv3 on Pasacl VOC
| 骨架网络 | 输入尺寸 | 每张GPU图片个数 | 学习率策略 |推理时间(fps)| Box AP | 下载 | 配置文件 |
| :----------- | :--: | :-----: | :-----: |:------------: |:----: | :-------: | :----: |
-| MobileNet-V1 | 608 | 8 | 270e | - | 75.2 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_voc.yml) |
-| MobileNet-V1 | 416 | 8 | 270e | - | 76.2 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_voc.yml) |
-| MobileNet-V1 | 320 | 8 | 270e | - | 74.3 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_270e_voc.yml) |
-| MobileNet-V3 | 608 | 8 | 270e | - | 79.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_270e_voc.yml) |
-| MobileNet-V3 | 416 | 8 | 270e | - | 78.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_270e_voc.yml) |
-| MobileNet-V3 | 320 | 8 | 270e | - | 76.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_270e_voc.yml) |
-| MobileNet-V1-SSLD | 608 | 8 | 270e | - | 78.3 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_voc.yml) |
-| MobileNet-V1-SSLD | 416 | 8 | 270e | - | 79.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_voc.yml) |
-| MobileNet-V1-SSLD | 320 | 8 | 270e | - | 77.3 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_voc.yml) |
-| MobileNet-V3-SSLD | 608 | 8 | 270e | - | 80.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_ssld_270e_voc.yml) |
-| MobileNet-V3-SSLD | 416 | 8 | 270e | - | 79.2 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_ssld_270e_voc.yml) |
-| MobileNet-V3-SSLD | 320 | 8 | 270e | - | 77.3 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_ssld_270e_voc.yml) |
+| MobileNet-V1 | 608 | 8 | 270e | - | 75.2 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v1_270e_voc.yml) |
+| MobileNet-V1 | 416 | 8 | 270e | - | 76.2 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v1_270e_voc.yml) |
+| MobileNet-V1 | 320 | 8 | 270e | - | 74.3 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v1_270e_voc.yml) |
+| MobileNet-V3 | 608 | 8 | 270e | - | 79.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v3_large_270e_voc.yml) |
+| MobileNet-V3 | 416 | 8 | 270e | - | 78.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v3_large_270e_voc.yml) |
+| MobileNet-V3 | 320 | 8 | 270e | - | 76.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v3_large_270e_voc.yml) |
+| MobileNet-V1-SSLD | 608 | 8 | 270e | - | 78.3 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_voc.yml) |
+| MobileNet-V1-SSLD | 416 | 8 | 270e | - | 79.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_voc.yml) |
+| MobileNet-V1-SSLD | 320 | 8 | 270e | - | 77.3 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_voc.yml) |
+| MobileNet-V3-SSLD | 608 | 8 | 270e | - | 80.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v3_large_ssld_270e_voc.yml) |
+| MobileNet-V3-SSLD | 416 | 8 | 270e | - | 79.2 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v3_large_ssld_270e_voc.yml) |
+| MobileNet-V3-SSLD | 320 | 8 | 270e | - | 77.3 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v3_large_ssld_270e_voc.yml) |
**注意：** YOLOv3均使用8GPU训练，训练270个epoch。由于动态图框架整体升级，以下几个PaddleDetection发布的权重模型评估时需要添加--bias字段, 例如
diff --git a/docs/MODEL_ZOO_cn.md b/docs/MODEL_ZOO_cn.md
index 61a5e34377c0797f975e26414cd240d8516827eb..6f80f3dcb81d15dfe5babc0797e68a6b264f7e28 100644
--- a/docs/MODEL_ZOO_cn.md
+++ b/docs/MODEL_ZOO_cn.md
@@ -29,59 +29,59 @@ Paddle提供基于ImageNet的骨架网络预训练模型。所有预训练模型
### Faster R-CNN
-请参考[Faster R-CNN](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/faster_rcnn/)
+请参考[Faster R-CNN](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/faster_rcnn/)
### Mask R-CNN
-请参考[Mask R-CNN](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/)
+请参考[Mask R-CNN](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mask_rcnn/)
### Cascade R-CNN
-请参考[Cascade R-CNN](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/cascade_rcnn)
+请参考[Cascade R-CNN](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/cascade_rcnn)
### YOLOv3
-请参考[YOLOv3](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/)
+请参考[YOLOv3](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/)
### SSD
-请参考[SSD](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ssd/)
+请参考[SSD](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ssd/)
### FCOS
-请参考[FCOS](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/fcos/)
+请参考[FCOS](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/fcos/)
### SOLOv2
-请参考[SOLOv2](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/solov2/)
+请参考[SOLOv2](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/solov2/)
### PP-YOLO
-请参考[PP-YOLO](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ppyolo/)
+请参考[PP-YOLO](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ppyolo/)
### TTFNet
-请参考[TTFNet](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ttfnet/)
+请参考[TTFNet](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/ttfnet/)
### Group Normalization
-请参考[Group Normalization](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/gn/)
+请参考[Group Normalization](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/gn/)
### Deformable ConvNets v2
-请参考[Deformable ConvNets v2](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/dcn/)
+请参考[Deformable ConvNets v2](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/dcn/)
### HRNets
-请参考[HRNets](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/hrnet/)
+请参考[HRNets](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/hrnet/)
### Res2Net
-请参考[Res2Net](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/res2net/)
+请参考[Res2Net](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/res2net/)
## 旋转框检测
### S2ANet
-请参考[S2ANet](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/dota/)
+请参考[S2ANet](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/dota/)
diff --git a/docs/feature_models/SSLD_PRETRAINED_MODEL.md b/docs/feature_models/SSLD_PRETRAINED_MODEL.md
index e27b69a664a5d19624e61caad5cc079d9de8f602..2f649fb561ab34c5619dad47659eb20feef95fdb 100644
--- a/docs/feature_models/SSLD_PRETRAINED_MODEL.md
+++ b/docs/feature_models/SSLD_PRETRAINED_MODEL.md
@@ -6,38 +6,38 @@
| 骨架网络 | 网络类型 | 每张GPU图片个数 | 学习率策略 |推理时间(fps) | Box AP | Mask AP | 下载 | 配置文件 |
| :------------------- | :------------| :-----: | :-----: | :------------: | :-----: | :-----: | :-----------------------------------------------------: | :-----: |
-| ResNet50-vd-SSLDv2-FPN | Faster | 1 | 1x | ---- | 41.4 | - | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/faster_rcnn/faster_rcnn_r50_vd_fpn_ssld_1x_coco.yml) |
-| ResNet50-vd-SSLDv2-FPN | Faster | 1 | 2x | ---- | 42.3 | - | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/faster_rcnn/faster_rcnn_r50_vd_fpn_ssld_2x_coco.yml) |
-| ResNet50-vd-SSLDv2-FPN | Mask | 1 | 1x | ---- | 42.0 | 38.2 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_r50_vd_fpn_ssld_1x_coco.yml) |
-| ResNet50-vd-SSLDv2-FPN | Mask | 1 | 2x | ---- | 42.7 | 38.9 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_r50_vd_fpn_ssld_2x_coco.yml) |
-| ResNet50-vd-SSLDv2-FPN | Cascade Faster | 1 | 1x | ---- | 44.4 | - | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/cascade_rcnn/cascade_rcnn_r50_vd_fpn_ssld_1x_coco.yml) |
-| ResNet50-vd-SSLDv2-FPN | Cascade Faster | 1 | 2x | ---- | 45.0 | - | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/cascade_rcnn/cascade_rcnn_r50_vd_fpn_ssld_2x_coco.yml) |
-| ResNet50-vd-SSLDv2-FPN | Cascade Mask | 1 | 1x | ---- | 44.9 | 39.1 | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_mask_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/cascade_rcnn/cascade_mask_rcnn_r50_vd_fpn_ssld_1x_coco.yml) |
-| ResNet50-vd-SSLDv2-FPN | Cascade Mask | 1 | 2x | ---- | 45.7 | 39.7 | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_mask_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/cascade_rcnn/cascade_mask_rcnn_r50_vd_fpn_ssld_2x_coco.yml) |
+| ResNet50-vd-SSLDv2-FPN | Faster | 1 | 1x | ---- | 41.4 | - | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/faster_rcnn/faster_rcnn_r50_vd_fpn_ssld_1x_coco.yml) |
+| ResNet50-vd-SSLDv2-FPN | Faster | 1 | 2x | ---- | 42.3 | - | [下载链接](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/faster_rcnn/faster_rcnn_r50_vd_fpn_ssld_2x_coco.yml) |
+| ResNet50-vd-SSLDv2-FPN | Mask | 1 | 1x | ---- | 42.0 | 38.2 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mask_rcnn/mask_rcnn_r50_vd_fpn_ssld_1x_coco.yml) |
+| ResNet50-vd-SSLDv2-FPN | Mask | 1 | 2x | ---- | 42.7 | 38.9 | [下载链接](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mask_rcnn/mask_rcnn_r50_vd_fpn_ssld_2x_coco.yml) |
+| ResNet50-vd-SSLDv2-FPN | Cascade Faster | 1 | 1x | ---- | 44.4 | - | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/cascade_rcnn/cascade_rcnn_r50_vd_fpn_ssld_1x_coco.yml) |
+| ResNet50-vd-SSLDv2-FPN | Cascade Faster | 1 | 2x | ---- | 45.0 | - | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/cascade_rcnn/cascade_rcnn_r50_vd_fpn_ssld_2x_coco.yml) |
+| ResNet50-vd-SSLDv2-FPN | Cascade Mask | 1 | 1x | ---- | 44.9 | 39.1 | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_mask_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/cascade_rcnn/cascade_mask_rcnn_r50_vd_fpn_ssld_1x_coco.yml) |
+| ResNet50-vd-SSLDv2-FPN | Cascade Mask | 1 | 2x | ---- | 45.7 | 39.7 | [下载链接](https://paddledet.bj.bcebos.com/models/cascade_mask_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/cascade_rcnn/cascade_mask_rcnn_r50_vd_fpn_ssld_2x_coco.yml) |
### YOLOv3 on COCO
| 骨架网络 | 输入尺寸 | 每张GPU图片个数 | 学习率策略 |推理时间(fps) | Box AP | 下载 | 配置文件 |
| :----------------- | :-------- | :-----------: | :------: | :---------: | :----: | :----------------------------------------------------: | :-----: |
-| MobileNet-V1-SSLD | 608 | 8 | 270e | ---- | 31.0 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_coco.yml) |
-| MobileNet-V1-SSLD | 416 | 8 | 270e | ---- | 30.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_coco.yml) |
-| MobileNet-V1-SSLD | 320 | 8 | 270e | ---- | 28.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_coco.yml) |
+| MobileNet-V1-SSLD | 608 | 8 | 270e | ---- | 31.0 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_coco.yml) |
+| MobileNet-V1-SSLD | 416 | 8 | 270e | ---- | 30.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_coco.yml) |
+| MobileNet-V1-SSLD | 320 | 8 | 270e | ---- | 28.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_coco.yml) |
### YOLOv3 on Pasacl VOC
| 骨架网络 | 输入尺寸 | 每张GPU图片个数 | 学习率策略 |推理时间(fps) | Box AP | 下载 | 配置文件 |
| :----------------- | :-------- | :-----------: | :------: | :---------: | :----: | :----------------------------------------------------: | :-----: |
-| MobileNet-V1-SSLD | 608 | 8 | 270e | - | 78.3 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_voc.yml) |
-| MobileNet-V1-SSLD | 416 | 8 | 270e | - | 79.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_voc.yml) |
-| MobileNet-V1-SSLD | 320 | 8 | 270e | - | 77.3 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_voc.yml) |
-| MobileNet-V3-SSLD | 608 | 8 | 270e | - | 80.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_ssld_270e_voc.yml) |
-| MobileNet-V3-SSLD | 416 | 8 | 270e | - | 79.2 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_ssld_270e_voc.yml) |
-| MobileNet-V3-SSLD | 320 | 8 | 270e | - | 77.3 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_ssld_270e_voc.yml) |
+| MobileNet-V1-SSLD | 608 | 8 | 270e | - | 78.3 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_voc.yml) |
+| MobileNet-V1-SSLD | 416 | 8 | 270e | - | 79.6 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_voc.yml) |
+| MobileNet-V1-SSLD | 320 | 8 | 270e | - | 77.3 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_voc.yml) |
+| MobileNet-V3-SSLD | 608 | 8 | 270e | - | 80.4 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v3_large_ssld_270e_voc.yml) |
+| MobileNet-V3-SSLD | 416 | 8 | 270e | - | 79.2 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v3_large_ssld_270e_voc.yml) |
+| MobileNet-V3-SSLD | 320 | 8 | 270e | - | 77.3 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v3_large_ssld_270e_voc.yml) |
**注意事项:**
-- [SSLD](https://arxiv.org/abs/2103.05959)是一种知识蒸馏方法，我们使用蒸馏后性能更强的backbone预训练模型，进一步提升检测精度，详细方案请参考[知识蒸馏教程](https://github.com/PaddlePaddle/PaddleClas/blob/develop/docs/en/advanced_tutorials/distillation/distillation_en.md)
+- [SSLD](https://arxiv.org/abs/2103.05959)是一种知识蒸馏方法，我们使用蒸馏后性能更强的backbone预训练模型，进一步提升检测精度，详细方案请参考[知识蒸馏教程](https://github.com/PaddlePaddle/PaddleClas/blob/release/2.2/docs/en/advanced_tutorials/distillation/distillation_en.md)
diff --git a/docs/feature_models/SSLD_PRETRAINED_MODEL_en.md b/docs/feature_models/SSLD_PRETRAINED_MODEL_en.md
index b97c3b71ee5b8e439181740ea6d7c1a0d7a6d2ba..16f93107137c84c0291adfbee502ded662acf9a0 100644
--- a/docs/feature_models/SSLD_PRETRAINED_MODEL_en.md
+++ b/docs/feature_models/SSLD_PRETRAINED_MODEL_en.md
@@ -6,37 +6,37 @@ English | [简体中文](SSLD_PRETRAINED_MODEL.md)
| Backbone | Model | Images/GPU | Lr schd | FPS | Box AP | Mask AP | Download | Config |
| :------------------- | :------------| :-----: | :-----: | :------------: | :-----: | :-----: | :-----------------------------------------------------: | :-----: |
-| ResNet50-vd-SSLDv2-FPN | Faster | 1 | 1x | ---- | 41.4 | - | [model](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/faster_rcnn/faster_rcnn_r50_vd_fpn_ssld_1x_coco.yml) |
-| ResNet50-vd-SSLDv2-FPN | Faster | 1 | 2x | ---- | 42.3 | - | [model](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/faster_rcnn/faster_rcnn_r50_vd_fpn_ssld_2x_coco.yml) |
-| ResNet50-vd-SSLDv2-FPN | Mask | 1 | 1x | ---- | 42.0 | 38.2 | [model](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_r50_vd_fpn_ssld_1x_coco.yml) |
-| ResNet50-vd-SSLDv2-FPN | Mask | 1 | 2x | ---- | 42.7 | 38.9 | [model](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/mask_rcnn/mask_rcnn_r50_vd_fpn_ssld_2x_coco.yml) |
-| ResNet50-vd-SSLDv2-FPN | Cascade Faster | 1 | 1x | ---- | 44.4 | - | [model](https://paddledet.bj.bcebos.com/models/cascade_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/cascade_rcnn/cascade_rcnn_r50_vd_fpn_ssld_1x_coco.yml) |
-| ResNet50-vd-SSLDv2-FPN | Cascade Faster | 1 | 2x | ---- | 45.0 | - | [model](https://paddledet.bj.bcebos.com/models/cascade_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/cascade_rcnn/cascade_rcnn_r50_vd_fpn_ssld_2x_coco.yml) |
-| ResNet50-vd-SSLDv2-FPN | Cascade Mask | 1 | 1x | ---- | 44.9 | 39.1 | [model](https://paddledet.bj.bcebos.com/models/cascade_mask_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/cascade_rcnn/cascade_mask_rcnn_r50_vd_fpn_ssld_1x_coco.yml) |
-| ResNet50-vd-SSLDv2-FPN | Cascade Mask | 1 | 2x | ---- | 45.7 | 39.7 | [model](https://paddledet.bj.bcebos.com/models/cascade_mask_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/cascade_rcnn/cascade_mask_rcnn_r50_vd_fpn_ssld_2x_coco.yml) |
+| ResNet50-vd-SSLDv2-FPN | Faster | 1 | 1x | ---- | 41.4 | - | [model](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/faster_rcnn/faster_rcnn_r50_vd_fpn_ssld_1x_coco.yml) |
+| ResNet50-vd-SSLDv2-FPN | Faster | 1 | 2x | ---- | 42.3 | - | [model](https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/faster_rcnn/faster_rcnn_r50_vd_fpn_ssld_2x_coco.yml) |
+| ResNet50-vd-SSLDv2-FPN | Mask | 1 | 1x | ---- | 42.0 | 38.2 | [model](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mask_rcnn/mask_rcnn_r50_vd_fpn_ssld_1x_coco.yml) |
+| ResNet50-vd-SSLDv2-FPN | Mask | 1 | 2x | ---- | 42.7 | 38.9 | [model](https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mask_rcnn/mask_rcnn_r50_vd_fpn_ssld_2x_coco.yml) |
+| ResNet50-vd-SSLDv2-FPN | Cascade Faster | 1 | 1x | ---- | 44.4 | - | [model](https://paddledet.bj.bcebos.com/models/cascade_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/cascade_rcnn/cascade_rcnn_r50_vd_fpn_ssld_1x_coco.yml) |
+| ResNet50-vd-SSLDv2-FPN | Cascade Faster | 1 | 2x | ---- | 45.0 | - | [model](https://paddledet.bj.bcebos.com/models/cascade_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/cascade_rcnn/cascade_rcnn_r50_vd_fpn_ssld_2x_coco.yml) |
+| ResNet50-vd-SSLDv2-FPN | Cascade Mask | 1 | 1x | ---- | 44.9 | 39.1 | [model](https://paddledet.bj.bcebos.com/models/cascade_mask_rcnn_r50_vd_fpn_ssld_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/cascade_rcnn/cascade_mask_rcnn_r50_vd_fpn_ssld_1x_coco.yml) |
+| ResNet50-vd-SSLDv2-FPN | Cascade Mask | 1 | 2x | ---- | 45.7 | 39.7 | [model](https://paddledet.bj.bcebos.com/models/cascade_mask_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/cascade_rcnn/cascade_mask_rcnn_r50_vd_fpn_ssld_2x_coco.yml) |
### YOLOv3 on COCO
| Backbone | Input shape | Images/GPU | Lr schd | FPS | Box AP | Download | Config |
| :----------------- | :-------- | :-----------: | :------: | :---------: | :----: | :----------------------------------------------------: | :-----: |
-| MobileNet-V1-SSLD | 608 | 8 | 270e | ---- | 31.0 | [model](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_coco.yml) |
-| MobileNet-V1-SSLD | 416 | 8 | 270e | ---- | 30.6 | [model](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_coco.yml) |
-| MobileNet-V1-SSLD | 320 | 8 | 270e | ---- | 28.4 | [model](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_coco.yml) |
+| MobileNet-V1-SSLD | 608 | 8 | 270e | ---- | 31.0 | [model](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_coco.yml) |
+| MobileNet-V1-SSLD | 416 | 8 | 270e | ---- | 30.6 | [model](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_coco.yml) |
+| MobileNet-V1-SSLD | 320 | 8 | 270e | ---- | 28.4 | [model](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_coco.yml) |
### YOLOv3 on Pasacl VOC
| Backbone | Input shape | Images/GPU | Lr schd | FPS | Box AP | Download | Config |
| :----------------- | :-------- | :-----------: | :------: | :---------: | :----: | :----------------------------------------------------: | :-----: |
-| MobileNet-V1-SSLD | 608 | 8 | 270e | - | 78.3 | [model](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_voc.yml) |
-| MobileNet-V1-SSLD | 416 | 8 | 270e | - | 79.6 | [model](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_voc.yml) |
-| MobileNet-V1-SSLD | 320 | 8 | 270e | - | 77.3 | [model](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_voc.yml) |
-| MobileNet-V3-SSLD | 608 | 8 | 270e | - | 80.4 | [model](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_ssld_270e_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_ssld_270e_voc.yml) |
-| MobileNet-V3-SSLD | 416 | 8 | 270e | - | 79.2 | [model](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_ssld_270e_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_ssld_270e_voc.yml) |
-| MobileNet-V3-SSLD | 320 | 8 | 270e | - | 77.3 | [model](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_ssld_270e_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_ssld_270e_voc.yml) |
+| MobileNet-V1-SSLD | 608 | 8 | 270e | - | 78.3 | [model](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_voc.yml) |
+| MobileNet-V1-SSLD | 416 | 8 | 270e | - | 79.6 | [model](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_voc.yml) |
+| MobileNet-V1-SSLD | 320 | 8 | 270e | - | 77.3 | [model](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_voc.yml) |
+| MobileNet-V3-SSLD | 608 | 8 | 270e | - | 80.4 | [model](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_ssld_270e_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v3_large_ssld_270e_voc.yml) |
+| MobileNet-V3-SSLD | 416 | 8 | 270e | - | 79.2 | [model](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_ssld_270e_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v3_large_ssld_270e_voc.yml) |
+| MobileNet-V3-SSLD | 320 | 8 | 270e | - | 77.3 | [model](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_ssld_270e_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/yolov3/yolov3_mobilenet_v3_large_ssld_270e_voc.yml) |
**Notes:**
-- [SSLD](https://arxiv.org/abs/2103.05959) is a knowledge distillation method. We use the stronger backbone pretrained model after distillation to further improve the detection accuracy. Please refer to the [knowledge distillation tutorial](https://github.com/PaddlePaddle/PaddleClas/blob/develop/docs/en/advanced_tutorials/distillation/distillation_en.md).
+- [SSLD](https://arxiv.org/abs/2103.05959) is a knowledge distillation method. We use the stronger backbone pretrained model after distillation to further improve the detection accuracy. Please refer to the [knowledge distillation tutorial](https://github.com/PaddlePaddle/PaddleClas/blob/release/2.2/docs/en/advanced_tutorials/distillation/distillation_en.md).
diff --git a/docs/tutorials/INSTALL.md b/docs/tutorials/INSTALL.md
index a9903151f9d61b58edc93bdafd808072a1982c20..38be706d467e7e323c855ea08c003a8806a25e26 100644
--- a/docs/tutorials/INSTALL.md
+++ b/docs/tutorials/INSTALL.md
@@ -6,7 +6,7 @@ English | [简体中文](INSTALL_cn.md)
This document covers how to install PaddleDetection and its dependencies
(including PaddlePaddle), together with COCO and Pascal VOC dataset.
-For general information about PaddleDetection, please see [README.md](https://github.com/PaddlePaddle/PaddleDetection/tree/develop).
+For general information about PaddleDetection, please see [README.md](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2).
## Requirements: