add 2.0rc changelog (PaddlePaddle#2254)

heavengate · Feb 23, 2021 · 1a66a9d · 1a66a9d
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diff --git a/README_cn.md b/README_cn.md
@@ -250,7 +250,7 @@ PaddleDetection模块化地实现了多种主流目标检测算法，提供了
 - [使用SSD-MobileNetv1完成一个项目--准备数据集到完成树莓派部署](https://github.com/PaddleCV-FAQ/PaddleDetection-FAQ/blob/main/Lite%E9%83%A8%E7%BD%B2/ssd_mobilenet_v1_for_raspi.md)
 
 ## 版本更新
-v0.5.0版本已经在`11/2020`发布，增加SOLOv2等多个模型，新增Android移动端Demo，新增PACT量化策略，新增目标检测全流程和Jetson平台部署等教程，提升易用性，修复已知诸多bug等，详细内容请参考[版本更新文档](docs/CHANGELOG.md)。
+v2.0-rc版本已经在`02/2021`发布，新增动态图版本，支持RCNN, YOLOv3, PP-YOLO, SSD/SSDLite, FCOS, TTFNet, SOLOv2等系列模型，支持模型剪裁和量化，支持预测部署及TensorRT推理加速，详细内容请参考[版本更新文档](docs/CHANGELOG.md)。
 
 ## 许可证书
 本项目的发布受[Apache 2.0 license](LICENSE)许可认证。

diff --git a/README_en.md b/README_en.md
@@ -260,7 +260,7 @@ All these models can be get in [Model Zoo](#ModelZoo)
 
 ## Updates
 
-v0.5.0 was released at `11/2020`, add SOLOv2, etc. And add Android mobile demo, add PACT quantization strategy, add object detection full-process documentation and Jetson platform deployment tutorials, and improved ease of use, fix many known bugs, etc. Please refer to [change log](docs/CHANGELOG.md) for details.
+v2.0-rc was released at `02/2021`, add dygraph version, which supports RCNN, YOLOv3, PP-YOLO, SSD/SSDLite, FCOS, TTFNet, SOLOv2, etc. supports model pruning and quantization, supports deploying and accelerating by TensorRT, etc. Please refer to [change log](docs/CHANGELOG.md) for details.
 
 
 ## License

diff --git a/docs/CHANGELOG.md b/docs/CHANGELOG.md
@@ -2,6 +2,31 @@
 
 ## 最新版本信息
 
+### 2.0-rc(02.23/2021)
+  - 动态图模型丰富度提升：
+    - 优化RCNN模型组网及训练方式，RCNN系列模型精度提升(依赖Paddle develop或2.0.1版本)
+    - 新增支持SSDLite，FCOS，TTFNet，SOLOv2系列模型
+    - 新增行人和车辆垂类目标检测模型
+
+  - 新增动态图基础模块：
+    - 新增MobileNetV3，HRNet骨干网络
+    - 优化RoIAlign计算逻辑，RCNN系列模型精度提升(依赖Paddle develop或2.0.1版本)
+    - 新增支持Synchronized Batch Norm
+    - 新增支持Modulated Deformable Convolution
+
+  - 预测部署：
+    - 发布动态图python、C++、Serving部署解决方案及文档，支持Faster RCNN，Mask RCNN，YOLOv3，PP-YOLO，SSD，TTFNet，FCOS，SOLOv2等系列模型预测部署
+    - 动态图预测部署支持TensorRT模式FP32，FP16推理加速
+
+  - 检测模型压缩：
+    - 裁剪：新增动态图裁剪支持，并发布YOLOv3-MobileNetV1裁剪模型
+    - 量化：新增动态图量化支持，并发布YOLOv3-MobileNetV1和YOLOv3-MobileNetV3量化模型
+
+  - 文档：
+    - 新增动态图入门教程文档：包含安装说明，快速开始，准备数据，训练/评估/预测流程文档
+    - 新增动态图进阶教程文档：包含模型压缩、推理部署文档
+    - 新增动态图模型库文档
+
 ### v2.0-beta(12.20/2020)
   - 动态图支持:
     - 支持Faster-RCNN, Mask-RCNN, FPN, Cascade Faster/Mask RCNN, YOLOv3和SSD模型，试用版本。

diff --git a/dygraph/configs/cascade_rcnn/README.md b/dygraph/configs/cascade_rcnn/README.md
@@ -7,6 +7,8 @@
 | 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/master/dygraph/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/master/dygraph/configs/cascade_rcnn/cascade_mask_rcnn_r50_fpn_1x_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。
+
 ## Citations
 ```
 @article{Cai_2019,

diff --git a/dygraph/configs/faster_rcnn/README.md b/dygraph/configs/faster_rcnn/README.md
@@ -19,6 +19,8 @@
 | 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/master/dygraph/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/master/dygraph/configs/faster_rcnn/faster_rcnn_x101_vd_64x4d_fpn_2x_coco.yml) |
 
+**注意：** Faster 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。
+
 ## Citations
 ```
 @article{Ren_2017,

diff --git a/dygraph/configs/fcos/README.md b/dygraph/configs/fcos/README.md
@@ -19,6 +19,7 @@ FCOS (Fully Convolutional One-Stage Object Detection) is a fast anchor-free obje
 **Notes:**
 
 - FCOS is trained on COCO train2017 dataset and evaluated on val2017 results of `mAP(IoU=0.5:0.95)`.
+- FCOS training performace is dependented on Paddle develop branch, performance reproduction shoule based on [Paddle daily version](https://www.paddlepaddle.org.cn/documentation/docs/zh/install/Tables.html#whl-dev) or Paddle 2.0.1(will be published on 2021.03), performace will loss slightly is training base on Paddle 2.0.0
 
 ## Citations
 ```

diff --git a/dygraph/configs/mask_rcnn/README.md b/dygraph/configs/mask_rcnn/README.md
@@ -15,6 +15,8 @@
 | 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/master/dygraph/configs/mask_rcnn/mask_rcnn_x101_vd_64x4d_fpn_1x_coco.yml) |
 | ResNeXt101-vd-FPN        | Mask         |    1    |   2x    |     ----     |  -  |    -   | [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/master/dygraph/configs/mask_rcnn/mask_rcnn_x101_vd_64x4d_fpn_2x_coco.yml) |
 
+**注意：** Mask 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。
+
 ## Citations
 ```
 @article{He_2017,

diff --git a/dygraph/configs/solov2/README.md b/dygraph/configs/solov2/README.md
@@ -25,6 +25,7 @@ SOLOv2 (Segmenting Objects by Locations) is a fast instance segmentation framewo
 **Notes:**
 
 - SOLOv2 is trained on COCO train2017 dataset and evaluated on val2017 results of `mAP(IoU=0.5:0.95)`.
+- SOLOv2 training performace is dependented on Paddle develop branch, performance reproduction shoule based on [Paddle daily version](https://www.paddlepaddle.org.cn/documentation/docs/zh/install/Tables.html#whl-dev) or Paddle 2.0.1(will be published on 2021.03), performace will loss slightly is training base on Paddle 2.0.0
 
 ## Citations
 ```