update readme (#5718)

configs/picodet/README.md

@@ -7,9 +7,9 @@
 ## 最新动态
 
 - 发布全新系列PP-PicoDet模型：**（2022.03.20）**
-  - (1)引入TAL及ETA Head，优化PAN等结构，精度大幅提升；
-  - (2)优化CPU端预测速度，同时训练速度大幅提升；
-  - (3)导出模型将后处理包含在网络中，预测直接输出box结果，无需二次开发，迁移成本更低。
+  - (1)引入TAL及ETA Head，优化PAN等结构，精度提升2个点以上；
+  - (2)优化CPU端预测速度，同时训练速度提升一倍；
+  - (3)导出模型将后处理包含在网络中，预测直接输出box结果，无需二次开发，迁移成本更低，端到端预测速度提升10%-20%。
 
 ## 历史版本模型
 
@@ -33,7 +33,7 @@ PP-PicoDet模型有如下特点：
 
 ## 基线
 
-| 模型     | 输入尺寸 | mAP<sup>val<br>0.5:0.95 | mAP<sup>val<br>0.5 | 参数量<br><sup>(M) | FLOPS<br><sup>(G) | 预测时延<sup><small>[CPU](#latency)</small><sup><br><sup>(ms) | 预测时延<sup><small>[Lite](#latency)</small><sup><br><sup>(ms) |  下载  | 配置文件 | 导出模型  |
+| 模型     | 输入尺寸 | mAP<sup>val<br>0.5:0.95 | mAP<sup>val<br>0.5 | 参数量<br><sup>(M) | FLOPS<br><sup>(G) | 预测时延<sup><small>[CPU](#latency)</small><sup><br><sup>(ms) | 预测时延<sup><small>[Lite](#latency)</small><sup><br><sup>(ms) |  权重下载  | 配置文件 | 导出模型  |
 | :-------- | :--------: | :---------------------: | :----------------: | :----------------: | :---------------: | :-----------------------------: | :-----------------------------: | :----------------------------------------: | :--------------------------------------- | :--------------------------------------- |
 | PicoDet-XS |  320*320   |          23.5           |        36.1       |        0.70        |       0.67        |              3.9ms              |            7.81ms             | [model](https://paddledet.bj.bcebos.com/models/picodet_xs_320_coco_lcnet.pdparams) &#124; [log](https://paddledet.bj.bcebos.com/logs/train_picodet_xs_320_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.4/configs/picodet/picodet_xs_320_coco_lcnet.yml) | [w/ 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_xs_320_coco_lcnet.tar) &#124; [w/o 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_xs_320_coco_lcnet_non_postprocess.tar) |
 | PicoDet-XS |  416*416   |          26.2           |        39.3        |        0.70        |       1.13        |              6.1ms             |            12.38ms             | [model](https://paddledet.bj.bcebos.com/models/picodet_xs_416_coco_lcnet.pdparams) &#124; [log](https://paddledet.bj.bcebos.com/logs/train_picodet_xs_416_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.4/configs/picodet/picodet_xs_416_coco_lcnet.yml) | [w/ 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_xs_416_coco_lcnet.tar) &#124; [w/o 后处理](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_xs_416_coco_lcnet_non_postprocess.tar) |
@@ -48,7 +48,7 @@ PP-PicoDet模型有如下特点：
 <details open>
 <summary><b>注意事项:</b></summary>
 
-- <a name="latency">时延测试：</a> 我们所有的模型都在英特尔酷睿i7 10750H 的CPU 和`骁龙865(4xA77+4xA55)`的ARM CPU上测试(4线程，FP16预测)。上面表格中标有`CPU`的是使用OpenVINO测试，标有`Lite`的是使用[Paddle Lite](https://github.com/PaddlePaddle/Paddle-Lite)进行测试。
+- <a name="latency">时延测试：</a> 我们所有的模型都在`英特尔酷睿i7 10750H`的CPU 和`骁龙865(4xA77+4xA55)`的ARM CPU上测试(4线程，FP16预测)。上面表格中标有`CPU`的是使用OpenVINO测试，标有`Lite`的是使用[Paddle Lite](https://github.com/PaddlePaddle/Paddle-Lite)进行测试。
 - PicoDet在COCO train2017上训练，并且在COCO val2017上进行验证。使用4卡GPU训练，并且上表所有的预训练模型都是通过发布的默认配置训练得到。
 - Benchmark测试：测试速度benchmark性能时，导出模型后处理不包含在网络中，需要设置`-o export.benchmark=True` 或手动修改[runtime.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.4/configs/runtime.yml#L12)。
 
@@ -107,10 +107,12 @@ python tools/train.py -c configs/picodet/picodet_s_320_coco_lcnet.yml --eval
 
 ```shell
 # training on multi-GPU
-export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
-python -m paddle.distributed.launch --gpus 0,1,2,3,4,5,6,7 tools/train.py -c configs/picodet/picodet_s_320_coco_lcnet.yml --eval
+export CUDA_VISIBLE_DEVICES=0,1,2,3
+python -m paddle.distributed.launch --gpus 0,1,2,3 tools/train.py -c configs/picodet/picodet_s_320_coco_lcnet.yml --eval
 ```
 
+**注意：**PicoDet所有模型均由4卡GPU训练得到，如果改变训练GPU卡数，需要按线性比例缩放学习率base_lr。
+
 - 评估:
 
 ```shell
@@ -134,8 +136,8 @@ python tools/infer.py -c configs/picodet/picodet_s_320_coco_lcnet.yml \
 
 ### 导出及转换模型
 
-<details>
-<summary>1. 导出模型 (点击展开)</summary>
+<details open>
+<summary>1. 导出模型</summary>
 
 ```shell
 cd PaddleDetection
@@ -145,7 +147,7 @@ python tools/export_model.py -c configs/picodet/picodet_s_320_coco_lcnet.yml \
 ```
 
 - 如无需导出后处理，请指定：`-o export.benchmark=True`（如果-o已出现过，此处删掉-o）或者手动修改[runtime.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.4/configs/runtime.yml) 中相应字段。
-- 如无需导出NMS，请指定：`-o export.nms=False`或者手动修改[runtime.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.4/configs/runtime.yml) 中相应字段。
+- 如无需导出NMS，请指定：`-o export.nms=False`或者手动修改[runtime.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.4/configs/runtime.yml) 中相应字段。许多导出至ONNX场景只支持单输入及固定shape输出，所以如果导出至ONNX，推荐不导出NMS。
 
 </details>
 
@@ -200,28 +202,34 @@ paddle2onnx --model_dir output_inference/picodet_s_320_coco_lcnet/ \
   python -m onnxsim picodet_s_320_coco.onnx picodet_s_processed.onnx
   ```
 
+  如果模型包含所有后处理，简化模型时需要指定`dynamic-input-shape`：
+  ```shell
+  python -m onnxsim picodet_s_320_coco.onnx picodet_s_processed.onnx --dynamic-input-shape --input-shape image:1,3,320,320
+  ```
+
 </details>
 
 - 部署用的模型
 
 | 模型     | 输入尺寸 | ONNX( w/o 后处理)  | Paddle Lite(fp32) | Paddle Lite(fp16) |
 | :-------- | :--------: | :---------------------: | :----------------: | :----------------: |
-| PicoDet-XS |  320*320   | [( w/ 后处理)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_xs_320_lcnet_postprocessed.onnx) &#124; [( w/o 后处理)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_xs_320_coco_lcnet.onnx) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_xs_320.tar) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_xs_320_fp16.tar) |
-| PicoDet-XS |  416*416   | [( w/ 后处理)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_xs_416_lcnet_postprocessed.onnx) &#124; [( w/o 后处理)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_xs_416_coco_lcnet.onnx) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_xs_416.tar) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_xs_416_fp16.tar) |
-| PicoDet-S |  320*320   | [( w/ 后处理)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_s_320_lcnet_postprocessed.onnx) &#124; [( w/o 后处理)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_s_320_coco_lcnet.onnx) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_s_320.tar) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_s_320_fp16.tar) |
-| PicoDet-S |  416*416   |  [( w/ 后处理)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_s_416_lcnet_postprocessed.onnx) &#124; [( w/o 后处理)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_s_416_coco_lcnet.onnx) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_s_416.tar) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_s_416_fp16.tar) |
-| PicoDet-M |  320*320   | [( w/ 后处理)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_m_320_lcnet_postprocessed.onnx) &#124; [( w/o 后处理)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_m_320_coco_lcnet.onnx) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_m_320.tar) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_m_320_fp16.tar) |
-| PicoDet-M |  416*416   | [( w/ 后处理)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_m_416_lcnet_postprocessed.onnx) &#124; [( w/o 后处理)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_m_416_coco_lcnet.onnx) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_m_416.tar) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_m_416_fp16.tar) |
-| PicoDet-L |  320*320   | [( w/ 后处理)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_l_320_lcnet_postprocessed.onnx) &#124; [( w/o 后处理)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_l_320_coco_lcnet.onnx) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_l_320.tar) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_l_320_fp16.tar) |
-| PicoDet-L |  416*416   | [( w/ 后处理)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_l_416_lcnet_postprocessed.onnx) &#124; [( w/o 后处理)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_l_416_coco_lcnet.onnx) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_l_416.tar) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_l_416_fp16.tar) |
-| PicoDet-L |  640*640   | [( w/ 后处理)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_l_640_lcnet_postprocessed.onnx) &#124; [( w/o 后处理)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_l_640_coco_lcnet.onnx) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_l_640.tar) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_l_640_fp16.tar) |
+| PicoDet-XS |  320*320   | [( w/ 后处理)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_xs_320_lcnet_postprocessed.onnx) &#124; [( w/o 后处理)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_xs_320_coco_lcnet.onnx) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_xs_320_coco_lcnet.tar) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_xs_320_coco_lcnet_fp16.tar) |
+| PicoDet-XS |  416*416   | [( w/ 后处理)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_xs_416_lcnet_postprocessed.onnx) &#124; [( w/o 后处理)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_xs_416_coco_lcnet.onnx) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_xs_416_coco_lcnet.tar) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_xs_416_coco_lcnet_fp16.tar) |
+| PicoDet-S |  320*320   | [( w/ 后处理)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_s_320_lcnet_postprocessed.onnx) &#124; [( w/o 后处理)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_s_320_coco_lcnet.onnx) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_s_320_coco_lcnet.tar) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_s_320_coco_lcnet_fp16.tar) |
+| PicoDet-S |  416*416   |  [( w/ 后处理)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_s_416_lcnet_postprocessed.onnx) &#124; [( w/o 后处理)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_s_416_coco_lcnet.onnx) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_s_416_coco_lcnet.tar) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_s_416_coco_lcnet_fp16.tar) |
+| PicoDet-M |  320*320   | [( w/ 后处理)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_m_320_lcnet_postprocessed.onnx) &#124; [( w/o 后处理)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_m_320_coco_lcnet.onnx) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_m_320_coco_lcnet.tar) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_m_320_coco_lcnet_fp16.tar) |
+| PicoDet-M |  416*416   | [( w/ 后处理)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_m_416_lcnet_postprocessed.onnx) &#124; [( w/o 后处理)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_m_416_coco_lcnet.onnx) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_m_416_coco_lcnet.tar) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_m_416_coco_lcnet_fp16.tar) |
+| PicoDet-L |  320*320   | [( w/ 后处理)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_l_320_lcnet_postprocessed.onnx) &#124; [( w/o 后处理)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_l_320_coco_lcnet.onnx) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_l_320_coco_lcnet.tar) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_l_320_coco_lcnet_fp16.tar) |
+| PicoDet-L |  416*416   | [( w/ 后处理)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_l_416_lcnet_postprocessed.onnx) &#124; [( w/o 后处理)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_l_416_coco_lcnet.onnx) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_l_416_coco_lcnet.tar) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_l_416_coco_lcnet_fp16.tar) |
+| PicoDet-L |  640*640   | [( w/ 后处理)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_l_640_lcnet_postprocessed.onnx) &#124; [( w/o 后处理)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_l_640_coco_lcnet.onnx) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_l_640_coco_lcnet.tar) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_l_640_coco_lcnet_fp16.tar) |
 
 
 ### 部署
 
-- OpenVINO demo [Python](../../deploy/third_engine/demo/openvino/python)
+- OpenVINO demo [Python](../../deploy/third_engine/demo_openvino/python)
 - [PaddleLite C++ demo](../../deploy/lite)
 - [Android demo(Paddle Lite)](https://github.com/PaddlePaddle/Paddle-Lite-Demo/tree/develop/object_detection/android/app/cxx/picodet_detection_demo)
+- ONNXRuntime demo [Python](../../deploy/third_engine/demo_onnxruntime)
 - PaddleInference demo [Python](../../deploy/python) & [C++](../../deploy/cpp)
 
 
@@ -272,7 +280,7 @@ python tools/train.py -c configs/picodet/picodet_s_416_coco_lcnet.yml \
 <details open>
 <summary>教程:</summary>
 
-训练及部署细节请参考[非结构化剪枝文档](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.4/configs/picodet/pruner/README.md)。
+训练及部署细节请参考[非结构化剪枝文档](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.4/configs/picodet/legacy_model/pruner/README.md)。
 
 </details>
 

configs/picodet/README_en.md

@@ -31,7 +31,7 @@ We release/2.4ed a series of lightweight models, named `PP-PicoDet`. Because of
 
 ## Benchmark
 
-| Model     | Input size | mAP<sup>val<br>0.5:0.95 | mAP<sup>val<br>0.5 | Params<br><sup>(M) | FLOPS<br><sup>(G) | Latency<sup><small>[CPU](#latency)</small><sup><br><sup>(ms) | Latency<sup><small>[Lite](#latency)</small><sup><br><sup>(ms) |  Download  | Config | Inference Model |
+| Model     | Input size | mAP<sup>val<br>0.5:0.95 | mAP<sup>val<br>0.5 | Params<br><sup>(M) | FLOPS<br><sup>(G) | Latency<sup><small>[CPU](#latency)</small><sup><br><sup>(ms) | Latency<sup><small>[Lite](#latency)</small><sup><br><sup>(ms) |  Weight  | Config | Inference Model |
 | :-------- | :--------: | :---------------------: | :----------------: | :----------------: | :---------------: | :-----------------------------: | :-----------------------------: | :----------------------------------------: | :--------------------------------------- | :--------------------------------------- |
 | PicoDet-XS |  320*320   |          23.5           |        36.1       |        0.70        |       0.67        |              3.9ms              |            7.81ms             | [model](https://paddledet.bj.bcebos.com/models/picodet_xs_320_coco_lcnet.pdparams) &#124; [log](https://paddledet.bj.bcebos.com/logs/train_picodet_xs_320_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.4/configs/picodet/picodet_xs_320_coco_lcnet.yml) | [w/ postprocess](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_xs_320_coco_lcnet.tar) &#124; [w/o postprocess](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_xs_320_coco_lcnet_non_postprocess.tar) |
 | PicoDet-XS |  416*416   |          26.2           |        39.3        |        0.70        |       1.13        |              6.1ms             |            12.38ms             | [model](https://paddledet.bj.bcebos.com/models/picodet_xs_416_coco_lcnet.pdparams) &#124; [log](https://paddledet.bj.bcebos.com/logs/train_picodet_xs_416_coco_lcnet.log) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.4/configs/picodet/picodet_xs_416_coco_lcnet.yml) | [w/ postprocess](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_xs_416_coco_lcnet.tar) &#124; [w/o postprocess](https://paddledet.bj.bcebos.com/deploy/Inference/picodet_xs_416_coco_lcnet_non_postprocess.tar) |
@@ -131,8 +131,8 @@ Detail also can refer to [Quick start guide](https://github.com/PaddlePaddle/Pad
 
 ### Export and Convert Model
 
-<details>
-<summary>1. Export model (click to expand)</summary>
+<details open>
+<summary>1. Export model</summary>
 
 ```shell
 cd PaddleDetection
@@ -142,7 +142,7 @@ python tools/export_model.py -c configs/picodet/picodet_s_320_coco_lcnet.yml \
 ```
 
 - If no post processing is required, please specify: `-o export.benchmark=True` (if -o has already appeared, delete -o here) or manually modify corresponding fields in [runtime.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.4/configs/runtime.yml).
-- If no NMS is required, please specify: `-o export.nms=True` or manually modify corresponding fields in [runtime.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.4/configs/runtime.yml).
+- If no NMS is required, please specify: `-o export.nms=True` or manually modify corresponding fields in [runtime.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.4/configs/runtime.yml). Many scenes exported to ONNX only support single input and fixed shape output, so if exporting to ONNX, it is recommended not to export NMS.
 
 
 </details>
@@ -198,27 +198,33 @@ paddle2onnx --model_dir output_inference/picodet_s_320_coco_lcnet/ \
   python -m onnxsim picodet_s_320_coco.onnx picodet_s_processed.onnx
   ```
 
+  If the model includes postprocessing, specify `dynamic-input-shape` when simplifying the model:
+  ```shell
+  python -m onnxsim picodet_s_320_coco.onnx picodet_s_processed.onnx --dynamic-input-shape --input-shape image:1,3,320,320
+  ```
+
 </details>
 
 - Deploy models
 
 | Model     | Input size | ONNX(w/o postprocess)  | Paddle Lite(fp32) | Paddle Lite(fp16) |
 | :-------- | :--------: | :---------------------: | :----------------: | :----------------: |
-| PicoDet-XS |  320*320   | [( w/ postprocess)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_xs_320_lcnet_postprocessed.onnx) &#124; [( w/o postprocess)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_xs_320_coco_lcnet.onnx) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_xs_320.tar) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_xs_320_fp16.tar) |
-| PicoDet-XS |  416*416   | [( w/ postprocess)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_xs_416_lcnet_postprocessed.onnx) &#124; [( w/o postprocess)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_xs_416_coco_lcnet.onnx) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_xs_416.tar) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_xs_416_fp16.tar) |
-| PicoDet-S |  320*320   | [( w/ postprocess)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_s_320_lcnet_postprocessed.onnx) &#124; [( w/o postprocess)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_s_320_coco_lcnet.onnx) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_s_320.tar) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_s_320_fp16.tar) |
-| PicoDet-S |  416*416   |  [( w/ postprocess)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_s_416_lcnet_postprocessed.onnx) &#124; [( w/o postprocess)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_s_416_coco_lcnet.onnx) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_s_416.tar) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_s_416_fp16.tar) |
-| PicoDet-M |  320*320   | [( w/ postprocess)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_m_320_lcnet_postprocessed.onnx) &#124; [( w/o postprocess)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_m_320_coco_lcnet.onnx) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_m_320.tar) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_m_320_fp16.tar) |
-| PicoDet-M |  416*416   | [( w/ postprocess)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_m_416_lcnet_postprocessed.onnx) &#124; [( w/o postprocess)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_m_416_coco_lcnet.onnx) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_m_416.tar) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_m_416_fp16.tar) |
-| PicoDet-L |  320*320   | [( w/ postprocess)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_l_320_lcnet_postprocessed.onnx) &#124; [( w/o postprocess)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_l_320_coco_lcnet.onnx) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_l_320.tar) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_l_320_fp16.tar) |
-| PicoDet-L |  416*416   | [( w/ postprocess)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_l_416_lcnet_postprocessed.onnx) &#124; [( w/o postprocess)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_l_416_coco_lcnet.onnx) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_l_416.tar) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_l_416_fp16.tar) |
-| PicoDet-L |  640*640   | [( w/ postprocess)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_l_640_lcnet_postprocessed.onnx) &#124; [( w/o postprocess)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_l_640_coco_lcnet.onnx) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_l_640.tar) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_l_640_fp16.tar) |
+| PicoDet-XS |  320*320   | [( w/ postprocess)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_xs_320_lcnet_postprocessed.onnx) &#124; [( w/o postprocess)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_xs_320_coco_lcnet.onnx) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_xs_320_coco_lcnet.tar) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_xs_320_coco_lcnet_fp16.tar) |
+| PicoDet-XS |  416*416   | [( w/ postprocess)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_xs_416_lcnet_postprocessed.onnx) &#124; [( w/o postprocess)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_xs_416_coco_lcnet.onnx) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_xs_416_coco_lcnet.tar) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_xs_416_coco_lcnet_fp16.tar) |
+| PicoDet-S |  320*320   | [( w/ postprocess)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_s_320_lcnet_postprocessed.onnx) &#124; [( w/o postprocess)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_s_320_coco_lcnet.onnx) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_s_320_coco_lcnet.tar) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_s_320_coco_lcnet_fp16.tar) |
+| PicoDet-S |  416*416   |  [( w/ postprocess)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_s_416_lcnet_postprocessed.onnx) &#124; [( w/o postprocess)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_s_416_coco_lcnet.onnx) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_s_416_coco_lcnet.tar) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_s_416_coco_lcnet_fp16.tar) |
+| PicoDet-M |  320*320   | [( w/ postprocess)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_m_320_lcnet_postprocessed.onnx) &#124; [( w/o postprocess)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_m_320_coco_lcnet.onnx) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_m_320_coco_lcnet.tar) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_m_320_coco_lcnet_fp16.tar) |
+| PicoDet-M |  416*416   | [( w/ postprocess)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_m_416_lcnet_postprocessed.onnx) &#124; [( w/o postprocess)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_m_416_coco_lcnet.onnx) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_m_416_coco_lcnet.tar) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_m_416_coco_lcnet_fp16.tar) |
+| PicoDet-L |  320*320   | [( w/ postprocess)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_l_320_lcnet_postprocessed.onnx) &#124; [( w/o postprocess)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_l_320_coco_lcnet.onnx) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_l_320_coco_lcnet.tar) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_l_320_coco_lcnet_fp16.tar) |
+| PicoDet-L |  416*416   | [( w/ postprocess)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_l_416_lcnet_postprocessed.onnx) &#124; [( w/o postprocess)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_l_416_coco_lcnet.onnx) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_l_416_coco_lcnet.tar) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_l_416_coco_lcnet_fp16.tar) |
+| PicoDet-L |  640*640   | [( w/ postprocess)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_l_640_lcnet_postprocessed.onnx) &#124; [( w/o postprocess)](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_l_640_coco_lcnet.onnx)  [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_l_640_coco_lcnet.tar) | [model](https://paddledet.bj.bcebos.com/deploy/paddlelite/picodet_l_640_coco_lcnet_fp16.tar) |
 
 ### Deploy
 
-- OpenVINO demo [Python](../../deploy/third_engine/demo/openvino/python)
+- OpenVINO demo [Python](../../deploy/third_engine/demo_openvino/python)
 - [PaddleLite C++ demo](../../deploy/lite)
 - [Android demo(Paddle Lite)](https://github.com/PaddlePaddle/Paddle-Lite-Demo/tree/develop/object_detection/android/app/cxx/picodet_detection_demo)
+- ONNXRuntime demo [Python](../../deploy/third_engine/demo_onnxruntime)
 - PaddleInference demo [Python](../../deploy/python) & [C++](../../deploy/cpp)
 
 
@@ -269,7 +275,8 @@ python tools/train.py -c configs/picodet/picodet_s_416_coco_lcnet.yml \
 <details open>
 <summary>Toturial:</summary>
 
-Please refer this [documentation](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.4/configs/picodet/pruner/README.md) for details such as requirements, training and deployment.
+Please refer this [documentation](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.4/configs/picodet/legacy_model/pruner/README.md) for details such as requirements, training and deployment.
+
 
 </details>
 

deploy/third_engine/demo_openvino/python/README.md

@@ -19,7 +19,6 @@ pip install openvino==2022.1.0
 
 - 准备测试所用图片：本demo默认利用PaddleDetection/demo/[000000014439.jpg](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.4/demo/000000014439.jpg)
 
-### Benchmark
 - 在本目录下直接运行：
 
 ```shell
@@ -30,16 +29,7 @@ python openvino_benchmark.py --img_path ..\..\..\..\demo\000000014439.jpg --onnx
 ```
 - 注意：```--in_shape```为对应模型输入size，默认为320
 
-### Inference images(w/o 后处理)
-
-```shell
-# Linux
-python openvino_benchmark.py --benchmark 0 --img_path ../../../../demo/000000014439.jpg --onnx_path out_onnxsim/picodet_s_320_coco_lcnet.onnx --in_shape 320
-# Windows
-python openvino_benchmark.py --benchmark 0 --img_path ..\..\..\..\demo\000000014439.jpg --onnx_path out_onnxsim\picodet_s_320_coco_lcnet.onnx --in_shape 320
-```
-
-## Inference images(w/ 后处理, w/o NMS)
+## 真实图片测试(网络包含后处理，但不包含NMS)
 
 - 准备测试模型：根据[PicoDet](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.4/configs/picodet)中【导出及转换模型】步骤，采用**包含后处理**但**不包含NMS**的方式导出模型（`-o export.benchmark=False export.nms=False` ），并生成待测试模型简化后的onnx模型（可在下文链接中直接下载）。同时在本目录下新建```out_onnxsim_infer```文件夹，将导出的onnx模型放在该目录下。
 
@@ -51,12 +41,22 @@ python openvino_infer.py --img_path ../../demo_onnxruntime/imgs/bus.jpg --onnx_p
 # Windows
 python openvino_infer.py --img_path ..\..\demo_onnxruntime\imgs\bus.jpg --onnx_path out_onnxsim_infer\picodet_s_320_postproccesed_woNMS.onnx --in_shape 320
 ```
+
+### 真实图片测试(网络不包含后处理)
+
+```shell
+# Linux
+python openvino_benchmark.py --benchmark 0 --img_path ../../../../demo/000000014439.jpg --onnx_path out_onnxsim/picodet_s_320_coco_lcnet.onnx --in_shape 320
+# Windows
+python openvino_benchmark.py --benchmark 0 --img_path ..\..\..\..\demo\000000014439.jpg --onnx_path out_onnxsim\picodet_s_320_coco_lcnet.onnx --in_shape 320
+```
+
 - 结果：
     <div align="center">
       <img src="../../../../docs/images/res.jpg" height="500px" >
     </div>
 
-## 结果
+## Benchmark结果
 
 - 测速结果如下：