diff --git a/configs/slim/README.md b/configs/slim/README.md index a695f9bb7fa2d7d204e9b901cf3b4abe533e933d..b3b0981533fa06d86ebf20e2b62babc5031470dd 100755 --- a/configs/slim/README.md +++ b/configs/slim/README.md @@ -13,7 +13,7 @@ - Python 3.7+ - PaddlePaddle >= 2.1.0 -- PaddleSlim >= 2.0.0 +- PaddleSlim >= 2.1.0 - CUDA 10.1+ - cuDNN >=7.6.5 @@ -72,6 +72,8 @@ python tools/infer.py -c configs/{MODEL.yml} --slim_config configs/slim/{SLIM_CO - `--infer_img`: 指定测试图像路径。 +## 全链条部署 + ### 动转静导出模型 ```shell @@ -82,6 +84,14 @@ python tools/export_model.py -c configs/{MODEL.yml} --slim_config configs/slim/{ - `--slim_config`: 指定压缩策略配置文件。 - `-o weights`: 指定压缩算法训好的模型路径。 +### 部署预测 + +- Paddle-Inference预测： + - [Python部署](../../deploy/python/README.md) + - [C++部署](../../deploy/cpp/README.md) + - [TensorRT预测部署教程](../../deploy/TENSOR_RT.md) +- 服务器端部署：使用[PaddleServing](../../deploy/serving/README.md)部署。 +- 手机移动端部署：使用[Paddle-Lite](../../deploy/lite/README.md) 在手机移动端部署。 ## Benchmark @@ -89,31 +99,51 @@ python tools/export_model.py -c configs/{MODEL.yml} --slim_config configs/slim/{ #### Pascal VOC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 | -| :----------------| :-------: | :------------: | :-------------: | :------: | :--------: | :------: | :-----------------------------------------------------: |:-------------: | :------: | -| YOLOv3-MobileNetV1 | baseline | 24.13 | 93 | 608 | 289.9ms | 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) | - | +| 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) | -- 目前剪裁支持YOLO系列、SSD、TTFNet、BlazeFace，其余模型正在开发支持中。 +#### 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 | 24.3 | [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) | + +说明： +- 目前剪裁除RCNN系列模型外，其余模型均已支持。 - SD855预测时延为使用PaddleLite部署，使用arm8架构并使用4线程(4 Threads)推理时延。 ### 量化 #### COCO上benchmark -| 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 | 28.8 | [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 | 普通在线量化 | 608 | 30.5 (+1.7) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v1_coco_qat.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/quant/yolov3_mobilenet_v1_qat.yml) | -| YOLOv3-MobileNetV3 | baseline | 608 | 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) | - | -| YOLOv3-MobileNetV3 | PACT在线量化 | 608 | 29.1 (-2.3) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_mobilenet_v3_coco_qat.pdparams) | [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 | 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) | - | -| YOLOv3-DarkNet53 | 普通在线量化 | 608 | 38.8 (-0.2) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/yolov3_darknet_coco_qat.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/quant/yolov3_darknet_qat.yml) | -| SSD-MobileNet_v1 | baseline | 300 | 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) | - | -| SSD-MobileNet_v1 | 普通在线量化 | 300 | 72.9(-0.9) | [下载链接](https://paddledet.bj.bcebos.com/models/slim/ssd_mobilenet_v1_300_voc_qat.pdparams) | [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) | 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) | - | -| 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) | [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) | - +| 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) | + +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。 +- SD855预测时延为使用PaddleLite部署，使用arm8架构并使用4线程(4 Threads)推理时延。 ### 蒸馏 @@ -130,7 +160,7 @@ python tools/export_model.py -c configs/{MODEL.yml} --slim_config configs/slim/{ #### COCO上benchmark -| 模型 | 压缩策略 | 输入尺寸 | GFLOPs | 模型体积(MB) | Box AP | 下载 | 模型配置文件 | 压缩算法配置文件 | -| ------------------ | ------------ | -------- | :---------: |:---------: | :---------: |:----------------------------------------------------------: | :----------------------------------------------------------: | :----------------------------------------------------------: | -| YOLOv3-MobileNetV1 | baseline | 608 | 24.65 | 94.6 | 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%) | 32.0(-66.0%) | 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) | +| 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) | diff --git a/configs/slim/prune/ppyolo_mbv3_large_prune_fpgm.yml b/configs/slim/prune/ppyolo_mbv3_large_prune_fpgm.yml new file mode 100644 index 0000000000000000000000000000000000000000..b9cecb3163f978b33123499f241ceb88fd05a688 --- /dev/null +++ b/configs/slim/prune/ppyolo_mbv3_large_prune_fpgm.yml @@ -0,0 +1,9 @@ +pretrain_weights: https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_large_coco.pdparams +slim: Pruner + +Pruner: + criterion: fpgm + pruned_params: ['conv2d_62.w_0', 'conv2d_63.w_0', 'conv2d_64.w_0', + 'conv2d_65.w_0', 'conv2d_66.w_0', 'conv2d_67.w_0'] + pruned_ratios: [0.75, 0.75, 0.75, 0.75, 0.75, 0.75] + print_params: True diff --git a/configs/slim/prune/ppyolo_r50vd_prune_fpgm.yml b/configs/slim/prune/ppyolo_r50vd_prune_fpgm.yml new file mode 100644 index 0000000000000000000000000000000000000000..00dc57ae9759bb32f774a1852b629cdcac2c1b4a --- /dev/null +++ b/configs/slim/prune/ppyolo_r50vd_prune_fpgm.yml @@ -0,0 +1,13 @@ +pretrain_weights: https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams +slim: Pruner + +Pruner: + criterion: fpgm + pruned_params: ['conv2d_56.w_0', 'conv2d_57.w_0', 'conv2d_58.w_0', + 'conv2d_59.w_0', 'conv2d_60.w_0', 'conv2d_61.w_0', + 'conv2d_63.w_0', 'conv2d_64.w_0', 'conv2d_65.w_0', + 'conv2d_66.w_0', 'conv2d_67.w_0', 'conv2d_68.w_0', + 'conv2d_70.w_0', 'conv2d_71.w_0', 'conv2d_72.w_0', + 'conv2d_73.w_0', 'conv2d_74.w_0', 'conv2d_75.w_0'] + pruned_ratios: [0.75,0.75,0.75,0.75,0.75,0.75,0.75,0.75,0.75,0.75,0.75,0.75,0.875,0.875,0.875,0.875,0.875,0.875] + print_params: False diff --git a/configs/slim/prune/yolov3_darknet_prune_fpgm.yml b/configs/slim/prune/yolov3_darknet_prune_fpgm.yml new file mode 100644 index 0000000000000000000000000000000000000000..850fefb956431cbb15fc20f58fd868171722ff3c --- /dev/null +++ b/configs/slim/prune/yolov3_darknet_prune_fpgm.yml @@ -0,0 +1,13 @@ +pretrain_weights: https://paddledet.bj.bcebos.com/models/yolov3_darknet53_270e_coco.pdparams +slim: Pruner + +Pruner: + criterion: fpgm + pruned_params: ['conv2d_52.w_0', 'conv2d_53.w_0', 'conv2d_54.w_0', + 'conv2d_55.w_0', 'conv2d_56.w_0', 'conv2d_57.w_0', + 'conv2d_59.w_0', 'conv2d_60.w_0', 'conv2d_61.w_0', + 'conv2d_62.w_0', 'conv2d_63.w_0', 'conv2d_64.w_0', + 'conv2d_66.w_0', 'conv2d_67.w_0', 'conv2d_68.w_0', + 'conv2d_69.w_0', 'conv2d_70.w_0', 'conv2d_71.w_0'] + pruned_ratios: [0.75,0.75,0.75,0.75,0.75,0.75,0.75,0.75,0.75,0.75,0.75,0.75,0.875,0.875,0.875,0.875,0.875,0.875] + print_params: True diff --git a/configs/slim/quant/ppyolo_mbv3_large_qat.yml b/configs/slim/quant/ppyolo_mbv3_large_qat.yml new file mode 100644 index 0000000000000000000000000000000000000000..2b2ddf90e7b36d60fbbd75f1b7beb6e7ffac9685 --- /dev/null +++ b/configs/slim/quant/ppyolo_mbv3_large_qat.yml @@ -0,0 +1,16 @@ +pretrain_weights: https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_large_coco.pdparams +slim: QAT + +QAT: + quant_config: { + 'weight_quantize_type': 'channel_wise_abs_max', 'activation_quantize_type': 'moving_average_abs_max', + 'weight_bits': 8, 'activation_bits': 8, 'dtype': 'int8', 'window_size': 10000, 'moving_rate': 0.99, + 'quantizable_layer_type': ['Conv2D', 'Linear']} + print_model: True + +PPYOLOFPN: + in_channels: [160, 368] + coord_conv: true + conv_block_num: 0 + spp: true + drop_block: false diff --git a/configs/slim/quant/ppyolo_r50vd_qat_pact.yml b/configs/slim/quant/ppyolo_r50vd_qat_pact.yml new file mode 100644 index 0000000000000000000000000000000000000000..fb6d98841040a13221ac8cba3acecc6236a6cb03 --- /dev/null +++ b/configs/slim/quant/ppyolo_r50vd_qat_pact.yml @@ -0,0 +1,39 @@ +pretrain_weights: https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams +slim: QAT + +QAT: + quant_config: { + 'activation_preprocess_type': 'PACT', + 'weight_quantize_type': 'channel_wise_abs_max', 'activation_quantize_type': 'moving_average_abs_max', + 'weight_bits': 8, 'activation_bits': 8, 'dtype': 'int8', 'window_size': 10000, 'moving_rate': 0.9, + 'quantizable_layer_type': ['Conv2D', 'Linear']} + print_model: True + +epoch: 50 + +LearningRate: + base_lr: 0.0005 + schedulers: + - !PiecewiseDecay + gamma: 0.1 + milestones: + - 30 + - 45 + - !LinearWarmup + start_factor: 0. + steps: 1000 + +OptimizerBuilder: + optimizer: + momentum: 0.9 + type: Momentum + regularizer: + factor: 0.0005 + type: L2 + +PPYOLOFPN: + coord_conv: true + block_size: 3 + keep_prob: 0.9 + spp: true + drop_block: false diff --git a/configs/slim/quant/ppyolov2_r50vd_dcn_qat.yml b/configs/slim/quant/ppyolov2_r50vd_dcn_qat.yml new file mode 100644 index 0000000000000000000000000000000000000000..d218e1edcbdb3597f43650467b98839c7d5e28c2 --- /dev/null +++ b/configs/slim/quant/ppyolov2_r50vd_dcn_qat.yml @@ -0,0 +1,33 @@ +pretrain_weights: https://paddledet.bj.bcebos.com/models/ppyolov2_r50vd_dcn_365e_coco.pdparams +slim: QAT + +QAT: + quant_config: { + 'activation_preprocess_type': 'PACT', + 'weight_quantize_type': 'channel_wise_abs_max', 'activation_quantize_type': 'moving_average_abs_max', + 'weight_bits': 8, 'activation_bits': 8, 'dtype': 'int8', 'window_size': 10000, 'moving_rate': 0.9, + 'quantizable_layer_type': ['Conv2D', 'Linear']} + print_model: True + +epoch: 50 +snapshot_epoch: 8 +LearningRate: + base_lr: 0.0005 + schedulers: + - !PiecewiseDecay + gamma: 0.1 + milestones: + - 30 + - 45 + - !LinearWarmup + start_factor: 0. + steps: 2000 + +TrainReader: + batch_size: 8 + +PPYOLOPAN: + drop_block: false + block_size: 3 + keep_prob: 0.9 + spp: true diff --git a/configs/slim/quant/yolov3_mobilenet_v3_qat.yml b/configs/slim/quant/yolov3_mobilenet_v3_qat.yml index 81269090865a8cac0e98af8c55b723eaf84fbf94..8e83f27aa92788a5a1ef1e0caa17ee9cc143bd4c 100644 --- a/configs/slim/quant/yolov3_mobilenet_v3_qat.yml +++ b/configs/slim/quant/yolov3_mobilenet_v3_qat.yml @@ -4,21 +4,21 @@ slim: QAT QAT: quant_config: { - 'weight_preprocess_type': 'PACT', + 'activation_preprocess_type': 'PACT', 'weight_quantize_type': 'channel_wise_abs_max', 'activation_quantize_type': 'moving_average_abs_max', 'weight_bits': 8, 'activation_bits': 8, 'dtype': 'int8', 'window_size': 10000, 'moving_rate': 0.9, 'quantizable_layer_type': ['Conv2D', 'Linear']} print_model: True -epoch: 30 +epoch: 50 LearningRate: base_lr: 0.0001 schedulers: - !PiecewiseDecay gamma: 0.1 milestones: - - 25 - - 28 + - 35 + - 45 - !LinearWarmup start_factor: 0. - steps: 2000 + steps: 1000 diff --git a/deploy/README.md b/deploy/README.md index b9f5a59ca70acc9122faab4245716391bb915172..3987ace763260471922684d31b3c5588c2512f26 100644 --- a/deploy/README.md +++ b/deploy/README.md @@ -6,7 +6,7 @@ - `C++`语言部署 ，支持`CPU`、`GPU`和`XPU`环境，支持在`Linux`、`Windows`系统下部署，支持`NV Jetson`嵌入式设备上部署。请参考文档[C++部署](cpp/README.md)。 - `TensorRT`加速：请参考文档[TensorRT预测部署教程](TENSOR_RT.md) - 服务器端部署：使用[PaddleServing](./serving/README.md)部署。 -- 手机移动端部署：使用[Paddle-Lite](https://github.com/PaddlePaddle/Paddle-Lite) 在手机移动端部署。 +- 手机移动端部署：使用[Paddle-Lite](./lite/README.md) 在手机移动端部署。 ## 1.模型导出 diff --git a/ppdet/engine/trainer.py b/ppdet/engine/trainer.py index 0c7a5d881dfb8685d187ae70214c08118f489e14..8a422c35921d1f88b7aa0f0d496983f86a9f22db 100644 --- a/ppdet/engine/trainer.py +++ b/ppdet/engine/trainer.py @@ -498,7 +498,7 @@ class Trainer(object): }] # dy2st and save model - if 'slim' not in self.cfg or self.cfg['slim'] != 'QAT': + if 'slim' not in self.cfg or self.cfg['slim_type'] != 'QAT': static_model = paddle.jit.to_static( self.model, input_spec=input_spec) # NOTE: dy2st do not pruned program, but jit.save will prune program diff --git a/ppdet/slim/__init__.py b/ppdet/slim/__init__.py index ab286647d89b70ea2aef01f831a5a3b2c68266fe..255a8859d043e10e5587ca5abb5dda97fc39ea07 100644 --- a/ppdet/slim/__init__.py +++ b/ppdet/slim/__init__.py @@ -53,6 +53,7 @@ def build_slim_model(cfg, slim_cfg, mode='train'): if mode == 'train': load_pretrain_weight(model, cfg.pretrain_weights) slim = create(cfg.slim) + cfg['slim_type'] = cfg.slim cfg['model'] = slim(model) cfg['slim'] = slim if mode != 'train':