From fd85f9dbdd2f4198272827cd301c9d427c101e0f Mon Sep 17 00:00:00 2001 From: Guanghua Yu <742925032@qq.com> Date: Thu, 18 Aug 2022 11:54:35 +0800 Subject: [PATCH] fix YOLO series act demo some bug (#1359) --- .../detection/configs/ppyoloe_l_qat_dis.yaml | 1 + .../detection/configs/ppyoloe_s_qat_dis.yaml | 1 + .../pytorch_yolo_series/README.md | 50 +++++++------------ .../configs/yolov5s_qat_dis.yaml | 1 - .../pytorch_yolo_series/eval.py | 5 +- .../pytorch_yolo_series/post_process.py | 4 +- .../configs/yolov5s_ptq.yaml | 2 +- .../pytorch_yolo_series/eval.py | 10 ++-- .../pytorch_yolo_series/post_process.py | 8 +-- 9 files changed, 37 insertions(+), 45 deletions(-) diff --git a/example/auto_compression/detection/configs/ppyoloe_l_qat_dis.yaml b/example/auto_compression/detection/configs/ppyoloe_l_qat_dis.yaml index cd39981c1eb44..f230ee578bf14 100644 --- a/example/auto_compression/detection/configs/ppyoloe_l_qat_dis.yaml +++ b/example/auto_compression/detection/configs/ppyoloe_l_qat_dis.yaml @@ -13,6 +13,7 @@ Distillation: loss: soft_label Quantization: + onnx_format: true use_pact: true activation_quantize_type: 'moving_average_abs_max' quantize_op_types: diff --git a/example/auto_compression/detection/configs/ppyoloe_s_qat_dis.yaml b/example/auto_compression/detection/configs/ppyoloe_s_qat_dis.yaml index 1efd1175eea17..466c9c2b53c12 100644 --- a/example/auto_compression/detection/configs/ppyoloe_s_qat_dis.yaml +++ b/example/auto_compression/detection/configs/ppyoloe_s_qat_dis.yaml @@ -13,6 +13,7 @@ Distillation: loss: soft_label Quantization: + onnx_format: true use_pact: true activation_quantize_type: 'moving_average_abs_max' quantize_op_types: diff --git a/example/auto_compression/pytorch_yolo_series/README.md b/example/auto_compression/pytorch_yolo_series/README.md index ededb9cbc0092..3f80ad6f17df4 100644 --- a/example/auto_compression/pytorch_yolo_series/README.md +++ b/example/auto_compression/pytorch_yolo_series/README.md @@ -33,7 +33,7 @@ | YOLOv7 | ACT量化训练 | 640*640 | **50.9** | 36MB | - | - | **4.55ms** | [config](./configs/yolov7_qat_dis.yaml) | [Infer Model](https://bj.bcebos.com/v1/paddle-slim-models/act/yolov7_quant.tar) | [ONNX Model](https://bj.bcebos.com/v1/paddle-slim-models/act/yolov7_quant.onnx) | | | | | | | | | | | | YOLOv7-Tiny | Base模型 | 640*640 | 37.3 | 24MB | 5.06ms | 2.32ms | - | - | [Model](https://paddle-slim-models.bj.bcebos.com/act/yolov7-tiny.onnx) | -| YOLOv7-Tiny | 离线量化 | 640*640 | - | 6.1MB | - | - | 1.68ms | - | - | +| YOLOv7-Tiny | 离线量化 | 640*640 | 35.8 | 6.1MB | - | - | 1.68ms | - | - | | YOLOv7-Tiny | ACT量化训练 | 640*640 | **37.0** | 6.1MB | - | - | **1.68ms** | [config](./configs/yolov7_tiny_qat_dis.yaml) | [Infer Model](https://bj.bcebos.com/v1/paddle-slim-models/act/yolov7_tiny_quant.tar) | [ONNX Model](https://bj.bcebos.com/v1/paddle-slim-models/act/yolov7_tiny_quant.onnx) | 说明： @@ -43,15 +43,15 @@ ## 3. 自动压缩流程 #### 3.1 准备环境 -- PaddlePaddle develop每日版本 （可从[Paddle官网](https://www.paddlepaddle.org.cn/install/quick?docurl=/documentation/docs/zh/develop/install/pip/linux-pip.html)下载安装） +- PaddlePaddle >= 2.3.2版本 （可从[Paddle官网](https://www.paddlepaddle.org.cn/install/quick?docurl=/documentation/docs/zh/install/pip/linux-pip.html)根据相应环境的安装指令进行安装） - PaddleSlim develop 版本 -（1）安装paddlepaddle： -```shell +（1）安装paddlepaddle +``` # CPU -pip install paddlepaddle +pip install paddlepaddle==2.3.2 # GPU -pip install paddlepaddle-gpu +pip install paddlepaddle-gpu==2.3.2 ``` （2）安装paddleslim： @@ -90,22 +90,22 @@ dataset/coco/ - YOLOv5: -可通过[ultralytics/yolov5](https://github.com/ultralytics/yolov5) 官方的[导出教程](https://github.com/ultralytics/yolov5/issues/251)来准备ONNX模型。也可以下载准备好的[yolov5s.onnx](https://paddle-slim-models.bj.bcebos.com/act/yolov5s.onnx)。 -```shell -python export.py --weights yolov5s.pt --include onnx -``` + 本示例模型使用[ultralytics/yolov5](https://github.com/ultralytics/yolov5)的master分支导出，要求v6.1之后的ONNX模型，可以根据官方的[导出教程](https://github.com/ultralytics/yolov5/issues/251)来准备ONNX模型。也可以下载准备好的[yolov5s.onnx](https://paddle-slim-models.bj.bcebos.com/act/yolov5s.onnx)。 + ```shell + python export.py --weights yolov5s.pt --include onnx + ``` - YOLOv6: -可通过[meituan/YOLOv6](https://github.com/meituan/YOLOv6)官方的[导出教程](https://github.com/meituan/YOLOv6/blob/main/deploy/ONNX/README.md)来准备ONNX模型。也可以下载已经准备好的[yolov6s.onnx](https://paddle-slim-models.bj.bcebos.com/act/yolov6s.onnx)。 + 可通过[meituan/YOLOv6](https://github.com/meituan/YOLOv6)官方的[导出教程](https://github.com/meituan/YOLOv6/blob/main/deploy/ONNX/README.md)来准备ONNX模型。也可以下载已经准备好的[yolov6s.onnx](https://paddle-slim-models.bj.bcebos.com/act/yolov6s.onnx)。 - YOLOv7: 可通过[WongKinYiu/yolov7](https://github.com/WongKinYiu/yolov7)的导出脚本来准备ONNX模型，具体步骤如下： -```shell -git clone https://github.com/WongKinYiu/yolov7.git -python export.py --weights yolov7-tiny.pt --grid -``` + ```shell + git clone https://github.com/WongKinYiu/yolov7.git + python export.py --weights yolov7-tiny.pt --grid + ``` -**注意**：目前ACT支持不带NMS模型，使用如上命令导出即可。也可以直接下载我们已经准备好的[yolov7.onnx](https://paddle-slim-models.bj.bcebos.com/act/yolov7-tiny.onnx)。 + **注意**：目前ACT支持**不带NMS**模型，使用如上命令导出即可。也可以直接下载我们已经准备好的[yolov7.onnx](https://paddle-slim-models.bj.bcebos.com/act/yolov7-tiny.onnx)。 #### 3.4 自动压缩并产出模型 @@ -138,25 +138,11 @@ python eval.py --config_path=./configs/yolov7_tiny_qat_dis.yaml #### 导出至ONNX使用TensorRT部署 -- 首先安装Paddle2onnx： -```shell -pip install paddle2onnx==1.0.0rc3 -``` - -- 然后将量化模型导出至ONNX： -```shell -paddle2onnx --model_dir output/ \ - --model_filename model.pdmodel \ - --params_filename model.pdiparams \ - --opset_version 13 \ - --enable_onnx_checker True \ - --save_file yolov7_quant.onnx \ - --deploy_backend tensorrt -``` +执行完自动压缩后会默认在`save_dir`中生成`quant_model.onnx`的ONNX模型文件，可以直接使用TensorRT测试脚本进行验证。 - 进行测试： ```shell -python yolov7_onnx_trt.py --model_path=yolov7_quant.onnx --image_file=images/000000570688.jpg --precision=int8 +python yolov7_onnx_trt.py --model_path=output/quant_model.onnx --image_file=images/000000570688.jpg --precision=int8 ``` #### Paddle-TensorRT部署 diff --git a/example/auto_compression/pytorch_yolo_series/configs/yolov5s_qat_dis.yaml b/example/auto_compression/pytorch_yolo_series/configs/yolov5s_qat_dis.yaml index 3cb4fb47fd926..d5c853bedeffa 100644 --- a/example/auto_compression/pytorch_yolo_series/configs/yolov5s_qat_dis.yaml +++ b/example/auto_compression/pytorch_yolo_series/configs/yolov5s_qat_dis.yaml @@ -15,7 +15,6 @@ Distillation: Quantization: onnx_format: true use_pact: true - onnx_format: False activation_quantize_type: 'moving_average_abs_max' quantize_op_types: - conv2d diff --git a/example/auto_compression/pytorch_yolo_series/eval.py b/example/auto_compression/pytorch_yolo_series/eval.py index b9a83845fb026..de11989e4da74 100644 --- a/example/auto_compression/pytorch_yolo_series/eval.py +++ b/example/auto_compression/pytorch_yolo_series/eval.py @@ -32,6 +32,8 @@ def argsparser(): default=None, help="path of compression strategy config.", required=True) + parser.add_argument( + '--batch_size', type=int, default=1, help="Batch size of model input.") parser.add_argument( '--devices', type=str, @@ -83,7 +85,8 @@ def main(): anno_path=global_config['val_anno_path']) global anno_file anno_file = dataset.ann_file - val_loader = paddle.io.DataLoader(dataset, batch_size=1) + val_loader = paddle.io.DataLoader( + dataset, batch_size=FLAGS.batch_size, drop_last=True) eval() diff --git a/example/auto_compression/pytorch_yolo_series/post_process.py b/example/auto_compression/pytorch_yolo_series/post_process.py index c4a845af03946..644c24b8157f7 100644 --- a/example/auto_compression/pytorch_yolo_series/post_process.py +++ b/example/auto_compression/pytorch_yolo_series/post_process.py @@ -159,8 +159,8 @@ def __call__(self, outs, scale_factor): if len(pred.shape) == 1: pred = pred[np.newaxis, :] pred_bboxes = pred[:, :4] - scale_factor = np.tile(scale_factor[i][::-1], (1, 2)) - pred_bboxes /= scale_factor + scale = np.tile(scale_factor[i][::-1], (2)) + pred_bboxes /= scale bbox = np.concatenate( [ pred[:, -1][:, np.newaxis], pred[:, -2][:, np.newaxis], diff --git a/example/post_training_quantization/pytorch_yolo_series/configs/yolov5s_ptq.yaml b/example/post_training_quantization/pytorch_yolo_series/configs/yolov5s_ptq.yaml index f99bb74f11193..eb9f792b10a4f 100644 --- a/example/post_training_quantization/pytorch_yolo_series/configs/yolov5s_ptq.yaml +++ b/example/post_training_quantization/pytorch_yolo_series/configs/yolov5s_ptq.yaml @@ -1,6 +1,6 @@ arch: YOLOv5 model_dir: ./yolov5s.onnx -dataset_dir: /dataset/coco/ +dataset_dir: dataset/coco/ train_image_dir: train2017 val_image_dir: val2017 train_anno_path: annotations/instances_train2017.json diff --git a/example/post_training_quantization/pytorch_yolo_series/eval.py b/example/post_training_quantization/pytorch_yolo_series/eval.py index 6705104b69ac3..e105bb788b148 100644 --- a/example/post_training_quantization/pytorch_yolo_series/eval.py +++ b/example/post_training_quantization/pytorch_yolo_series/eval.py @@ -20,7 +20,7 @@ import paddle from paddleslim.common import load_config as load_slim_config from paddleslim.common import load_inference_model -from post_process import YOLOv6PostProcess, coco_metric +from post_process import YOLOPostProcess, coco_metric from dataset import COCOValDataset @@ -32,6 +32,8 @@ def argsparser(): default=None, help="path of compression strategy config.", required=True) + parser.add_argument( + '--batch_size', type=int, default=1, help="Batch size of model input.") parser.add_argument( '--devices', type=str, @@ -60,8 +62,7 @@ def eval(): feed={feed_target_names[0]: data_all['image']}, fetch_list=fetch_targets, return_numpy=False) - res = {} - postprocess = YOLOv6PostProcess( + postprocess = YOLOPostProcess( score_threshold=0.001, nms_threshold=0.65, multi_label=True) res = postprocess(np.array(outs[0]), data_all['scale_factor']) bboxes_list.append(res['bbox']) @@ -83,7 +84,8 @@ def main(): anno_path=config['val_anno_path']) global anno_file anno_file = dataset.ann_file - val_loader = paddle.io.DataLoader(dataset, batch_size=1) + val_loader = paddle.io.DataLoader( + dataset, batch_size=FLAGS.batch_size, drop_last=True) eval() diff --git a/example/post_training_quantization/pytorch_yolo_series/post_process.py b/example/post_training_quantization/pytorch_yolo_series/post_process.py index 3232fe3f56ede..5988258b8766c 100644 --- a/example/post_training_quantization/pytorch_yolo_series/post_process.py +++ b/example/post_training_quantization/pytorch_yolo_series/post_process.py @@ -70,9 +70,9 @@ def nms(boxes, scores, iou_threshold): return keep -class YOLOv6PostProcess(object): +class YOLOPostProcess(object): """ - Post process of YOLOv6 network. + Post process of YOLO serise network. args: score_threshold(float): Threshold to filter out bounding boxes with low confidence score. If not provided, consider all boxes. @@ -159,8 +159,8 @@ def __call__(self, outs, scale_factor): if len(pred.shape) == 1: pred = pred[np.newaxis, :] pred_bboxes = pred[:, :4] - scale_factor = np.tile(scale_factor[i][::-1], (1, 2)) - pred_bboxes /= scale_factor + scale = np.tile(scale_factor[i][::-1], (2)) + pred_bboxes /= scale bbox = np.concatenate( [ pred[:, -1][:, np.newaxis], pred[:, -2][:, np.newaxis],