[Model] add pptracking model (#357)

* add override mark * delete some * recovery * recovery * add tracking * add tracking py_bind and example * add pptracking * add pptracking * iomanip head file * add opencv_video lib * add python libs package Signed-off-by: ChaoII <849453582@qq.com> * complete comments Signed-off-by: ChaoII <849453582@qq.com> * add jdeTracker_ member variable Signed-off-by: ChaoII <849453582@qq.com> * add 'FASTDEPLOY_DECL' macro Signed-off-by: ChaoII <849453582@qq.com> * remove kwargs params Signed-off-by: ChaoII <849453582@qq.com> * [Doc]update pptracking docs * delete 'ENABLE_PADDLE_FRONTEND' switch * add pptracking unit test * update pptracking unit test Signed-off-by: ChaoII <849453582@qq.com> * modify test video file path and remove trt test * update unit test model url * remove 'FASTDEPLOY_DECL' macro Signed-off-by: ChaoII <849453582@qq.com> * fix build python packages about pptracking on win32 Signed-off-by: ChaoII <849453582@qq.com> Signed-off-by: ChaoII <849453582@qq.com> Co-authored-by: Jason <jiangjiajun@baidu.com>
2025-10-06 00:57:33 +08:00 · 2022-10-26 14:27:55 +08:00
parent da7247aa41
commit ba501fd963
38 changed files with 2959 additions and 16 deletions
--- a/examples/vision/tracking/pptracking/python/README.md
+++ b/examples/vision/tracking/pptracking/python/README.md
@@ -0,0 +1,70 @@
+# PP-Tracking Python部署示例
+
+在部署前，需确认以下两个步骤
+
+- 1. 软硬件环境满足要求，参考[FastDeploy环境要求](../../../../../docs/cn/build_and_install/download_prebuilt_libraries.md)  
+- 2. FastDeploy Python whl包安装，参考[FastDeploy Python安装](../../../../../docs/cn/build_and_install/download_prebuilt_libraries.md)
+
+本目录下提供`infer.py`快速完成PP-Tracking在CPU/GPU，以及GPU上通过TensorRT加速部署的示例。执行如下脚本即可完成
+
+```bash
+#下载部署示例代码
+git clone https://github.com/PaddlePaddle/FastDeploy.git
+cd FastDeploy/examples/vision/tracking/pptracking/python
+
+# 下载PP-Tracking模型文件和测试视频
+wget https://bj.bcebos.com/paddlehub/fastdeploy/fairmot_hrnetv2_w18_dlafpn_30e_576x320.tgz
+tar -xvf fairmot_hrnetv2_w18_dlafpn_30e_576x320.tgz
+wget https://bj.bcebos.com/paddlehub/fastdeploy/person.mp4
+# CPU推理
+python infer.py --model fairmot_hrnetv2_w18_dlafpn_30e_576x320 --video person.mp4 --device cpu
+# GPU推理
+python infer.py --model fairmot_hrnetv2_w18_dlafpn_30e_576x320 --video person.mp4  --device gpu
+# GPU上使用TensorRT推理 （注意：TensorRT推理第一次运行，有序列化模型的操作，有一定耗时，需要耐心等待）
+python infer.py --model fairmot_hrnetv2_w18_dlafpn_30e_576x320 --video person.mp4  --device gpu --use_trt True
+```
+
+## PP-Tracking Python接口
+
+```python
+fd.vision.tracking.PPTracking(model_file, params_file, config_file, runtime_option=None, model_format=ModelFormat.PADDLE)
+```
+
+PP-Tracking模型加载和初始化，其中model_file, params_file以及config_file为训练模型导出的Paddle inference文件，具体请参考其文档说明[模型导出](https://github.com/PaddlePaddle/PaddleSeg/tree/release/2.6/Matting)
+
+**参数**
+
+> * **model_file**(str): 模型文件路径
+> * **params_file**(str): 参数文件路径
+> * **config_file**(str): 推理部署配置文件
+> * **runtime_option**(RuntimeOption): 后端推理配置，默认为None，即采用默认配置
+> * **model_format**(ModelFormat): 模型格式，默认为Paddle格式
+
+### predict函数
+
+> ```python 
+> PPTracking.predict(frame)
+> ```
+>
+> 模型预测结口，输入图像直接输出检测结果。
+>
+> **参数**
+>
+> > * **frame**(np.ndarray): 输入数据，注意需为HWC，BGR格式,frame为视频帧如：_,frame=cap.read()得到
+
+> **返回**
+>
+> > 返回`fastdeploy.vision.MOTResult`结构体，结构体说明参考文档[视觉模型预测结果](../../../../../docs/api/vision_results/)
+
+### 类成员属性
+#### 预处理参数
+用户可按照自己的实际需求，修改下列预处理参数，从而影响最终的推理和部署效果
+
+
+
+## 其它文档
+
+- [PP-Tracking 模型介绍](..)
+- [PP-Tracking C++部署](../cpp)
+- [模型预测结果说明](../../../../../docs/api/vision_results/)
+- [如何切换模型推理后端引擎](../../../../../docs/cn/faq/how_to_change_backend.md)
--- a/examples/vision/tracking/pptracking/python/infer.py
+++ b/examples/vision/tracking/pptracking/python/infer.py
@@ -0,0 +1,79 @@
+# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import fastdeploy as fd
+import cv2
+import time
+import os
+
+
+def parse_arguments():
+    import argparse
+    import ast
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        "--model", required=True, help="Path of PaddleSeg model.")
+    parser.add_argument(
+        "--video", type=str, required=True, help="Path of test video file.")
+    parser.add_argument(
+        "--device",
+        type=str,
+        default='cpu',
+        help="Type of inference device, support 'cpu' or 'gpu'.")
+    parser.add_argument(
+        "--use_trt",
+        type=ast.literal_eval,
+        default=False,
+        help="Wether to use tensorrt.")
+    return parser.parse_args()
+
+
+def build_option(args):
+    option = fd.RuntimeOption()
+
+    if args.device.lower() == "gpu":
+        option.use_gpu()
+
+    if args.use_trt:
+        option.use_trt_backend()
+    return option
+
+
+args = parse_arguments()
+
+# 配置runtime，加载模型
+runtime_option = build_option(args)
+model_file = os.path.join(args.model, "model.pdmodel")
+params_file = os.path.join(args.model, "model.pdiparams")
+config_file = os.path.join(args.model, "infer_cfg.yml")
+model = fd.vision.tracking.PPTracking(
+    model_file, params_file, config_file, runtime_option=runtime_option)
+
+# 预测图片分割结果
+cap = cv2.VideoCapture(args.video)
+frame_id = 0
+while True:
+    start_time = time.time()
+    frame_id = frame_id+1
+    _, frame = cap.read()
+    if frame is None:
+        break
+    result = model.predict(frame)
+    end_time = time.time()
+    fps = 1.0/(end_time-start_time)
+    img = fd.vision.vis_mot(frame, result, fps, frame_id)
+    cv2.imshow("video", img)
+    cv2.waitKey(30)
+cap.release()
+cv2.destroyAllWindows()