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* 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>
71 lines
2.9 KiB
Markdown
71 lines
2.9 KiB
Markdown
# PP-Tracking Python部署示例
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在部署前，需确认以下两个步骤
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- 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)
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- 2. FastDeploy Python whl包安装，参考[FastDeploy Python安装](../../../../../docs/cn/build_and_install/download_prebuilt_libraries.md)
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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
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```bash
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#下载部署示例代码
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git clone https://github.com/PaddlePaddle/FastDeploy.git
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cd FastDeploy/examples/vision/tracking/pptracking/python
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# 下载PP-Tracking模型文件和测试视频
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wget https://bj.bcebos.com/paddlehub/fastdeploy/fairmot_hrnetv2_w18_dlafpn_30e_576x320.tgz
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tar -xvf fairmot_hrnetv2_w18_dlafpn_30e_576x320.tgz
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wget https://bj.bcebos.com/paddlehub/fastdeploy/person.mp4
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# CPU推理
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python infer.py --model fairmot_hrnetv2_w18_dlafpn_30e_576x320 --video person.mp4 --device cpu
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# GPU推理
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python infer.py --model fairmot_hrnetv2_w18_dlafpn_30e_576x320 --video person.mp4 --device gpu
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# 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）
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python infer.py --model fairmot_hrnetv2_w18_dlafpn_30e_576x320 --video person.mp4 --device gpu --use_trt True
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```
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## PP-Tracking Python接口
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```python
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fd.vision.tracking.PPTracking(model_file, params_file, config_file, runtime_option=None, model_format=ModelFormat.PADDLE)
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```
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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)
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**参数**
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> * **model_file**(str): 模型文件路径
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> * **params_file**(str): 参数文件路径
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> * **config_file**(str): 推理部署配置文件
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> * **runtime_option**(RuntimeOption): 后端推理配置，默认为None，即采用默认配置
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> * **model_format**(ModelFormat): 模型格式，默认为Paddle格式
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### predict函数
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> ```python
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> PPTracking.predict(frame)
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> ```
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>
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> 模型预测结口，输入图像直接输出检测结果。
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>
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> **参数**
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>
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> > * **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
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> **返回**
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>
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> > 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/)
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### 类成员属性
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#### 预处理参数
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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
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## 其它文档
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- [PP-Tracking 模型介绍](..)
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- [PP-Tracking C++部署](../cpp)
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- [模型预测结果说明](../../../../../docs/api/vision_results/)
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- [如何切换模型推理后端引擎](../../../../../docs/cn/faq/how_to_change_backend.md)
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