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Hu Chuqi
2023-01-06 09:34:28 +08:00
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examples/vision/facedet/ultraface/python/README.md
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# UltraFace Python部署示例
English | [简体中文](README_CN.md)
# UltraFace Python Deployment Example
在部署前，需确认以下两个步骤
Before deployment, two steps require confirmation
- 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)
- 1. Software and hardware should meet the requirements. Please refer to [FastDeploy Environment Requirements](../../../../../docs/cn/build_and_install/download_prebuilt_libraries.md)
- 2. Install FastDeploy Python whl package. Refer to [FastDeploy Python Installation](../../../../../docs/cn/build_and_install/download_prebuilt_libraries.md)
本目录下提供`infer.py`快速完成UltraFace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
This directory provides examples that `infer.py` fast finishes the deployment of UltraFace on CPU/GPU and GPU accelerated by TensorRT. The script is as follows
```bash
#下载部署示例代码
# Download the example code for deployment
git clone https://github.com/PaddlePaddle/FastDeploy.git
cd examples/vision/facedet/ultraface/python/
#下载ultraface模型文件和测试图片
# Download ultraface model files and test images
wget https://bj.bcebos.com/paddlehub/fastdeploy/version-RFB-320.onnx
wget https://raw.githubusercontent.com/DefTruth/lite.ai.toolkit/main/examples/lite/resources/test_lite_face_detector_3.jpg
# CPU推理
# CPU inference
python infer.py --model version-RFB-320.onnx --image test_lite_face_detector_3.jpg --device cpu
# GPU推理
# GPU inference
python infer.py --model version-RFB-320.onnx --image test_lite_face_detector_3.jpg --device gpu
# GPU上使用TensorRT推理
# TensorRT inference on GPU
python infer.py --model version-RFB-320.onnx --image test_lite_face_detector_3.jpg --device gpu --use_trt True
```
运行完成可视化结果如下图所示
The visualized result after running is as follows
<img width="640" src="https://user-images.githubusercontent.com/67993288/184301821-0788483b-a72b-42b0-a566-b6430f184f6e.jpg">
## UltraFace Python接口
## UltraFace Python Interface
```python
fastdeploy.vision.facedet.UltraFace(model_file, params_file=None, runtime_option=None, model_format=ModelFormat.ONNX)
```
UltraFace模型加载和初始化，其中model_file为导出的ONNX模型格式
UltraFace model loading and initialization, among which model_file is the exported ONNX model format
**参数**
**Parameter**
> * **model_file**(str): 模型文件路径
> * **params_file**(str): 参数文件路径，当模型格式为ONNX格式时，此参数无需设定
> * **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ONNX
> * **model_file**(str): Model file path
> * **params_file**(str): Parameter file path. No need to set when the model is in ONNX format
> * **runtime_option**(RuntimeOption): Backend inference configuration. None by default, which is the default configuration
> * **model_format**(ModelFormat): Model format. ONNX format by default
### predict函数
### predict function
> ```python
> UltraFace.predict(image_data, conf_threshold=0.25, nms_iou_threshold=0.5)
> ```
>
> 模型预测结口，输入图像直接输出检测结果。
> Model prediction interface. Input images and output detection results.
>
> **参数**
> **Parameter**
>
> > * **image_data**(np.ndarray): 输入数据，注意需为HWC，BGR格式
> > * **conf_threshold**(float): 检测框置信度过滤阈值
> > * **nms_iou_threshold**(float): NMS处理过程中iou阈值
> > * **image_data**(np.ndarray): Input data in HWC or BGR format
> > * **conf_threshold**(float): Filtering threshold of detection box confidence
> > * **nms_iou_threshold**(float): iou threshold during NMS processing
> **返回**
> **Return**
>
> > 返回`fastdeploy.vision.FaceDetectionResult`结构体，结构体说明参考文档[视觉模型预测结果](../../../../../docs/api/vision_results/)
> > Return `fastdeploy.vision.FaceDetectionResult` structure. Refer to [Vision Model Prediction Results](../../../../../docs/api/vision_results/) for its description.
### 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
### Class Member Property
#### Pre-processing Parameter
Users can modify the following pre-processing parameters to their needs, which affects the final inference and deployment results
> > * **size**(list[int]): 通过此参数修改预处理过程中resize的大小，包含两个整型元素，表示[width, height], 默认值为[320, 240]
> > * **size**(list[int]): This parameter changes the size of the resize used during preprocessing, containing two integer elements for [width, height] with default value [320, 240]
## 其它文档
## Other Documents
- [UltraFace 模型介绍](..)
- [UltraFace 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)
- [UltraFace Model Description](..)
- [UltraFace C++ Deployment](../cpp)
- [Model Prediction Results](../../../../../docs/api/vision_results/)
- [How to switch the model inference backend engine](../../../../../docs/cn/faq/how_to_change_backend.md)