[Model] Support YOLOv7-face Model (#651)

* 测试

* delete test

* add yolov7-face

* fit vision.h

* add yolov7-face test

* fit: yolov7-face infer.cc

* fit

* fit Yolov7-face Cmakelist

* fit yolov7Face.cc

* add yolov7-face pybind

* add yolov7-face python infer

* feat yolov7-face pybind

* feat yolov7-face format error

* feat yolov7face_pybind error

* feat add yolov7face-pybind to facedet-pybind

* same as before

* same sa before

* feat __init__.py

* add yolov7face.py

* feat yolov7face.h ignore ","

* feat .py

* fit yolov7face.py

* add yolov7face test teadme file

* add test file

* fit postprocess

* delete remain annotation

* fit preview

* fit yolov7facepreprocessor

* fomat code

* fomat code

* fomat code

* fit format error and confthreshold and nmsthres

* fit confthreshold and nmsthres

* fit test-yolov7-face

* fit test_yolov7face

* fit review

* fit ci error

Co-authored-by: kongbohua <kongbh2022@stu.pku.edu.cn>
Co-authored-by: CoolCola <49013063+kongbohua@users.noreply.github.com>

examples/vision/facedet/yolov7face/python/README.md

@@ -0,0 +1,87 @@
+# YOLOv7Face 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YOLOv7Face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 examples/vision/facedet/yolov7face/python/
+
+#下载YOLOv7Face模型文件和测试图片
+wget https://raw.githubusercontent.com/DefTruth/lite.ai.toolkit/main/examples/lite/resources/test_lite_face_detector_3.jpg
+wget https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-lite-e.onnx
+
+#使用yolov7-tiny-face.onnx模型
+# CPU推理
+python infer.py --model yolov7-tiny-face.onnx --image test_lite_face_detector_3.jpg --device cpu
+# GPU推理
+python infer.py --model yolov7-tiny-face.onnx --image test_lite_face_detector_3.jpg --device gpu
+# GPU上使用TensorRT推理
+python infer.py --model yolov7-tiny-face.onnx --image test_lite_face_detector_3.jpg --device gpu --use_trt True
+
+#使用yolov7-lite-e.onnx模型
+# CPU推理
+python infer.py --model yolov7-lite-e.onnx --image test_lite_face_detector_3.jpg --device cpu
+# GPU推理
+python infer.py --model yolov7-lite-e.onnx --image test_lite_face_detector_3.jpg --device gpu
+# GPU上使用TensorRT推理
+python infer.py --model yolov7-lite-e.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
+
+<img width="640" src="https://user-images.githubusercontent.com/67993288/184301839-a29aefae-16c9-4196-bf9d-9c6cf694f02d.jpg">
+
+## YOLOv7Face Python接口
+
+```python
+fastdeploy.vision.facedet.YOLOv7Face(model_file, params_file=None, runtime_option=None, model_format=ModelFormat.ONNX)
+```
+
+YOLOv7Face模型加载和初始化，其中model_file为导出的ONNX模型格式
+
+**参数**
+
+> * **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
+
+### predict函数
+
+> ```python
+> YOLOv7Face.predict(image_data, conf_threshold=0.3, nms_iou_threshold=0.5)
+> ```
+>
+> 模型预测结口，输入图像直接输出检测结果。
+>
+> **参数**
+>
+> > * **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
+
+> **返回**
+>
+> > 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/)
+
+### 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
+
+> > * **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[640, 640]
+> > * **padding_value**(list[float]): 通过此参数可以修改图片在resize时候做填充(padding)的值, 包含三个浮点型元素, 分别表示三个通道的值, 默认值为[114, 114, 114]
+> > * **is_no_pad**(bool): 通过此参数让图片是否通过填充的方式进行resize, `is_no_pad=True` 表示不使用填充的方式，默认值为`is_no_pad=False`
+> > * **is_mini_pad**(bool): 通过此参数可以将resize之后图像的宽高这是为最接近`size`成员变量的值, 并且满足填充的像素大小是可以被`stride`成员变量整除的。默认值为`is_mini_pad=False`
+> > * **stride**(int): 配合`is_mini_pad`成员变量使用, 默认值为`stride=32`
+
+## 其它文档
+
+- [YOLOv7Face 模型介绍](..)
+- [YOLOv7Face C++部署](../cpp)
+- [模型预测结果说明](../../../../../docs/api/vision_results/)