[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/infer.py

@@ -0,0 +1,51 @@
+import fastdeploy as fd
+import cv2
+
+
+def parse_arguments():
+    import argparse
+    import ast
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        "--model", required=True, help="Path of yolov7face onnx model.")
+    parser.add_argument(
+        "--image", required=True, help="Path of test image 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()
+        option.set_trt_input_shape("images", [1, 3, 640, 640])
+    return option
+
+
+args = parse_arguments()
+
+# Configure runtime and load the model
+runtime_option = build_option(args)
+model = fd.vision.facedet.YOLOv7Face(args.model, runtime_option=runtime_option)
+
+# Predict image detection results
+im = cv2.imread(args.image)
+result = model.predict(im)
+print(result)
+# Visualization of prediction Results
+vis_im = fd.vision.vis_face_detection(im, result)
+cv2.imwrite("visualized_result.jpg", vis_im)
+print("Visualized result save in ./visualized_result.jpg")