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import cv2
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import mediapipe as mp
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import analysisPoint as mp_drawing
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mp_holistic = mp.solutions.holistic
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import numpy as np
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class MediapipeProcess:
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def mediapipe_det(image,holistic):
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'''
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调用模型推理获得检测结果
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'''
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image.flags.writeable = False
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image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
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results = holistic.process(image)
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return results
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def get_analysis_result(image,results):
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'''
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images: 检测的图片
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results: 图片的检测结果
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对上述结果进行分析
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'''
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image.flags.writeable = True
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image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
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# face_result = mp_drawing.draw_landmarks(
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# image,
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# results.face_landmarks,
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# mp_holistic.FACEMESH_CONTOURS)
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right_hand_result = mp_drawing.draw_landmarks(
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image,
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results.right_hand_landmarks,
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mp_holistic.HAND_CONNECTIONS)
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left_hand_result = mp_drawing.draw_landmarks(
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image,
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results.left_hand_landmarks,
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mp_holistic.HAND_CONNECTIONS)
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# face_bbox = MediapipeProcess.point_to_bbox(face_result)
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right_hand_bbox = MediapipeProcess.point_to_bbox(right_hand_result)
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left_hand_bbox = MediapipeProcess.point_to_bbox(left_hand_result)
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result_dict = {'hand_bbox':[right_hand_bbox,left_hand_bbox]}
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return result_dict
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def point_to_bbox(result_list):
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'''
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根据关键点坐标，获取坐标点的最小外接矩形
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'''
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result_array = np.array(result_list)
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if result_array.all():
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rect = cv2.minAreaRect(result_array) # 得到最小外接矩形的（中心(x,y), (宽,高), 旋转角度）
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bbox = cv2.boxPoints(rect) # 获取最小外接矩形的4个顶点坐标(ps: cv2.boxPoints(rect) for OpenCV 3.x)
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bbox = np.int0(bbox)
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bbox=bbox.tolist()
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left_top = [min(bbox, key=lambda p: p[0])[0], min(bbox, key=lambda p: p[1])[1]]
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right_bottom = [max(bbox, key=lambda p: p[0])[0], max(bbox, key=lambda p: p[1])[1]]
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bbox_list = left_top + right_bottom
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return bbox_list
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