【Python】Opencv检测行人

Bertha 。 2022-12-27 07:42 229阅读 0赞

# coding:utf-8
    
    import cv2
    from timeit import default_timer as timer
    
    
    class Predict(object):
        def __init__(self):
            # 获取hog检测器对象
            self.hog = cv2.HOGDescriptor()
            # 设置检测人的默认检测器
            self.hog.setSVMDetector(cv2.HOGDescriptor_getDefaultPeopleDetector())
            print("模型加载完成！")
    
        # 检测i方框 包含o方框
        def is_inside(self, o, i):
            ox, oy, ow, oh = o
            ix, iy, iw, ih = i
            return ox > ix and ox + ow < ix + iw and oy + oh < iy + ih
    
        # 将人外面的方框画出来
        def draw_person(self, image, person):
            x, y, w, h = person
            cv2.rectangle(image, (x, y), (x+w, y+h), (0, 255, 255), 2)
    
        def detect_img(self, img):
            # 在图片中检测人，
            # 返回found列表 每个元素是一个(x, y, w, h)的矩形，w是每一个矩形的置信度
            found, w = self.hog.detectMultiScale(img)
            found_filtered = []
            # 如果方框有包含，只留下内部的小方块
            for ri, r in enumerate(found):
                for qi, q in enumerate(found):
                    if ri != qi and self.is_inside(r, q):
                        break
                    else:
                        found_filtered.append(r)
    
            # 将每一个方块画出来
            for person in found_filtered:
                self.draw_person(img, person)
    
            return img
    
        def detect_video(self, video_path):
            vid = cv2.VideoCapture(video_path)
            if not vid.isOpened():
                raise IOError("Couldn't open webcam or video")
    
            while True:
                return_value, frame = vid.read()
                t1 = timer()
                result = self.detect_img(frame)
                t2 = timer()
                fps = 1 / (t2 - t1)
                print(fps)
                cv2.imshow("person detection", result)
                if cv2.waitKey(1) & 0xFF == ord('q'):
                    break
    
    
    if __name__ == '__main__':
        predict = Predict()
        # 检测图片
        if False:
            img = cv2.imread("person1.jpg")
            result = predict.detect_img(img)
            cv2.imshow("person detection", result)
            cv2.waitKey()
            cv2.destroyAllWindows()
    
        # 检测视频
        if True:
            video_path = 'video1.mp4'
            predict.detect_video(video_path=video_path)