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2021-09-08 23:58
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已结题

使用 Python+opencv实现视频中的物体识别

需求 : 使用 Python+opencv实现视频中的物体识别,
细节描述 : 用电子设备录制视屏, 对此视频进行识别,里面可能任何物品。

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  • String name="小吴"; 2021-09-09 00:41
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    #!/user/bin/env python3
    # -*- coding: utf-8 -*-
    
    
    import cv2
    
    # 深度学习-图像识别
    def getContuors(img):
        contours, hierarchy = cv2.findContours(img, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
        for cnt in contours:
            area = cv2.contourArea(cnt)
            # print(area)
            if area > 500:
                cv2.drawContours(imgContour, cnt, -1, (0, 0, 0), 1)
                peri = cv2.arcLength(cnt, True)  # 轮廓长度
                approx = cv2.approxPolyDP(cnt, 0.02 * peri, True)
                objCor = len(approx)
                # print(objCor)
                x, y, w, h = cv2.boundingRect(approx)
                if objCor == 3:
                    objectType = 'Tri'
                elif objCor == 4:
                    aspRatio = w / float(h)
                    # print(aspRatio)
                    if aspRatio > 0.95 and aspRatio < 1.05:
                        objectType = 'ZFX'
                    else:
                        objectType = 'CFX'
                elif objCor > 4:
                    objectType = 'YX'
    
                else:
                    objectType = 'NONE'
                cv2.rectangle(imgContour, (x, y), (x + w, y + h), (255, 0, 0), 1)
                cv2.putText(imgContour, objectType, (x + (w // 2) - 10, y + (h // 5) - 10), cv2.FONT_HERSHEY_COMPLEX, 0.5,
                            (0, 0, 0), 2)
    
    
    img = cv2.imread('ss.png')
    imgsize = cv2.resize(img, (500, 400))  # 裁剪后
    imgContour = imgsize.copy()
    imgGRAY = cv2.cvtColor(imgsize, cv2.COLOR_BGR2GRAY)
    imgBlur = cv2.GaussianBlur(imgGRAY, (7, 7), 1)  # 模糊度
    imgCann = cv2.Canny(imgBlur, 50, 50)
    getContuors(imgCann)
    if __name__ == '__main__':
        cv2.imshow('windows', imgCann)
        cv2.imshow('window', imgContour)
        cv2.waitKey(0)
    
    
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