Python 通过MobilenetSSD检测循环

我有一个问题可能很简单，但我发现代码中有一部分很难理解

for subdir, dirs, files in os.walk(directory):
    for file in files:
        filepath = subdir + os.sep + file
        image = cv2.imread(filepath)
        (h, w) = image.shape[:2]
        blob = cv2.dnn.blobFromImage(cv2.resize(image, (300, 300)), 0.007843, (300, 300), 127.5)

        # pass the blob through the neural network
        net.setInput(blob)
        detections = net.forward()

        # loop over the detections
        for i in np.arange(0, detections.shape[2]):
            # extract the confidence (i.e., the probability) associated with the prediction
            confidence = detections[0, 0, i, 2]

            if confidence > 0.2:
                idx = int(detections[0, 0, i, 1])
                box = detections[0, 0, i, 3:7] * np.array([w, h, w, h])
                (startX, startY, endX, endY) = box.astype('int')

                label = '{}: {:.2f}%'.format(CLASSES[idx], confidence * 100)
                print(label)
                label2 = "{}".format(CLASSES[idx])
                cv2.rectangle(image, (startX, startY), (endX, endY), COLORS[idx], 2)
                y = startY - 15 if startY - 15 > 15 else startY + 15
                cv2.putText(image, label, (startX, y), cv2.FONT_HERSHEY_SIMPLEX, 0.5, COLORS[idx], 2)
                if label2 == 'person':
                    cv2.imwrite('output/persons/pic' + str(number) + '.jpg', image)
                    number += 1 
            

现在，脚本以不需要的方式运行。例如，如果图片有五个人，它会将同一张图片保存五次。如果我是对的，就是这个部分导致了问题，因为它循环了图片中的所有检测：

# loop over the detections
        for i in np.arange(0, detections.shape[2]):
            # extract the confidence (i.e., the probability) associated with the prediction
            confidence = detections[0, 0, i, 2]

如果照片中有人，我想保存一次。我不知道如何修改脚本，因为np.arange（0，detections.shape[2]）中I的

I

：也用于

置信度
和
idx
值中。所以仅仅把东西从循环中移出是行不通的。欢迎任何建议和帮助