OpenCV DNN-尝试对象检测-元组索引超出范围

Question

我正在尝试使用在Darknet YOLO上训练的模型来使用OpenCV DNN模块检测对象。以下是令人关注的摘要。所有必需的库均已导入。

# Create a 4D blob from a frame.
blob = cv.dnn.blobFromImage(frame, 1/255, (inpWidth, inpHeight), [0,0,0], 1, crop=False)

# Sets the input to the network
net.setInput(blob)

# Runs the forward pass to get output of the output layers
outs = net.forward()
rects = []
#Tracker code
for i in range(0, outs.shape[2]):
    # filter out weak detections by ensuring the predicted
    # probability is greater than a minimum threshold
    if outs[0, 0, i, 2] > args['confidence']:
        print (outs[0,0,i,2])
        # compute the (x, y)-coordinates of the bounding box for
        # the object, then update the bounding box rectangles list
        box = outs[0, 0, i, 3:7] * np.array([frame.shape[1], frame.shape[0], frame.shape[1], frame.shape[0]])
        rects.append(box.astype("int"))

        # draw a bounding box surrounding the object so we can
        # visualize it
        (startX, startY, endX, endY) = box.astype("int")
        cv2.rectangle(frame, (startX, startY), (endX, endY),
            (0, 255, 0), 2)

此部分引发以下错误：

     for i in range(0, outs.shape[2]):
     IndexError: tuple index out of range

从网络获得的检测结果需要进行循环，以过滤掉具有低置信度得分的检测结果。 “输出”数组存储所有宽松的检测坐标。

在这种情况下，请帮助找出为什么元组索引超出范围？