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目前，下面的脚本工作得很好，但我现在想给每个矩形边界框一个标识符。

while True:
    # grab the current frame and initialize the occupied/unoccupied
    (grabbed, frame) = camera.read()

    if not grabbed:
        break

    # resize the frame, convert it to grayscale, and blur it
    frame = imutils.resize(frame, width=500)
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    gray = cv2.GaussianBlur(gray, (21, 21), 0)

    # if the first frame is None, initialize it
    if firstFrame is None:
        firstFrame = gray
        continue

    # compute the absolute difference between the current frame and
    # first frame
    frameDelta = cv2.absdiff(firstFrame, gray)
    thresh = cv2.threshold(frameDelta, 25, 255, cv2.THRESH_BINARY)[1]

    # dilate the thresholded image to fill in holes, then find contours
    # on thresholded image
    thresh = cv2.dilate(thresh, None, iterations=2)
    (_, cnts, _) = cv2.findContours(thresh.copy(),   cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)

    # loop over the contours
    for c in cnts:
        # if the contour is too small, ignore it

        if cv2.contourArea(c) < args["min_area"]:
            continue

        # compute the bounding box for the contour, draw it on the frame
        (x, y, w, h) = cv2.boundingRect(c)
        cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)

例如，给定下图：

我希望能够将四个矩形边界中的每一个识别为一个对象。（即最左边是方块皇后卡的绑定框，最右边是红桃A的绑定框）

现在，我很困惑我怎么可能做到这一点，想知道是否有人能给我灵感。

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1 回答 1

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您需要做的就是使用连续帧之间的差异找到轮廓并遍历轮廓并订购坐标以单独检测每个轮廓，然后您可以标记它们......供参考http://www.pyimagesearch.com/2016/ 03/21/ordering-coordinates-顺时针-with-python-and-opencv/

于 2016-07-01T09:57:27.753 回答