Question

所以，我已经从http://www.pyimagesearch.com/2015/05/25/basic-motion-detection-and-tracking-with-python-and-opencv/下载了这个源代码：

    # import the necessary packages
    import argparse
    import datetime
    import imutils
    import time
    import cv2
    # construct the argument parser and parse the arguments
    ap = argparse.ArgumentParser()
    ap.add_argument("-v", "--video", help="path to the video file")
    ap.add_argument("-a", "--min-area", type=int, default=500,        
    help="minimum area size")
    args = vars(ap.parse_args())
    # if the video argument is None, then we are reading from webcam
    if args.get("video", None) is None:
        camera = cv2.VideoCapture(0)
    time.sleep(0.25)

    # otherwise, we are reading from a video file
    else:
        camera = cv2.VideoCapture(args["video"])

    # initialize the first frame in the video stream
    firstFrame = None

    # loop over the frames of the video
    while True:
    # grab the current frame and initialize the occupied/unoccupied
        # text
        (grabbed, frame) = camera.read()
        text = "Unoccupied"

    # if the frame could not be grabbed, then we have reached the end
    # of the video
    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,
        # and update the text
        (x, y, w, h) = cv2.boundingRect(c)
        cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
        text = "Occupied"

但是当我运行它时，它给了我这个错误：

Traceback (most recent call last):
  File "/Users/luistripa/Downloads/basic-motion-detection/motion_detector.py", line 57, in <module>
cv2.CHAIN_APPROX_SIMPLE)
ValueError: too many values to unpack (expected 2)

任何人都可以帮我解决这个问题吗？

Answer 1

尝试在

后添加[-2：]

（cnts，_）= cv2.findContours（thresh.copy（），cv2.RETR_EXTERNAL， cv2.CHAIN_APPROX_SIMPLE）[ - 2：]

Python3使用opencv2跟踪移动

1 个答案: