python - 使用python进行相机校准

Question

我正在尝试使用棋盘法校准拖曳网络摄像头
但是每次我执行opencv示例中提供的代码源
我收到此消息:

processing ../cpp\img1.jpg... chessboard not found
processing ../cpp\img2.jpg... chessboard not found
processing ../cpp\img3.jpg... chessboard not found
processing ../cpp\img4.jpg... chessboard not found
processing ../cpp\img5.jpg... chessboard not found

这是img1
http://i.stack.imgur.com/04b4U.jpg

好的，代码是opencv示例中的代码，这里是cv2的一部分。FindChessboard()

 for fn in img_names:
    print 'processing %s...' % fn,
    img = cv2.imread(fn, 0)
    h, w = img.shape[:2]
    found, corners = cv2.findChessboardCorners(img, pattern_size)
    if found:
        term = ( cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_COUNT, 30, 0.1 )
        cv2.cornerSubPix(img, corners, (5, 5), (-1, -1), term)
    if debug_dir:
        vis = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
        cv2.drawChessboardCorners(vis, pattern_size, corners, found)
        path, name, ext = splitfn(fn)
        cv2.imwrite('%s/%s_chess.bmp' % (debug_dir, name), vis)
    if not found:
        print 'chessboard not found'
        continue
    img_points.append(corners.reshape(-1, 2))
    obj_points.append(pattern_points)

    print 'ok'

Answer 1

假设您的代码正确，则您的棋盘可能有问题。查看有关函数findChessboardCorners(link)的文档，最后有一条注释说明:

The function requires white space (like a square-thick border, the wider the better) around the board to make the detection more robust in various environments. Otherwise, if there is no border and the background is dark, the outer black squares cannot be segmented properly and so the square grouping and ordering algorithm fails.

如果您查看 this calibration tutorial， 中提供的图像，则棋盘周围会有更多空白，这很重要:

同样，这可能是一种印象，但是看来您的外部正方形与其他正方形的大小不同，这也可能很重要。