skin_detector.py 文件源码

def grab_cut_mask(img_col, mask, debug=False):
    assert isinstance(img_col, numpy.ndarray), 'image must be a numpy array'
    assert isinstance(mask, numpy.ndarray), 'mask must be a numpy array'
    assert img_col.ndim == 3, 'skin detection can only work on color images'
    assert mask.ndim == 2, 'mask must be 2D'

    kernel = numpy.ones((50, 50), numpy.float32) / (50 * 50)
    dst = cv2.filter2D(mask, -1, kernel)
    dst[dst != 0] = 255
    free = numpy.array(cv2.bitwise_not(dst), dtype=numpy.uint8)

    if debug:
        scripts.display('not skin', free)
        scripts.display('grabcut input', mask)

    grab_mask = numpy.zeros(mask.shape, dtype=numpy.uint8)
    grab_mask[:, :] = 2
    grab_mask[mask == 255] = 1
    grab_mask[free == 255] = 0

    if numpy.unique(grab_mask).tolist() == [0, 1]:
        logger.debug('conducting grabcut')
        bgdModel = numpy.zeros((1, 65), numpy.float64)
        fgdModel = numpy.zeros((1, 65), numpy.float64)

        if img_col.size != 0:
            mask, bgdModel, fgdModel = cv2.grabCut(img_col, grab_mask, None, bgdModel, fgdModel, 5,
                                                   cv2.GC_INIT_WITH_MASK)
            mask = numpy.where((mask == 2) | (mask == 0), 0, 1).astype(numpy.uint8)
        else:
            logger.warning('img_col is empty')

    return mask