camshift.py 文件源码

def count_fingers(img):
    img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

    # Otsu's thresholding after Gaussian filtering
    img = cv2.GaussianBlur(img, (5, 5), 0)
    ret, mask = cv2.threshold(img, 0, 255,
                              cv2.THRESH_BINARY_INV+cv2.THRESH_OTSU)
    cv2.imshow("Threshold", mask)

    (_, cnts, _) = cv2.findContours(mask,
                                    cv2.RETR_EXTERNAL,
                                    cv2.CHAIN_APPROX_SIMPLE)
    list_far = []
    list_end = []
    if cnts:
        areas = [cv2.contourArea(c) for c in cnts]
        max_index = np.argmax(areas)
        cnt = cnts[max_index]

        M = cv2.moments(cnt)
        cx = int(M['m10']/M['m00'])
        cy = int(M['m01']/M['m00'])

        hull1 = cv2.convexHull(cnt)

        hull2 = cv2.convexHull(cnt, returnPoints=False)

        try:
            defects = cv2.convexityDefects(cnt, hull2)
        except Exception,  e:
            defects = None
            print e

        counter = 0
        if defects is not None:
            for i in range(defects.shape[0]):
                s, e, f, d = defects[i, 0]
                # start = tuple(cnt[s][0])
                end = tuple(cnt[e][0])
                far = tuple(cnt[f][0])
                if d < 20000:
                    continue
                if far[1] >= (cy+40):
                    continue

                diff1 = abs(end[0]-far[0])
                if diff1 > 100:
                    continue

                cv2.line(img, end, far, (0, 0, 0), 2, 8)
                cv2.imshow("hand", img)
                cv2.waitKey(1)
                list_far.append(far)
                list_end.append(end)
                counter += 1

    return mask, counter, hull1, (cx, cy), list_far, list_end