HandRecognition.py 文件源码

def hand_threshold(frame_in,hand_hist):
    frame_in=cv2.medianBlur(frame_in,3)
    hsv=cv2.cvtColor(frame_in,cv2.COLOR_BGR2HSV)
    hsv[0:int(cap_region_y_end*hsv.shape[0]),0:int(cap_region_x_begin*hsv.shape[1])]=0 # Right half screen only
    hsv[int(cap_region_y_end*hsv.shape[0]):hsv.shape[0],0:hsv.shape[1]]=0
    back_projection = cv2.calcBackProject([hsv], [0,1],hand_hist, [00,180,0,256], 1)
    disc = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (morph_elem_size,morph_elem_size))
    cv2.filter2D(back_projection, -1, disc, back_projection)
    back_projection=cv2.GaussianBlur(back_projection,(gaussian_ksize,gaussian_ksize), gaussian_sigma)
    back_projection=cv2.medianBlur(back_projection,median_ksize)
    ret, thresh = cv2.threshold(back_projection, hsv_thresh_lower, 255, 0)

    return thresh

# 3. Find hand contour