# 移除视频数据的背景噪声
def _remove_background(frame):
fgbg = cv2.createBackgroundSubtractorMOG2() # 利用BackgroundSubtractorMOG2算法消除背景
# fgmask = bgModel.apply(frame)
fgmask = fgbg.apply(frame)
# kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (3, 3))
# res = cv2.morphologyEx(fgmask, cv2.MORPH_OPEN, kernel)
kernel = np.ones((3, 3), np.uint8)
fgmask = cv2.erode(fgmask, kernel, iterations=1)
res = cv2.bitwise_and(frame, frame, mask=fgmask)
return res
# 视频数据的人体皮肤检测
def _divskin_detetc(frame):
# 肤色检测: YCrCb之Cr分量 + OTSU二值化
ycrcb = cv2.cvtColor(frame, cv2.COLOR_BGR2YCrCb) # 分解为YUV图像,得到CR分量
(_, cr, _) = cv2.split(ycrcb)
cr1 = cv2.GaussianBlur(cr, (5, 5), 0) # 高斯滤波
_, skin = cv2.threshold(cr1, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU) # OTSU图像二值化
return skin