python类fastNlMeansDenoisingColored()的实例源码

def skin_detect(self, raw_yrb, img_src):
        # use median blurring to remove signal noise in YCRCB domain
        raw_yrb = cv2.medianBlur(raw_yrb, 5)
        mask_skin = cv2.inRange(raw_yrb, self.mask_lower_yrb, self.mask_upper_yrb)

        # morphological transform to remove unwanted part
        kernel = np.ones((5, 5), np.uint8)
        #mask_skin = cv2.morphologyEx(mask_skin, cv2.MORPH_OPEN, kernel)
        mask_skin = cv2.dilate(mask_skin, kernel, iterations=2)

        res_skin = cv2.bitwise_and(img_src, img_src, mask=mask_skin)
        #res_skin_dn = cv2.fastNlMeansDenoisingColored(res_skin, None, 10, 10, 7,21)

        return res_skin


# Do background subtraction with some filtering

def denoise_image(image, value):
    if (value < 0):
        value = 0
    elif (value > 100):
        value = 100
    return cv2.fastNlMeansDenoisingColored(image, None, value, value)

def non_local_means_color_py(imgs, search_window, block_size, photo_render):
    import cv2
    ret_imgs = opencv_wrapper(imgs, cv2.fastNlMeansDenoisingColored, [None,photo_render,photo_render,block_size,search_window])
    return ret_imgs