实现亮度调整和饱和度调整的方法，都是通过对原图进行修改得到的。

如果不做处理，在调整亮度之后，再进行调整饱和度，显示的结果只有饱和度的调整，没有保留上一步亮度的调整

处理办法：

通过添加flag变量作为标识位，用来标识亮度（饱和度）是否被更改。

添加imageTemp变量，保存亮度（饱和度）属性被更改后，改变后的图片，作为下一步调整的原图

    def BaoHeDu(self,value):
        print('调整饱和度{}'.format(value))
        if value == 0:
            value = 1
        if self.flag1 == 1:
            hsv_image = cv2.cvtColor(self.pic_imageTemp, cv2.COLOR_RGB2HSV)
        else:
            hsv_image = cv2.cvtColor(self.pic_image0,cv2.COLOR_BGR2HSV)#####
        h, s, v = cv2.split(hsv_image)
        v = np.clip(v + value - 50, 0, 250)
        hsv_image = cv2.merge((h, s, v))
        self.pic_image = cv2.cvtColor(hsv_image, cv2.COLOR_HSV2RGB)
        if value != 50:
            self.pic_imageTemp1 = self.pic_image
            self.flag2 = 1
        else:
            self.flag2 = 0
        self.show_pic()
    def LiangDu(self,value):
        print("调整亮度")
        if value == 0:
            value = 1
        contrast = value / 50.0  # float类型
        if self.flag2 == 1:
            self.pic_imageTemp = cv2.cvtColor(self.pic_imageTemp1, cv2.COLOR_RGB2BGR)
            tmp_image = np.float32(self.pic_imageTemp) * contrast
            #print(tmp_image)
        else:
            tmp_image = np.float32(self.pic_image0) * contrast
        tmp_image = np.clip(tmp_image, 0, 255)
        self.pic_image = np.uint8(tmp_image)
        self.pic_image = cv2.cvtColor(self.pic_image, cv2.COLOR_BGR2RGB)
        # print(value)
        if value != 50:
            self.pic_imageTemp = self.pic_image
            self.flag1 = 1
        else:
            self.flag1 = 0
        self.show_pic()