class SlideCrack(object):
    def __init__(self, gap, bg):
        """
        init code
        :param gap: 缺口圖片
        :param bg: 背景圖片
        :param out: 輸出圖片
        """
        self.front = gap
        self.bg = bg

    @staticmethod
    def clear_white(img):
        # 清除圖片的空白區域，這裡主要清除滑塊的空白
        img_data = base64.b64decode(img)
        img_array 
 
= np.fromstring(img_data, np.uint8)
        img = cv2.imdecode(img_array, cv2.COLOR_RGB2BGR)
        rows, cols, channel = img.shape
        min_x = 255
        min_y = 255
        max_x = 0
        max_y = 0
        for x in range(1, rows):
            for y in range(1, cols):
                t = set(img[x, y])
                
 
if len(t) >= 2:
                    if x <= min_x:
                        min_x = x
                    elif x >= max_x:
                        max_x = x

                    if y <= min_y:
                        min_y = y
                    elif y >= max_y:
                        max_y 
 
= y
        img1 = img[min_x:max_x, min_y: max_y]
        return img1

    def template_match(self, tpl, target):
        th, tw = tpl.shape[:2]
        result = cv2.matchTemplate(target, tpl, cv2.TM_CCOEFF_NORMED)
        # 尋找矩陣(一維陣列當作向量,用Mat定義) 中最小值和最大值的位置
        min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(result)
        tl = max_loc
        br = (tl[0] + tw, tl[1] + th)
        # 繪製矩形邊框，將匹配區域標註出來
        # target：目標影象
        # tl：矩形定點
        # br：矩形的寬高
        # (0,0,255)：矩形邊框顏色
        # 1：矩形邊框大小
        cv2.rectangle(target, tl, br, (0, 0, 255), 2)
        return tl

    @staticmethod
    def image_edge_detection(img):
        edges = cv2.Canny(img, 100, 200)
        return edges

    def discern(self):
        img1 = self.clear_white(self.front)
        img1 = cv2.cvtColor(img1, cv2.COLOR_RGB2GRAY)
        slide = self.image_edge_detection(img1)
        img_data = base64.b64decode(self.bg)
        img_array = np.fromstring(img_data, np.uint8)
        back = cv2.imdecode(img_array, cv2.COLOR_RGB2BGR)
        back = self.image_edge_detection(back)

        slide_pic = cv2.cvtColor(slide, cv2.COLOR_GRAY2RGB)
        back_pic = cv2.cvtColor(back, cv2.COLOR_GRAY2RGB)
        pos = self.template_match(slide_pic, back_pic)
        # 輸出橫座標, 即 滑塊在圖片上的位置
        return pos