How to use _get_target_rectangle method in Airtest

Best Python code snippet using Airtest

template.py

Source:template.py Github

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...19 h, w = im_search.shape[:2]20 # 求取可信度:21 confidence = _get_confidence_from_matrix(im_source, im_search, max_loc, max_val, w, h, rgb)22 # 求取识别位置: 目标中心 + 目标区域:23 # middle_point, rectangle = _get_target_rectangle(max_loc, w, h)24 # best_match = generate_result(middle_point, rectangle, confidence)25 # LOGGING.debug("threshold=%s, result=%s" % (threshold, best_match))26 # return best_match if confidence >= threshold else None27 print confidence28 return True if confidence >= threshold else None29def find_all_template(im_source, im_search, threshold=0.8, rgb=False, max_count=10):30 """根据输入图片和参数设置,返回所有的图像识别结果."""31 # 第一步：校验图像输入32 check_source_larger_than_search(im_source, im_search)33 # 第二步：计算模板匹配的结果矩阵res34 res = _get_template_result_matrix(im_source, im_search)35 # 第三步：依次获取匹配结果36 result = []37 h, w = im_search.shape[:2]38 while True:39 # 本次循环中,取出当前结果矩阵中的最优值40 min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)41 # 求取可信度:42 confidence = _get_confidence_from_matrix(im_source, im_search, max_loc, max_val, w, h, rgb)43 if confidence < threshold or len(result) > max_count:44 break45 # 求取识别位置: 目标中心 + 目标区域:46 middle_point, rectangle = _get_target_rectangle(max_loc, w, h)47 one_good_match = generate_result(middle_point, rectangle, confidence)48 result.append(one_good_match)49 # 屏蔽已经取出的最优结果,进入下轮循环继续寻找:50 cv2.floodFill(res, None, max_loc, (-1000,), max(max_val, 0), flags=cv2.FLOODFILL_FIXED_RANGE)51 return result if result else None52def _get_confidence_from_matrix(im_source, im_search, max_loc, max_val, w, h, rgb):53 """根据结果矩阵求出confidence."""54 # 求取可信度:55 if rgb:56 # 如果有颜色校验,对目标区域进行BGR三通道校验:57 img_crop = im_source[max_loc[1]:max_loc[1] + h, max_loc[0]: max_loc[0] + w]58 confidence = cal_rgb_confidence(img_crop, im_search)59 else:60 confidence = max_val61 return confidence62def _get_template_result_matrix(im_source, im_search):63 """求取模板匹配的结果矩阵."""64 # 灰度识别: cv2.matchTemplate( )只能处理灰度图片参数65 s_gray, i_gray = img_mat_rgb_2_gray(im_search), img_mat_rgb_2_gray(im_source)66 return cv2.matchTemplate(i_gray, s_gray, cv2.TM_CCOEFF_NORMED)67def _get_target_rectangle(left_top_pos, w, h):68 """根据左上角点和宽高求出目标区域."""69 x_min, y_min = left_top_pos70 # 中心位置的坐标:71 x_middle, y_middle = int(x_min + w / 2), int(y_min + h / 2)72 # 左下(min,max)->右下(max,max)->右上(max,min)73 left_bottom_pos, right_bottom_pos = (x_min, y_min + h), (x_min + w, y_min + h)74 right_top_pos = (x_min + w, y_min)75 # 点击位置:76 middle_point = (x_middle, y_middle)77 # 识别目标区域: 点序:左上->左下->右下->右上, 左上(min,min)右下(max,max)78 rectangle = (left_top_pos, left_bottom_pos, right_bottom_pos, right_top_pos)...

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