feat: 修复初始无法保存图片的bug，增加stub机制以便自动跳过无图的页

from pathlib import Path

from pathlib import Path

import json

import json

debug = False

this_file = Path(__file__).resolve()

this_file = Path(__file__).resolve()

this_directory = this_file.parent

this_directory = this_file.parent

    valid_rects = list(filter(lambda rect:

    valid_rects = list(filter(lambda rect:

                    1<=(max(rect[2:])/min(rect[2:]))<=(var_dict['max_length_width_ratio']['value']/percents*10)

                    1<=(max(rect[2:])/min(rect[2:]))<=(var_dict['max_length_width_ratio']['value']/percents*10)

        , rects))

        , rects))

    if debug:

        for rect in valid_rects:

        for rect in valid_rects:

            print((max(rect[2:])/min(rect[2:])))

            print((max(rect[2:])/min(rect[2:])))

    new_img = img.copy()

    new_img = img.copy()

    path = f"{var_dict['number']['value']}-*.png"

    path = f"{var_dict['number']['value']}-*.png"

    for f in output_folder.glob(path):

    for f in output_folder.glob(path):

        f.unlink()

        f.unlink()

    if len(rects)==0:

        with open(output_folder/f"{var_dict['number']['value']}-stub.png", 'w') as f:

            f.write("该页没有文物图片。\n")

    for i, rect in enumerate(rects):

    for i, rect in enumerate(rects):

        roi = image[rect[1]:rect[1]+rect[3], rect[0]:rect[0]+rect[2]]

        roi = image[rect[1]:rect[1]+rect[3], rect[0]:rect[0]+rect[2]]

        cv2.imwrite((output_folder/f"{var_dict['number']['value']}-{i}.png").as_posix(), roi)

        cv2.imwrite((output_folder/f"{var_dict['number']['value']}-{i}.png").as_posix(), roi)

    print(f"enter: 确认标注，已保存标注结果到{path}！")

    print(f"enter: 确认标注，已保存标注结果到{output_folder/path}！")

import time

import time

last_prompt_time = time.time()

last_prompt_time = time.time()

def init():

def init():

    global current_img, visual_res, valid_rects

    cv2.namedWindow(window_name, cv2.WINDOW_NORMAL)

    cv2.namedWindow(window_name, cv2.WINDOW_NORMAL)

    cv2.resizeWindow(window_name, *window_size)

    cv2.resizeWindow(window_name, *window_size)

{"number": {"range": [1, 256], "value": 4, "comment": "\u8fd9\u662f\u5f53\u524d\u5904\u7406\u7684\u56fe\u7247\u7f16\u53f7\u3002"}, "processing_step": {"range": [0, 3], "value": 3, "comment": "0\u8868\u793a\u663e\u793a\u539f\u56fe\uff0c1\u8868\u793a\u663e\u793a\u9ed1\u767d\u5904\u7406\u56fe\uff0c2\u8868\u793a\u8f6e\u5ed3\u56fe\uff0c3\u8868\u793a\u76ee\u6807\u6846\u9009\u56fe\u3002"}, "blur_ksize": {"range": [0, 10], "value": 0, "comment": "0\u8868\u793a\u4e0d\u8fdb\u884c\u5e73\u6ed1\uff0c1-10\u8868\u793a\u6ee4\u6ce2\u7684\u8303\u56f4\u5927\u5c0f\u3002"}, "black_threshold": {"range": [0, 255], "value": 240, "comment": "\u8fd9\u662f\u7528\u4e8e\u4e8c\u503c\u5316\u56fe\u7247\u4e3a\u9ed1\u767d\u56fe\u7247\u7684\u9608\u503c\uff0c\u5927\u4e8e\u8fd9\u4e2a\u4eae\u5ea6\u503c\u7684\u50cf\u7d20\u4f1a\u53d8\u6210\u9ed1\u8272\uff0c\u5176\u4ed6\u5730\u65b9\u662f\u767d\u8272\u3002"}, "min_valid_area": {"range": [0, 1000], "value": 1, "comment": "\u8fd9\u662f\u60f3\u8981\u68c0\u6d4b\u7684\u5185\u56fe\u6700\u5c0f\u53ef\u4ee5\u63a5\u53d7\u7684\u9762\u79ef\u3002(\u5355\u4f4d\u662f1000\u5206\u6570)"}, "max_valid_area": {"range": [0, 1000], "value": 998, "comment": "\u8fd9\u662f\u60f3\u8981\u68c0\u6d4b\u7684\u5185\u56fe\u6700\u5927\u53ef\u4ee5\u63a5\u53d7\u7684\u9762\u79ef\u3002(\u5355\u4f4d\u662f1000\u5206\u6570)"}, "max_length_width_ratio": {"range": [0, 1000], "value": 1000, "comment": "\u8fd9\u662f\u60f3\u8981\u68c0\u6d4b\u7684\u5185\u56fe\u6700\u5927\u7684\u957f\u5bbd\u6bd4\u3002(\u5355\u4f4d\u662f1000\u5206\u6bd4\uff0c\u53d6\u52301000/1000\u65f6\u6700\u5927\u957f\u5bbd\u6bd4\u662f10\u3002)"}}

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