作用如题目，批量将标注好的json文件转成png标签，jpg原图，其中标签时红黑图。

代码如下：

import argparse
import base64
import json
import os
import os.path as osp
import imgviz
import PIL.Image
import yaml
from labelme.logger import logger
from labelme import utils
 
'''single json file'''
def main():
    logger.warning(
        "This script is aimed to demonstrate how to convert the "
        "JSON file to a single image dataset."
    )
    logger.warning(
        "It won't handle multiple JSON files to generate a "
        "real-use dataset."
    )
 
    parser = argparse.ArgumentParser()
    #parser.add_argument("json_file")
    parser.add_argument('--jsonfiles', nargs='?', const=True, default="datasets//before", help='resume most recent training') #设置输入路径  将default里面的路径转成json文件下的路径
    parser.add_argument("-o", "--out", default="datasets//png")  #设置输出路径 default里面的路径改为要存放标签png和原图jpg的路径
    args = parser.parse_args()
    import glob
    jsonfiles = glob.glob(args.jsonfiles+"/*.json")
    print(jsonfiles)
    for json_file in jsonfiles:
        if args.out is None:
            out_dir = osp.basename(json_file).replace(".", "_")
            out_dir = osp.join(osp.dirname(json_file), out_dir)
        else:
            out_dir = args.out
        if not osp.exists(out_dir):
            os.mkdir(out_dir)
 
        data = json.load(open(json_file))
        imageData = data.get("imageData")
 
        if not imageData:
            imagePath = os.path.join(os.path.dirname(json_file), data["imagePath"])
            with open(imagePath, "rb") as f:
                imageData = f.read()
                imageData = base64.b64encode(imageData).decode("utf-8")
        img = utils.img_b64_to_arr(imageData)
 
        label_name_to_value = {"_background_": 0}
        for shape in sorted(data["shapes"], key=lambda x: x["label"]):
            label_name = shape["label"]
            if label_name in label_name_to_value:
                label_value = label_name_to_value[label_name]
            else:
                label_value = len(label_name_to_value)
                label_name_to_value[label_name] = label_value
        lbl, _ = utils.shapes_to_label(
            img.shape, data["shapes"], label_name_to_value
        )
 
        label_names = [None] * (max(label_name_to_value.values()) + 1)
        for name, value in label_name_to_value.items():
            label_names[value] = name
 
        lbl_viz = imgviz.label2rgb(
            label=lbl, image=imgviz.asgray(img), label_names=label_names, loc="rb"
        )
 
        label_name  = json_file.split('\\')[-1].replace('.json','.png')
        image_name  = json_file.split('\\')[-1].replace('.json','.jpg')
        PIL.Image.fromarray(img).save(osp.join(out_dir, image_name))
        utils.lblsave(osp.join(out_dir, label_name), lbl)
        PIL.Image.fromarray(lbl_viz).save(osp.join(out_dir, "label_viz.png"))
 
        with open(osp.join(out_dir, "label_names.txt"), "w") as f:
            for lbl_name in label_names:
                f.write(lbl_name + "\n")
 
        # 生成info.yaml文件
        # logger.warning('info.yaml is being replaced by label_names.txt')
        # info = dict(label_names=label_names)
        # with open(osp.join(out_dir, 'info.yaml'), 'w') as f:
        #     yaml.safe_dump(info, f, default_flow_style=False)
 
        logger.info("Saved to: {}".format(out_dir))
 
if __name__ == "__main__":
    main()