如何将labelme生成的json文件转换成png图片（亲测有效）

如何将labelme生成的json文件转换成png图片

• 单个转换（费时）

1.先进入到你存放json的文件夹的磁盘中,输入d:

2. 激活labelme环境

3. 输入labelme_json_to_dataset并进入到存放json的文件夹

labelme_json_to_dataset D:\data

4.完成转换

• 批量转换（等我更新）
• 更新来啦！！！（步骤）
  1、修改json_to_dataset.py代码
  这里它的地址为D:\Anaconda3\envs\labelme\Lib\site-packages\labelme\cli\json_to_dataset.py

import argparse
import json
import os
import os.path as osp
import warnings

import PIL.Image
import yaml

from labelme import utils
import base64


def main():
    warnings.warn("This script is aimed to demonstrate how to convert the\n"
                  "JSON file to a single image dataset, and not to handle\n"
                  "multiple JSON files to generate a real-use dataset.")
    parser = argparse.ArgumentParser()
    parser.add_argument('json_file')
    parser.add_argument('-o', '--out', default=None)
    args = parser.parse_args()

    json_file = args.json_file
    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)

    count = os.listdir(json_file)
    for i in range(0, len(count)):
        path = os.path.join(json_file, count[i])
        if os.path.isfile(path):
            data = json.load(open(path))

            if data['imageData']:
                imageData = data['imageData']
            else:
                imagePath = os.path.join(os.path.dirname(path), 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 data['shapes']:
                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

            # label_values must be dense
            label_values, label_names = [], []
            for ln, lv in sorted(label_name_to_value.items(), key=lambda x: x[1]):
                label_values.append(lv)
                label_names.append(ln)
            assert label_values == list(range(len(label_values)))

            lbl = utils.shapes_to_label(img.shape, data['shapes'], label_name_to_value)

            captions = ['{}: {}'.format(lv, ln)
                        for ln, lv in label_name_to_value.items()]
            lbl_viz = utils.draw_label(lbl, img, captions)

            out_dir = osp.basename(count[i]).replace('.', '_')
            out_dir = osp.join(osp.dirname(count[i]), out_dir)
            if not osp.exists(out_dir):
                os.mkdir(out_dir)

            PIL.Image.fromarray(img).save(osp.join(out_dir, 'img.png'))
            # PIL.Image.fromarray(lbl).save(osp.join(out_dir, 'label.png'))
            utils.lblsave(osp.join(out_dir, 'label.png'), 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')

            warnings.warn('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)

            print('Saved to: %s' % out_dir)


if __name__ == '__main__':
    main()

2、找到json_to_dataset.exe的地址
这里我的地址是：D:\Anaconda3\envs\labelme\Scripts
3、在cmd中操作

• 激活labelme
  在cmd中输入activate labelme
• 切换到d盘，然后转到json_to_dataset.exe的地址
• 输入labelme_json_to_dataset.exe和生成的json文件夹
• 最后生成的文件在D:\Anaconda3\envs\labelme\Scripts地址中
  
  4、可能错误
  如果出现 module ‘labelme.utils’ has no attribute 'draw_label’错误，应该是 labelme版本问题。在cmd中输入pip install labelme==3.16.2，下载 labelme3.16.2版本

参考链接：
https://blog.csdn.net/weixin_44715623/article/details/106807501?utm_medium=distribute.pc_relevant.none-task-blog-baidujs_title-0&spm=1001.2101.3001.4242
https://blog.csdn.net/weixin_47286519/article/details/116993802