labelmeWithAI/labelme/cli/json_to_dataset.py

import argparse
import base64
import json
import os
import os.path as osp
import warnings

import PIL.Image
import yaml

from labelme import utils


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)

    data = json.load(open(json_file))

    if data['imageData']:
        imageData = data['imageData']
    else:
        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 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)

    PIL.Image.fromarray(img).save(osp.join(out_dir, 'img.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()