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
  alist = os.listdir(json_file)
  for i in range(0,len(alist)):
    path = os.path.join(json_file,alist[i])
    data = json.load(open(path))
    out_dir = osp.basename(path).replace('.', '_')
    out_dir = osp.join(osp.dirname(path), out_dir)
    if not osp.exists(out_dir):
      os.mkdir(out_dir)
    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)
    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()