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()