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# coding: utf-8
"""
Create a reference json file used for evaluation with `coco-caption` repo.
Used when reference json is not provided, (e.g., flickr30k, or you have your own split of train/val/test)
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
import json
import argparse
import sys
import hashlib
from random import shuffle, seed
def main(params):
imgs = json.load(open(params['input_json'][0], 'r'))['images']
# tmp = []
# for k in imgs.keys():
# for img in imgs[k]:
# img['filename'] = img['image_id'] # k+'/'+img['image_id']
# img['image_id'] = int(
# int(hashlib.sha256(img['image_id']).hexdigest(), 16) % sys.maxint)
# tmp.append(img)
# imgs = tmp
# create output json file
out = {'info': {'description': 'This is stable 1.0 version of the 2014 MS COCO dataset.', 'url': 'http://mscoco.org', 'version': '1.0', 'year': 2014, 'contributor': 'Microsoft COCO group', 'date_created': '2015-01-27 09:11:52.357475'}, 'licenses': [{'url': 'http://creativecommons.org/licenses/by-nc-sa/2.0/', 'id': 1, 'name': 'Attribution-NonCommercial-ShareAlike License'}, {'url': 'http://creativecommons.org/licenses/by-nc/2.0/', 'id': 2, 'name': 'Attribution-NonCommercial License'}, {'url': 'http://creativecommons.org/licenses/by-nc-nd/2.0/', 'id': 3, 'name': 'Attribution-NonCommercial-NoDerivs License'}, {'url': 'http://creativecommons.org/licenses/by/2.0/', 'id': 4, 'name': 'Attribution License'}, {'url': 'http://creativecommons.org/licenses/by-sa/2.0/', 'id': 5, 'name': 'Attribution-ShareAlike License'}, {'url': 'http://creativecommons.org/licenses/by-nd/2.0/', 'id': 6, 'name': 'Attribution-NoDerivs License'}, {'url': 'http://flickr.com/commons/usage/', 'id': 7, 'name': 'No known copyright restrictions'}, {'url': 'http://www.usa.gov/copyright.shtml', 'id': 8, 'name': 'United States Government Work'}], 'type': 'captions'}
out.update({'images': [], 'annotations': []})
cnt = 0
empty_cnt = 0
for i, img in enumerate(imgs):
if img['split'] == 'train':
continue
out['images'].append(
{'id': img.get('cocoid', img['imgid'])})
for j, s in enumerate(img['sentences']):
if len(s) == 0:
continue
s = ' '.join(s['tokens'])
out['annotations'].append(
{'image_id': out['images'][-1]['id'], 'caption': s, 'id': cnt})
cnt += 1
json.dump(out, open(params['output_json'], 'w'))
print('wrote ', params['output_json'])
if __name__ == "__main__":
parser = argparse.ArgumentParser()
# input json
parser.add_argument('--input_json', nargs='+', required=True,
help='input json file to process into hdf5')
parser.add_argument('--output_json', default='data.json',
help='output json file')
args = parser.parse_args()
params = vars(args) # convert to ordinary dict
print('parsed input parameters:')
print(json.dumps(params, indent=2))
main(params)
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