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import json
from tqdm import tqdm
def cook_data(input_file, image_path, locate_token=None, postfix='.out'):
# read a json file
print(input_file)
dataset = json.load(open(input_file, 'r', encoding='utf-8'))
with open(input_file + postfix, 'w', encoding='utf-8') as f:
for ann in tqdm(dataset['annotations']):
image_id = ann['image_id']
image_info = [img for img in dataset['images'] if img['id'] == image_id][0]
file_name = image_info['file_name']
caption = image_info['caption']
# pdb.set_trace()
if 'train2014' in file_name:
dir_name = 'train2014'
else:
dir_name = 'val2014'
if not locate_token:
sentence = f'[image]{image_path}/{dir_name}/{file_name}<tab><phrase>{caption}</phrase>'
else:
sentence = f'[image]{image_path}/{dir_name}/{file_name}<tab>{locate_token}<phrase>{caption}</phrase>'
f.write(sentence + '\n')
if __name__ == '__main__':
import argparse
parser = argparse.ArgumentParser()
parser.add_argument('json_path', help='/path/to/mdetr_annotations')
parser.add_argument('image_path', help='/path/to/MSCOCO2014 images')
args = parser.parse_args()
cook_data(f"{args.json_path}/finetune_refcoco_testA.json", args.image_path, locate_token='<grounding>', postfix='.locout')
cook_data(f"{args.json_path}/finetune_refcoco_testB.json", args.image_path, locate_token='<grounding>', postfix='.locout')
cook_data(f"{args.json_path}/finetune_refcoco_val.json", args.image_path, locate_token='<grounding>', postfix='.locout')
cook_data(f"{args.json_path}/finetune_refcoco+_testA.json", args.image_path, locate_token='<grounding>', postfix='.locout')
cook_data(f"{args.json_path}/finetune_refcoco+_testB.json", args.image_path, locate_token='<grounding>', postfix='.locout')
cook_data(f"{args.json_path}/finetune_refcoco+_val.json", args.image_path, locate_token='<grounding>', postfix='.locout')
cook_data(f"{args.json_path}/finetune_refcocog_test.json", args.image_path, locate_token='<grounding>', postfix='.locout')
cook_data(f"{args.json_path}/finetune_refcocog_val.json", args.image_path, locate_token='<grounding>', postfix='.locout')
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