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6d7fe91a98
* format * remove abs path * init add flickr30k caption * remove abs dir * update blip readme * add convert sscripts * minor * minor
57 lines
1.7 KiB
Python
57 lines
1.7 KiB
Python
# Copyright (c) OpenMMLab. All rights reserved.
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"""Create COCO-Style GT annotations based on raw annotation of Flickr30k.
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GT annotations are used for evaluation in image caption task.
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"""
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import json
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def main():
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with open('dataset_flickr30k.json', 'r') as f:
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annotations = json.load(f)
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ann_list = []
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img_list = []
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splits = ['train', 'val', 'test']
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for split in splits:
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for img in annotations['images']:
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# img_example={
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# "sentids": [0, 1, 2],
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# "imgid": 0,
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# "sentences": [
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# {"raw": "Two men in green shirts standing in a yard.",
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# "imgid": 0, "sentid": 0},
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# {"raw": "A man in a blue shirt standing in a garden.",
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# "imgid": 0, "sentid": 1},
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# {"raw": "Two friends enjoy time spent together.",
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# "imgid": 0, "sentid": 2}
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# ],
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# "split": "train",
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# "filename": "1000092795.jpg"
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# },
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if img['split'] != split:
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continue
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img_list.append({'id': img['imgid']})
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for sentence in img['sentences']:
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ann_info = {
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'image_id': img['imgid'],
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'id': sentence['sentid'],
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'caption': sentence['raw']
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}
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ann_list.append(ann_info)
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json_file = {'annotations': ann_list, 'images': img_list}
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# generate flickr30k_train_gt.json, flickr30k_val_gt.json
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# and flickr30k_test_gt.json
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with open(f'flickr30k_{split}_gt.json', 'w') as f:
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json.dump(json_file, f)
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if __name__ == '__main__':
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main()
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