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import pandas as pd |
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import os.path |
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import sys |
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import json |
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import logging |
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import contexttimer |
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logging.basicConfig(filename='download.log', filemode='w', level=logging.INFO) |
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if len(sys.argv) != 4: |
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print("Provide .tsv file name, images dir, output file name. e.g. python coco.py coco_captions_train2017.json /mnt/disks/data-1/flickr8k/coco_train.json coco_dataset_train.json") |
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exit(1) |
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annotation_file = sys.argv[1] |
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images_dir = sys.argv[2] |
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output_file = sys.argv[3] |
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logging.info("Processing cc12m dataset") |
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with contexttimer.Timer(prefix="Loading from tsv"): |
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df = pd.read_csv(annotation_file, delimiter='\t') |
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lines = [] |
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df = df[["caption", "url"]] |
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print(f"Loaded {len(df)} images.") |
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for index, caption_reference_description, image_url in df.itertuples(): |
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index+=1 |
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base_url = os.path.basename(image_url) |
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stem, ext = os.path.splitext(base_url) |
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filename = f'{index:08d}---{stem}.jpg' |
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full_image_path = images_dir+"/"+filename |
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if os.path.isfile(full_image_path): |
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lines.append(json.dumps({"image_path": full_image_path, "captions": [caption_reference_description]})) |
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else: |
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logging.error(full_image_path) |
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with open(output_file, "w") as f: |
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f.write("\n".join(lines)) |
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logging.info(f"Processing cc12m dataset done. {len(lines)} images processed.") |
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