data/scripts/coco.py

import json
import collections
import logging
import sys

if len(sys.argv) != 4:
    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")
    exit(1)

annotation_file = sys.argv[1]
images_dir = sys.argv[2]
output_file = sys.argv[3]

logging.info("Processing COCO dataset")

with open(annotation_file, "r") as f:
    annotations = json.load(f)["annotations"]

image_path_to_caption = collections.defaultdict(list)
for element in annotations:
    caption = f"{element['caption'].lower().rstrip('.')}"
    image_path = images_dir + "/%012d.jpg" % (element["image_id"])
    image_path_to_caption[image_path].append(caption)

lines = []
for image_path, captions in image_path_to_caption.items():
    lines.append(json.dumps({"image_path": image_path, "captions": captions}))

train_lines = lines[:-10_001]
valid_lines = lines[-10_001:]

with open(output_file+"_train.json", "w") as f:
    f.write("\n".join(train_lines))

with open(output_file+"_val.json", "w") as f:
    f.write("\n".join(valid_lines))

logging.info(f"Processing COCO dataset done. {len(lines)} images processed.")

# python scripts/coco.py annotations/coco_captions_train2017.json coco_dataset_train.json