Datasets:
Tasks:
Object Detection
Modalities:
Image
Formats:
imagefolder
Languages:
English
Size:
1K - 10K
License:
#!/usr/bin/env python3 | |
from pycocotools.coco import COCO | |
import os | |
import shutil | |
import json | |
# MODIFY ME! | |
# --------------------------------- | |
coco_dataset='/opt/datasets/coco/' | |
year='2017' | |
splits=['train', 'val'] | |
dst_dir='citw' | |
metadata='metadata.jsonl' | |
# --------------------------------- | |
def process_split(coco_dataset, year, split, dst_dir, metadata): | |
annotations=f'{coco_dataset}/annotations/instances_{split}{year}.json' | |
coco=COCO(annotations) | |
cats =coco.loadCats(coco.getCatIds()) | |
target_name='cell phone' | |
target_id=coco.getCatIds(catNms=[target_name])[0]; | |
print(f'Found "{target_name}" id: {target_id}') | |
image_ids=coco.getImgIds(catIds=[target_id]); | |
images=coco.loadImgs(image_ids) | |
print(f'Found {len(images)} images containing a "{target_name}"') | |
image_dir=f'{coco_dataset}/{split}{year}/' | |
image_dst_dir=f'{dst_dir}/{split}/' | |
os.makedirs(image_dst_dir, exist_ok=True) | |
dst_metadata=f'{image_dst_dir}/{metadata}' | |
with open(dst_metadata, 'w') as f: | |
for image in images: | |
ann_ids = coco.getAnnIds(imgIds=image['id'], catIds=target_id, iscrowd=None) | |
anns = coco.loadAnns(ann_ids) | |
src_image=f'{image_dir}/{image["file_name"]}' | |
shutil.copy(src_image, image_dst_dir) | |
entry={} | |
entry['file_name']=image["file_name"] | |
boxes=[ann['bbox'] for ann in anns] | |
cats=[0]*len(boxes) | |
entry['objects']={ | |
'bbox': boxes, | |
'categories': cats | |
} | |
f.write(f'{json.dumps(entry)}\n') | |
print(f'Done processing the "{split}" split!') | |
if __name__ == "__main__": | |
for split in splits: | |
process_split(coco_dataset, year, split, dst_dir, metadata) | |