| """Prepare every official gRefCOCO evaluation expression, without subsampling.""" |
| from pathlib import Path |
| import json, hashlib, collections, concurrent.futures, urllib.request, time, os |
| import numpy as np |
| from PIL import Image |
| from pycocotools import mask as cm |
| ROOT=Path(__file__).resolve().parents[1] |
| from project_paths import legacy_root;OLD=legacy_root(ROOT) |
|
|
| def main(): |
| refs=json.loads((OLD/'assets/grefcoco/grefs(unc).json').read_text()) |
| coco=json.loads((OLD/'assets/grefcoco/instances.json').read_text()) |
| ims={x['id']:x for x in coco['images']}; anns={x['id']:x for x in coco['annotations']} |
| chosen=[r for r in refs if r['split'] in ('val','testA','testB')] |
| idir=ROOT/'data/natural/images';mdir=ROOT/'data/natural/masks' |
| idir.mkdir(parents=True,exist_ok=True);mdir.mkdir(parents=True,exist_ok=True) |
| image_ids=sorted({r['image_id'] for r in chosen}) |
| def fetch(i): |
| name=ims[i]['file_name']; out=idir/name |
| if out.exists():return i,'cached' |
| candidates=[OLD/'data/natural/images'/name,OLD/'data/natural/images'/f'{i:012d}.jpg'] |
| for p in candidates: |
| if p.exists():out.symlink_to(p);return i,'reused' |
| url='https://s3.amazonaws.com/images.cocodataset.org/train2014/'+name |
| for attempt in range(4): |
| try: |
| with urllib.request.urlopen(url,timeout=90) as response:blob=response.read() |
| tmp=out.with_suffix('.partial');tmp.write_bytes(blob) |
| with Image.open(tmp) as image:image.verify() |
| tmp.replace(out);return i,'downloaded' |
| except Exception: |
| if attempt==3:raise |
| time.sleep(2**attempt) |
| counts=collections.Counter() |
| with concurrent.futures.ThreadPoolExecutor(max_workers=16) as pool: |
| for k,(iid,state) in enumerate(pool.map(fetch,image_ids)): |
| counts[state]+=1 |
| if k%100==0:print('IMAGES',k,len(image_ids),dict(counts),flush=True) |
| rows=[]; strata=collections.Counter() |
| for r in chosen: |
| im=ims[r['image_id']];h,w=im['height'],im['width']; gt=np.zeros((h,w),bool) |
| aids=[] if r['no_target'] else r['ann_id'] |
| if not isinstance(aids,list):aids=[aids] |
| for aid in aids: |
| seg=anns[aid]['segmentation'] |
| if isinstance(seg,list):z=cm.decode(cm.frPyObjects(seg,h,w)) |
| elif isinstance(seg['counts'],list):z=cm.decode(cm.frPyObjects(seg,h,w)) |
| else:z=cm.decode(seg) |
| gt|=z.any(axis=2) if z.ndim==3 else z.astype(bool) |
| assert bool(gt.any())==bool(aids),(r['ref_id'],aids) |
| gp=mdir/f"ref_{r['ref_id']}.png";Image.fromarray(gt.astype('uint8')*255).save(gp) |
| for sentence in r['sentences']: |
| row=dict(id=f"gref_{r['ref_id']}_{sentence['sent_id']}",scene_id=f"coco_{r['image_id']}",image_id=r['image_id'],ref_id=r['ref_id'],sent_id=sentence['sent_id'],domain='natural_full',split=r['split'],mode='zero' if not aids else 'one' if len(aids)==1 else 'multi',target_count=len(aids),query=sentence['raw'],image_path=str((idir/im['file_name']).relative_to(ROOT)),gt_path=str(gp.relative_to(ROOT)),seed=0,corruption='clean',pair_id=None,endpoint=None,template='official') |
| rows.append(row);strata[(r['split'],row['mode'])]+=1 |
| assert len(rows)==49492 and len({r['id'] for r in rows})==len(rows) |
| mp=ROOT/'data/natural_full.jsonl';mp.write_text(''.join(json.dumps(r)+'\n' for r in rows)) |
| old_rows=[json.loads(s) for s in (OLD/'data/manifest.jsonl').read_text().splitlines()] |
| train_ids={int(r['scene_id'].split('_')[-1]) for r in old_rows if r['domain']=='natural' and r['split'] in ('fit','cal')} |
| overlap=sorted(train_ids&set(image_ids)) |
| meta=dict(expressions=len(rows),references=len(chosen),images=len(image_ids),image_fetch=dict(counts),strata={f'{k[0]}/{k[1]}':v for k,v in strata.items()},manifest_sha256=hashlib.sha256(mp.read_bytes()).hexdigest(),old_calibration_image_overlap=overlap,source='FudanCVL/gRefCOCO; official repository-linked release',source_sha256={p.name:hashlib.sha256(p.read_bytes()).hexdigest() for p in [OLD/'assets/grefcoco/grefs(unc).json',OLD/'assets/grefcoco/instances.json']},slurm_job_id=os.getenv('SLURM_JOB_ID')) |
| (ROOT/'protocol/natural_full_manifest.json').write_text(json.dumps(meta,indent=2));print(json.dumps(meta,indent=2),flush=True) |
| if __name__=='__main__':main() |
|
|
