#!/usr/bin/env python """Recompute split.json from metadata.jsonl (no re-render needed), then build pairs. Rejection rule (same as render_full.py): object rejected if ANY of its 24 views has alpha coverage < 0.08 or bbox_span > 0.95. Heldout: 40 objects, stratified by category, drawn from NON-rejected objects only. Seed 20260923. Render filenames follow render_full.py: az{000..315}_el{low|eye|high}.png (no separator: az315_eleye.png, az045_ellow.png, ...). Pair paths are validated against the metadata.jsonl 'file' fields, so any mismatch fails loudly here. Uploads split.json + pairs_train.jsonl + pairs_eval.jsonl to ysharma/gso-orbit-rgba. """ import json, os, random from collections import Counter, defaultdict from huggingface_hub import HfApi REPO = 'ysharma/gso-orbit-rgba' ELEV_NAME = {'low': 'low angle', 'eye': 'eye level', 'high': 'elevated'} AZS = list(range(0, 360, 45)) SEED = 20260923 HELDOUT_N = 40 def render_file(object_id, az, elev_key): return f'renders/{object_id}/az{az:03d}_el{elev_key}.png' def instruction(move_deg, side, elev_key): if move_deg == 0: return f" keep the camera angle, {ELEV_NAME[elev_key]}" if move_deg == 180: return f" rotate the camera 180 degrees, {ELEV_NAME[elev_key]}" return (f" rotate the camera {move_deg} degrees to the {side}, " f"{ELEV_NAME[elev_key]}") def plain_instruction(move_deg, side, elev_key): e = {'low': 'low-angle', 'eye': 'eye-level', 'high': 'raised'}[elev_key] if move_deg == 0: return f"Show the same object from a {e} viewpoint." if move_deg == 180: return f"Show the same object with the camera rotated 180 degrees, from a {e} viewpoint." return (f"Show the same object with the camera rotated {move_deg} degrees " f"to the {side}, from a {e} viewpoint.") def make_pair(object_id, move_deg, side, elev_key, src_az, idx): sign = -1 if side == 'right' else 1 tgt_az = src_az if move_deg == 0 else ((src_az + 180) % 360 if move_deg == 180 else (src_az + sign * move_deg) % 360) return { 'object_id': object_id, 'instruction': instruction(move_deg, side, elev_key), 'instruction_plain': plain_instruction(move_deg, side, elev_key), 'move_deg': move_deg, 'side': side, 'elevation': elev_key, 'src_azimuth': src_az, 'tgt_azimuth': tgt_az, 'source_file': render_file(object_id, src_az, 'eye'), 'target_file': render_file(object_id, tgt_az, elev_key), 'pair_id': f'{object_id}_{idx}', } def main(): api = HfApi(token=os.environ.get('HF_TOKEN')) import urllib.request urllib.request.urlretrieve( 'https://huggingface.co/datasets/ysharma/gso-orbit-rgba/resolve/main/metadata.jsonl', 'metadata.jsonl') print('metadata.jsonl downloaded', flush=True) rows = [json.loads(l) for l in open('metadata.jsonl')] on_disk = {r['file'] for r in rows} by_obj = {} cats = defaultdict(set) for r in rows: by_obj.setdefault(r['object_id'], []).append(r) cats[r['category']].add(r['object_id']) rejected = {oid for oid, vr in by_obj.items() if any(v['coverage'] < 0.08 or v['bbox_span'] > 0.95 for v in vr)} n_total = len(by_obj) print(f'objects: {n_total} | rejected: {len(rejected)} | usable: {n_total - len(rejected)}', flush=True) # ---- split ---- rng = random.Random(SEED) pool_by_cat = {c: sorted(ids - rejected) for c, ids in cats.items()} pool_by_cat = {c: p for c, p in pool_by_cat.items() if p} total_pool = sum(len(p) for p in pool_by_cat.values()) heldout = [] for c in sorted(pool_by_cat): pool = pool_by_cat[c][:] rng.shuffle(pool) n = max(1, round(HELDOUT_N * len(pool) / total_pool)) heldout.extend(pool[:n]) rng.shuffle(heldout) heldout = heldout[:HELDOUT_N] hs = set(heldout) train = sorted(o for c in pool_by_cat for o in pool_by_cat[c] if o not in hs) print(f'split: {len(heldout)} heldout, {len(train)} train', flush=True) split = {'heldout_40': heldout, 'train_objects': train, 'rejected_objects': sorted(rejected), 'failed_objects': [], 'seed': SEED, 'n_renders': len(rows), 'instructions_version': 'orbit-relative-v1'} # ---- pairs ---- instr_cycle = [] for d in (45, 90, 135): for s in ('left', 'right'): for e in ('low', 'eye', 'high'): instr_cycle.append((d, s, e)) instr_cycle.append((180, '', 'low')) instr_cycle.append((180, '', 'eye')) instr_cycle.append((180, '', 'high')) instr_cycle.append((0, '', 'low')) instr_cycle.append((0, '', 'high')) assert len(instr_cycle) == 23 rng.shuffle(instr_cycle) qi = 0 train_pairs = [] for obj in train: src_az = rng.choice(AZS) for k in range(4): d, s, e = instr_cycle[qi % 23]; qi += 1 p = make_pair(obj, d, s, e, src_az, k) assert p['source_file'] in on_disk, f'missing {p["source_file"]}' assert p['target_file'] in on_disk, f'missing {p["target_file"]}' train_pairs.append(p) cbal = Counter(p['instruction'] for p in train_pairs) print(f'train pairs: {len(train_pairs)} from {len(train)} objects | ' f'instruction balance min/max: {min(cbal.values())}/{max(cbal.values())}', flush=True) eval_pairs = [] for obj in heldout: src_az = rng.choice(AZS) for k, d in enumerate((45, 90, 180, 0)): s = rng.choice(['left', 'right']) if d in (45, 90) else '' e = rng.choice(['low', 'eye', 'high']) if d else rng.choice(['low', 'high']) p = make_pair(obj, d, s, e, src_az, k) assert p['source_file'] in on_disk, f'missing {p["source_file"]}' assert p['target_file'] in on_disk, f'missing {p["target_file"]}' eval_pairs.append(p) print(f'eval pairs: {len(eval_pairs)} from {len(heldout)} heldout objects', flush=True) with open('split.json', 'w') as f: json.dump(split, f, indent=2) api.upload_file(repo_id=REPO, repo_type='dataset', path_in_repo='split.json', path_or_fileobj='split.json') print('uploaded split.json', flush=True) for name, pairs in (('pairs_train.jsonl', train_pairs), ('pairs_eval.jsonl', eval_pairs)): with open(name, 'w') as f: for p in pairs: f.write(json.dumps(p) + '\n') api.upload_file(repo_id=REPO, repo_type='dataset', path_in_repo=name, path_or_fileobj=name) print(f'uploaded {name}', flush=True) if __name__ == '__main__': main()