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Download tools/validate_character_release.py from laion/Vivarium-Greenscreen-Characters-FLUX-9B: direct link, hf CLI and curl.
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- Download file 6.65 kB
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https://huggingface.co/datasets/laion/Vivarium-Greenscreen-Characters-FLUX-9B/resolve/61743ad28b6d1bf91f61884d9680c80ed4af11d3/tools/validate_character_release.py
- Command line
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hf download hf://datasets/laion/Vivarium-Greenscreen-Characters-FLUX-9B@61743ad28b6d1bf91f61884d9680c80ed4af11d3/tools/validate_character_release.py
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curl -L -o validate_character_release.py https://huggingface.co/datasets/laion/Vivarium-Greenscreen-Characters-FLUX-9B/resolve/61743ad28b6d1bf91f61884d9680c80ed4af11d3/tools/validate_character_release.py
6.65 kB
| """Full PNG decode, planned distribution and neutral-reference linkage checks.""" | |
| import argparse | |
| from collections import Counter | |
| import hashlib | |
| import io | |
| import json | |
| import tarfile | |
| from PIL import Image | |
| from character_production import STATE,BUFFER,connect | |
| from background_production import sha,dump,utc,BASE_REV,LORA_REV | |
| from character_pilot import LORA_SHA | |
| def validate(complete=False,extension=False): | |
| global STATE,BUFFER,connect | |
| if extension: | |
| from character_extension import STATE,BUFFER,connect | |
| con=connect();persons={p['personality_id']:p for p in json.loads((STATE/'person-plan.json').read_text())} | |
| plan={e['id']:(p,e) for p in persons.values() for e in p['expressions']} | |
| shards=list(con.execute('SELECT * FROM shards ORDER BY name'));seen=set();neutral_hash={};references=[];groups={};index=[] | |
| for shard in shards: | |
| path=BUFFER/shard['name'];assert path.is_file(),f'Restore verified shard before decoding: {path}' | |
| assert path.stat().st_size==shard['bytes'] and sha(path)==shard['sha256'] | |
| shard_types=set() | |
| with tarfile.open(path,'r:') as tar: | |
| members=tar.getmembers();assert len(members)==shard['count']*3 and len({m.name for m in members})==len(members) | |
| for i in range(0,len(members),3): | |
| png,j,t=members[i:i+3];ident=png.name.removesuffix('.png') | |
| assert [png.name,j.name,t.name]==[ident+'.png',ident+'.json',ident+'.txt'] | |
| assert ident in plan and ident not in seen | |
| person,expression=plan[ident];meta=json.loads(tar.extractfile(j).read());data=tar.extractfile(png).read() | |
| shard_types.add(person.get('record_type','human')) | |
| assert meta['id']==ident and meta['prompt']==tar.extractfile(t).read().decode() | |
| for key,value in person.items(): | |
| if key not in ['expressions','seed']:assert meta[key]==value,(ident,key) | |
| for key,value in expression.items():assert meta[key]==value,(ident,key) | |
| digest=hashlib.sha256(data).hexdigest();assert meta['image_sha256']==digest | |
| if extension: | |
| from teen_generation_safety import approved_metadata | |
| assert approved_metadata(meta),(ident,'under20 screening') | |
| with Image.open(io.BytesIO(data)) as im:assert im.format=='PNG' and im.mode=='RGB' and im.size==(832,1248);im.verify() | |
| with Image.open(io.BytesIO(data)) as im:im.load() | |
| inf=meta['inference'];assert inf['revision']==BASE_REV and inf['lora_sha256']==LORA_SHA | |
| assert inf['model']=='black-forest-labs/FLUX.2-klein-base-9B' and inf['lora_revision']==LORA_REV | |
| assert (inf['width'],inf['height'])==(832,1248) and inf['lora_rank']==64 and inf['lora_alpha']==64 | |
| assert inf['steps']==50 and inf['guidance_scale']==4. and inf['lora_scale']==float(person.get('lora_scale',1.0)) | |
| assert inf['quantization'] is False and inf['distillation'] is False and inf['dtype']=='bfloat16' | |
| assert inf['seed']==meta['seed']==expression['seed'] | |
| if person.get('seed_strategy')!='safety-per-emotion-attempt':assert meta['seed']==person['seed'] | |
| if expression['emotion']=='neutral': | |
| assert not meta['reference_image_sha256'] and not meta['reference_id'];neutral_hash[person['personality_id']]=digest | |
| else: | |
| assert meta['reference_id']==person['personality_id']+'-neutral' | |
| assert meta['reference_resize']==dict(width=416,height=624,resample='PIL BICUBIC') | |
| references.append((person['personality_id'],meta['reference_image_sha256'])) | |
| assert meta['storage']['shard']==shard['name'] | |
| groups.setdefault(person['personality_id'],set()).add(expression['emotion']);seen.add(ident) | |
| index.append(dict(id=ident,personality_id=person['personality_id'],emotion=expression['emotion'],shard=shard['name'], | |
| repo_path=('extension-data/' if extension else 'data/')+shard['name'], | |
| image_offset=png.offset_data,image_bytes=png.size,image_sha256=digest,seed=expression['seed'])) | |
| assert len(shard_types)==1,'Each shard must contain only one record family' | |
| for person,digest in references:assert neutral_hash[person]==digest,(person,'neutral reference SHA mismatch') | |
| assert all(g=={e['emotion'] for e in persons[p]['expressions']} for p,g in groups.items()),'Closed shards must contain complete planned expression groups' | |
| if complete: | |
| assert seen==set(plan) and len(seen)==(2500 if extension else 5000) and len(groups)==(340 if extension else 500) | |
| assert all(s['status']=='uploaded' for s in shards) | |
| allocation=json.loads((STATE/'planning/allocation.json').read_text()) | |
| humans=[p for p in groups if persons[p].get('record_type','human')=='human'] | |
| assert dict(Counter(persons[p]['gender'] for p in humans))==allocation['human_gender_counts' if extension else 'gender_counts'] | |
| assert dict(Counter(persons[p]['ethnicity'] for p in humans))==allocation['human_ethnicity_counts' if extension else 'ethnicity_counts'] | |
| assert dict(Counter(persons[p]['age_group']+'/'+persons[p]['gender'] for p in humans))==allocation['by_age_and_gender'] | |
| if extension: | |
| assert dict(Counter(persons[p]['special_class'] for p in groups if p not in humans))==allocation['special_class_counts'] | |
| result=dict(status='passed',scope='complete' if complete else 'closed-shard snapshot',utc=utc(),images_verified=len(seen), | |
| persons_verified=len(groups),shards_verified=len(shards),bytes_verified=sum(s['bytes'] for s in shards), | |
| checks=['TAR SHA256 and byte size','three adjacent unique members per sample','PNG CRC and full decode','832x1248 RGB', | |
| 'unique expected IDs','every person and expression field matches plan','prompt/seed consistency','PNG SHA256', | |
| 'exact neutral reference linkage and416x624 resize','complete planned expressions per closed identity','50-step CFG4 BF16 pinned model/LoRA', | |
| 'no quantization or distillation']+(['complete age/gender/ethnicity prompt distribution'] if complete else [])) | |
| dump(STATE/'integrity-validation.json',result);dump(STATE/'sample-index.json',index);print(json.dumps(result,indent=2)) | |
| if __name__=='__main__': | |
| p=argparse.ArgumentParser();p.add_argument('--complete',action='store_true');p.add_argument('--extension',action='store_true');a=p.parse_args();validate(a.complete,a.extension) | |