File size: 3,310 Bytes
60c4331 23739c9 13eb21e 23739c9 8b10b57 23739c9 60c4331 8b10b57 60c4331 8b10b57 60c4331 23739c9 60c4331 8b10b57 60c4331 8739fa2 60c4331 a74a30b 8b10b57 a74a30b 8b10b57 60c4331 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 | import os, subprocess, zipfile
from pathlib import Path
from huggingface_hub import hf_hub_download, snapshot_download
def writable_data_root():
preferred = Path(os.environ.get('DATA_ROOT', '/data/amodal'))
for candidate in (preferred, Path('/tmp/amodal')):
try:
candidate.mkdir(parents=True, exist_ok=True)
test = candidate / '.write_test'
test.write_text('ok')
test.unlink(missing_ok=True)
return candidate
except Exception:
continue
raise RuntimeError('No writable data directory found; tried /data/amodal and /tmp/amodal')
data_root = writable_data_root()
cache_root = data_root.parent/'hf_cache'
os.environ.setdefault('HF_HOME', str(cache_root))
os.environ.setdefault('HUGGINGFACE_HUB_CACHE', str(cache_root/'hub'))
os.environ.setdefault('TRANSFORMERS_CACHE', str(cache_root/'transformers'))
os.environ.setdefault('HOME', str(data_root.parent))
os.environ.setdefault('XDG_CACHE_HOME', str(data_root.parent/'.cache'))
ckpt_root = data_root/'checkpoints'
ckpt_root.mkdir(parents=True, exist_ok=True)
cache_root.mkdir(parents=True, exist_ok=True)
(data_root/'LISAoutput').mkdir(parents=True, exist_ok=True)
def run(cmd, cwd=None, check=True):
print('+', ' '.join(cmd))
return subprocess.run(cmd, cwd=cwd, check=check)
# Public direct downloads
files = [
('https://dl.fbaipublicfiles.com/segment_anything/sam_vit_h_4b8939.pth', ckpt_root/'sam_vit_h_4b8939.pth'),
('https://github.com/IDEA-Research/GroundingDINO/releases/download/v0.1.0-alpha/groundingdino_swint_ogc.pth', ckpt_root/'groundingdino_swint_ogc.pth'),
]
for url, dst in files:
if not dst.exists():
run(['wget', '-O', str(dst), url])
# HF-hosted RAM++ checkpoint
ram_dst = ckpt_root/'ram_plus_swin_large_14m.pth'
if not ram_dst.exists():
src = hf_hub_download('xinyu1205/recognize-anything-plus-model', 'ram_plus_swin_large_14m.pth')
os.symlink(src, ram_dst)
# LISA model: use snapshot cache; app.py can load repo_id directly, but snapshot warms cache.
# Requires HF_TOKEN if the repo/license requires it.
snapshot_download('xinlai/LISA-13B-llama2-v1', local_dir=str(cache_root/'LISA-13B-llama2-v1'), local_dir_use_symlinks=False)
# InstaOrder checkpoint zip is on Google Drive and can be throttled. Try gdown.
insta_ckpt = ckpt_root/'InstaOrder_InstaOrderNet_od.pth.tar'
if not insta_ckpt.exists():
zip_path = Path('/tmp/InstaOrder_ckpt.zip')
if not zip_path.exists():
# Use the raw file id; older gdown versions do not support --fuzzy.
run(['gdown', '1_GEmCmofLSkJZnidfp4vsQb2Nqq5aqBU', '-O', str(zip_path)], check=False)
if zip_path.exists():
try:
with zipfile.ZipFile(zip_path) as z:
z.extractall(ckpt_root)
except zipfile.BadZipFile:
print('WARNING: downloaded InstaOrder checkpoint is not a valid zip; removing it so a later run can retry.')
zip_path.unlink(missing_ok=True)
if not insta_ckpt.exists():
nested = ckpt_root/'InstaOrder_ckpt'/'InstaOrder_InstaOrderNet_od.pth.tar'
if nested.exists():
nested.replace(insta_ckpt)
if not insta_ckpt.exists():
print('WARNING: InstaOrder checkpoint missing. Upload InstaOrder_ckpt.zip manually or mirror it to HF.')
|