Datasets:
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aa991fc 358e603 aa991fc 358e603 aa991fc 358e603 aa991fc 358e603 aa991fc | 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 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 | #!/usr/bin/env python
"""Push the staging tree to the HuggingFace dataset repo.
Two upload paths:
* SMALL files (README, previews/, assets/, scripts/, cameras.json, smplx.npz,
capture.json, preview.jpg) -> `upload_folder`, one atomic commit.
* BIG files (data/<PxCy>/videos/*.mp4, ~2 GiB per capture) -> `upload_large_folder`,
which is chunked, multi-worker and RESUMABLE: it keeps per-file state under
<staging>/.cache/huggingface, so re-running after a network drop skips what is done.
Usage:
python hf_upload.py --staging .../staging --capture P1C1 # meta + that capture
python hf_upload.py --staging .../staging --meta-only # README/previews/scripts
python hf_upload.py --staging .../staging --capture P1C1 --videos-only
"""
from __future__ import annotations
import argparse
import json
import sys
from pathlib import Path
from huggingface_hub import HfApi
REPO_ID = "initialneil/DREAMS-AVATAR"
META_PATTERNS = [
"README.md", "LICENSE",
"previews/*.jsonl", "previews/*.jpg", "assets/**/*.jpg",
"scripts/*.py", "scripts/*.sh",
]
CAPTURE_SMALL = ["data/{cap}/cameras.json", "data/{cap}/smplx.npz",
"data/{cap}/capture.json", "data/{cap}/preview.jpg"]
CAPTURE_BIG = ["data/{cap}/videos/*.mp4"]
def ensure_repo(api: HfApi, repo_id: str, private: bool) -> str:
url = api.create_repo(repo_id=repo_id, repo_type="dataset", private=private,
exist_ok=True)
info = api.repo_info(repo_id=repo_id, repo_type="dataset")
print(f"[repo] {url} private={info.private}", flush=True)
return str(url)
def main() -> int:
ap = argparse.ArgumentParser(description=__doc__,
formatter_class=argparse.RawDescriptionHelpFormatter)
ap.add_argument("--staging", type=Path, required=True)
ap.add_argument("--repo-id", default=REPO_ID)
ap.add_argument("--capture", default=None)
ap.add_argument("--meta-only", action="store_true")
ap.add_argument("--videos-only", action="store_true")
ap.add_argument("--private", action="store_true", help="create as private (default PUBLIC)")
ap.add_argument("--prune-previews", action="store_true",
help="delete repo previews/showcase jpgs that are no longer in staging "
"(needed when frame labels change). Never touches data/ or scripts/.")
ap.add_argument("--workers", type=int, default=4)
a = ap.parse_args()
api = HfApi()
who = api.whoami()["name"]
print(f"[hf] logged in as {who}", flush=True)
ensure_repo(api, a.repo_id, a.private)
if not a.videos_only:
pats = list(META_PATTERNS)
if a.capture:
pats += [p.format(cap=a.capture) for p in CAPTURE_SMALL]
msg = (f"Add {a.capture} metadata + SMPL-X + previews" if a.capture
else "Update dataset card / previews / scripts")
# scoped on purpose: only preview/showcase images may be pruned, so a stale
# frame labelling cannot leave orphan rows in the viewer. data/ is never touched.
dels = ["previews/*.jpg", "assets/showcase/*.jpg"] if a.prune_previews else None
print(f"[upload] small files: {pats}", flush=True)
if dels:
print(f"[upload] pruning stale: {dels}", flush=True)
ci = api.upload_folder(repo_id=a.repo_id, repo_type="dataset",
folder_path=str(a.staging), allow_patterns=pats,
delete_patterns=dels, commit_message=msg)
print(f"[upload] commit {getattr(ci, 'oid', ci)}", flush=True)
if a.capture and not a.meta_only:
pats = [p.format(cap=a.capture) for p in CAPTURE_BIG]
print(f"[upload] LARGE (resumable): {pats}", flush=True)
api.upload_large_folder(repo_id=a.repo_id, repo_type="dataset",
folder_path=str(a.staging), allow_patterns=pats,
num_workers=a.workers, print_report=True,
print_report_every=30)
print("[upload] large folder done", flush=True)
files = api.list_repo_files(repo_id=a.repo_id, repo_type="dataset")
print(json.dumps({"repo": f"https://huggingface.co/datasets/{a.repo_id}",
"n_files": len(files)}))
return 0
if __name__ == "__main__":
sys.exit(main())
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