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bd4a96a | 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 | #!/usr/bin/env python
"""Download ROI flow data from HuggingFace.
Downloads the probe embedding, ROI vectors, ROI centers, and OOS manifold
points needed for ROI flow mode.
Usage:
python scripts/download_roi_flow_data.py
"""
import os
import sys
from pathlib import Path
PROJECT_ROOT = Path(__file__).resolve().parent.parent
DATA_DIR = PROJECT_ROOT / "data" / "roi_flow"
def _fix_ssl():
try:
import certifi
os.environ["SSL_CERT_FILE"] = certifi.where()
os.environ["REQUESTS_CA_BUNDLE"] = certifi.where()
except ImportError:
pass
def main():
_fix_ssl()
try:
from huggingface_hub import hf_hub_download
except ImportError:
print("huggingface_hub not installed. Install with:")
print(" pip install huggingface_hub")
sys.exit(1)
REPO_ID = "Pixedar/mindVisualizer-roi-flow-data"
FILES = [
# Probe data
"probe_embed.npy",
"probe_roi.npy",
"probe_roi_centers.npy",
# Manifold OOS points
"universal_soul_2sdm_rest_points.ply",
# MDN flow field (manifold space, not brain space)
"mdn_training_all_points.npy",
"mdn_universal_raw_grid64_meta.json",
"mdn_universal_all_grid64_mean_xyz3.bin",
"mdn_universal_all_grid64_mu1_xyz3.bin",
"mdn_universal_all_grid64_mu2_xyz3.bin",
"mdn_universal_all_grid64_pi.bin",
"mdn_universal_all_grid64_entropy.bin",
]
DATA_DIR.mkdir(parents=True, exist_ok=True)
for fname in FILES:
dest = DATA_DIR / fname
if dest.exists():
print(f" [skip] {fname} (already exists)")
continue
print(f" Downloading {fname}...")
try:
downloaded = hf_hub_download(
repo_id=REPO_ID,
filename=fname,
repo_type="dataset",
local_dir=str(DATA_DIR),
)
print(f" [ok] {fname}")
except Exception as e:
print(f" [error] {fname}: {e}")
print(f"\nDone! Files saved to: {DATA_DIR}")
print("\nYou can now run ROI flow mode:")
print(" python examples/roi_flow_mode.py")
if __name__ == "__main__":
main()
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