| |
| import argparse |
| import hashlib |
| import json |
| from pathlib import Path |
|
|
| import numpy as np |
|
|
|
|
| REQUIRED_KEYS = ["pointcloud", "mask", "VX", "VY", "PS", "PG"] |
| REQUIRED_FILES = [ |
| "sim.npz", |
| "triangles.npy", |
| "constrained_kmeans_10.npy", |
| "constrained_kmeans_20.npy", |
| "constrained_kmeans_30.npy", |
| "constrained_kmeans_40.npy", |
| ] |
|
|
|
|
| def fail(message): |
| raise SystemExit(f"[ERROR] {message}") |
|
|
|
|
| def sha256_file(path): |
| h = hashlib.sha256() |
| with path.open("rb") as f: |
| for chunk in iter(lambda: f.read(1024 * 1024), b""): |
| h.update(chunk) |
| return h.hexdigest() |
|
|
|
|
| def iter_inventory(path): |
| with path.open("r", encoding="utf-8") as f: |
| for line in f: |
| if line.strip(): |
| yield json.loads(line) |
|
|
|
|
| def inspect_sample(sample_dir): |
| for name in REQUIRED_FILES: |
| if not (sample_dir / name).exists(): |
| fail(f"missing required file: {sample_dir / name}") |
|
|
| with np.load(sample_dir / "sim.npz", mmap_mode="r") as data: |
| missing = [key for key in REQUIRED_KEYS if key not in data.files] |
| if missing: |
| fail(f"{sample_dir / 'sim.npz'} missing keys: {missing}") |
| pointcloud = data["pointcloud"] |
| mask = data["mask"] |
| if pointcloud.ndim != 3 or pointcloud.shape[-1] != 2: |
| fail(f"unexpected pointcloud shape: {pointcloud.shape}") |
| if pointcloud.dtype != np.float32: |
| fail(f"unexpected pointcloud dtype: {pointcloud.dtype}") |
| if mask.shape != pointcloud.shape[:2]: |
| fail(f"mask shape {mask.shape} does not match pointcloud {pointcloud.shape[:2]}") |
| for key in ["VX", "VY", "PS", "PG"]: |
| arr = data[key] |
| if arr.shape != pointcloud.shape[:2]: |
| fail(f"{key} shape {arr.shape} does not match pointcloud {pointcloud.shape[:2]}") |
| if arr.dtype != np.float32: |
| fail(f"{key} dtype should be float32, got {arr.dtype}") |
|
|
| triangles = np.load(sample_dir / "triangles.npy", mmap_mode="r") |
| if triangles.ndim != 3 or triangles.shape[0] != pointcloud.shape[0] or triangles.shape[-1] != 3: |
| fail(f"unexpected triangles shape: {triangles.shape}") |
|
|
| for n_cluster in [10, 20, 30, 40]: |
| clusters = np.load(sample_dir / f"constrained_kmeans_{n_cluster}.npy", mmap_mode="r") |
| if clusters.ndim != 3 or clusters.shape[0] != pointcloud.shape[0] or clusters.shape[-1] != n_cluster: |
| fail(f"unexpected constrained_kmeans_{n_cluster}.npy shape: {clusters.shape}") |
|
|
|
|
| def validate_inventory(dataset_root, inventory_path, full_hash): |
| checked = 0 |
| for item in iter_inventory(inventory_path): |
| rel = item["path"] |
| path = dataset_root / rel |
| if not path.exists(): |
| fail(f"inventory path missing: {path}") |
| size = path.stat().st_size |
| if size != item["size"]: |
| fail(f"size mismatch for {rel}: expected {item['size']}, got {size}") |
| if full_hash: |
| digest = sha256_file(path) |
| if digest != item["sha256"]: |
| fail(f"sha256 mismatch for {rel}: expected {item['sha256']}, got {digest}") |
| checked += 1 |
| return checked |
|
|
|
|
| def main(): |
| parser = argparse.ArgumentParser() |
| parser.add_argument("--data-root", default="data/Eagle_dataset") |
| parser.add_argument("--sample-limit", type=int, default=3) |
| parser.add_argument("--full-hash", action="store_true") |
| args = parser.parse_args() |
|
|
| repo_root = Path.cwd() |
| dataset_root = repo_root / args.data_root |
| inventory_path = repo_root / "files_sha256.jsonl" |
| summary_path = repo_root / "data_integrity_summary.json" |
|
|
| if not dataset_root.exists(): |
| fail(f"dataset root not found: {dataset_root}") |
| if not inventory_path.exists(): |
| fail(f"inventory not found: {inventory_path}") |
| if not summary_path.exists(): |
| fail(f"summary not found: {summary_path}") |
|
|
| for geom in ["Cre", "Spl", "Tri"]: |
| geom_dir = dataset_root / geom |
| if not geom_dir.exists(): |
| fail(f"missing geometry directory: {geom_dir}") |
|
|
| sample_dirs = sorted(p for p in dataset_root.glob("*/*/*") if p.is_dir()) |
| if len(sample_dirs) != 1200: |
| fail(f"expected 1200 sample directories, got {len(sample_dirs)}") |
| for sample_dir in sample_dirs[: args.sample_limit]: |
| inspect_sample(sample_dir) |
|
|
| checked = validate_inventory(dataset_root, inventory_path, args.full_hash) |
| if checked != 7200: |
| fail(f"expected 7200 inventory files, got {checked}") |
|
|
| if args.full_hash: |
| print(f"[OK] checksum manifest verified in size+sha256 mode: {checked} files") |
| else: |
| print(f"[OK] checksum manifest verified in size mode: {checked} files") |
| print(f"[OK] dataset validation completed: {len(sample_dirs)} samples, sampled {args.sample_limit}") |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
