Datasets:
Download scripts/verify_shards.py from mcbuehler/cafca-dataset: direct link, hf CLI and curl.
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- Download file 6.38 kB
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https://huggingface.co/datasets/mcbuehler/cafca-dataset/resolve/main/scripts/verify_shards.py
- Command line
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hf download hf://datasets/mcbuehler/cafca-dataset/scripts/verify_shards.py
-
curl -L -o verify_shards.py https://huggingface.co/datasets/mcbuehler/cafca-dataset/resolve/main/scripts/verify_shards.py
6.38 kB
| """Local verification of the converted WebDataset shards (Step 5 of the plan): | |
| 1. Decode a sample of each tier through both `webdataset` and HF `datasets` loaders. | |
| 2. Build the FLAME-params in-memory dict and confirm it joins to every view-tier scene via | |
| ENV = EXPR_ENV[5:] (not a prefix match). | |
| 3. Confirm scene-mesh key is a true prefix of the corresponding view-tier keys. | |
| 4. Test itertools.groupby scene (30-view) and subject assembly, single-process/no-shuffle. | |
| """ | |
| import glob | |
| import io | |
| import itertools | |
| import sys | |
| import numpy as np | |
| import trimesh | |
| import webdataset as wds | |
| from datasets import load_dataset | |
| SHARD_DIR = sys.argv[1] if len(sys.argv) > 1 else "./data/shards_single_subject" | |
| def view_key_parts(key): | |
| subject, expr_env, cam = key.split("/") | |
| expr, env = expr_env.split("_") | |
| return subject, expr, env, cam | |
| def check_decode_both_loaders(): | |
| print("=" * 60) | |
| print("1. Decode check (webdataset lib + HF datasets) per tier") | |
| print("=" * 60) | |
| view_shards = sorted(glob.glob(f"{SHARD_DIR}/views/*.tar")) | |
| mesh_shards = sorted(glob.glob(f"{SHARD_DIR}/scene_mesh/*.tar")) | |
| flame_shards = sorted(glob.glob(f"{SHARD_DIR}/flame_params/*.tar")) | |
| print(f"\n--- view tier: webdataset lib, first 3 samples ---") | |
| ds = wds.WebDataset(view_shards, shardshuffle=False).decode() | |
| for i, s in enumerate(ds): | |
| rgb = np.array(s["rgb.png"]) if hasattr(s["rgb.png"], "shape") else None | |
| print(f" key={s['__key__']} cam.json keys={list(s['cam.json'].keys())[:3]} " | |
| f"landmark keys={list(s['landmark.npz'].keys())}") | |
| if i >= 2: | |
| break | |
| print(f"\n--- view tier: HF datasets, first sample features ---") | |
| hf_ds = load_dataset("webdataset", data_files=view_shards, split="train") | |
| print(" features:", {k: str(v)[:60] for k, v in hf_ds.features.items()}) | |
| sample = hf_ds[0] | |
| print(f" seg.png mode={sample['seg.png'].mode} size={sample['seg.png'].size}") | |
| print(f" rgb.png mode={sample['rgb.png'].mode} size={sample['rgb.png'].size}") | |
| assert sample["seg.png"].mode == "I;16", "segmentation did not decode as 16-bit!" | |
| print(f"\n--- scene-mesh tier: webdataset lib ---") | |
| ds = wds.WebDataset(mesh_shards, shardshuffle=False).decode() | |
| for i, s in enumerate(ds): | |
| mesh = trimesh.load(io.BytesIO(s["mesh.obj"] if isinstance(s["mesh.obj"], bytes) else s["mesh.obj"]), file_type="obj") | |
| print(f" key={s['__key__']} mesh vertices={mesh.vertices.shape}") | |
| if i >= 1: | |
| break | |
| print(f"\n--- flame-params tier: HF datasets ---") | |
| hf_flame = load_dataset("webdataset", data_files=flame_shards, split="train") | |
| print(" count:", len(hf_flame)) | |
| for row in hf_flame: | |
| shape = np.array(row["flame.npz"]["expr"]).shape | |
| print(f" key={row['__key__']} expr shape={shape}") | |
| return view_shards, mesh_shards, flame_shards | |
| def check_flame_join(view_shards, flame_shards): | |
| print("\n" + "=" * 60) | |
| print("2. FLAME-params join via ENV = EXPR_ENV[5:] (dict lookup, not prefix)") | |
| print("=" * 60) | |
| flame_ds = wds.WebDataset(flame_shards, shardshuffle=False).decode() | |
| flame_by_key = {s["__key__"]: s["flame.npz"] for s in flame_ds} | |
| print(f" loaded {len(flame_by_key)} flame-params entries: {list(flame_by_key.keys())}") | |
| view_ds = wds.WebDataset(view_shards, shardshuffle=False) | |
| scenes_seen = set() | |
| missing = [] | |
| for s in view_ds: | |
| subject, expr, env, cam = view_key_parts(s["__key__"]) | |
| expr_env = f"{expr}_{env}" | |
| scene_key = f"{subject}/{expr_env}" | |
| if scene_key in scenes_seen: | |
| continue | |
| scenes_seen.add(scene_key) | |
| flame_key = f"{subject}/{env}" | |
| if flame_key not in flame_by_key: | |
| missing.append((scene_key, flame_key)) | |
| print(f" checked {len(scenes_seen)} distinct scenes") | |
| if missing: | |
| print(f" MISSING flame entries for: {missing}") | |
| else: | |
| print(" OK: every scene's FLAME-params entry found via env slice") | |
| def check_scene_mesh_prefix(view_shards, mesh_shards): | |
| print("\n" + "=" * 60) | |
| print("3. Scene-mesh key is a true prefix of view-tier keys") | |
| print("=" * 60) | |
| mesh_keys = {s["__key__"] for s in wds.WebDataset(mesh_shards, shardshuffle=False)} | |
| view_ds = wds.WebDataset(view_shards, shardshuffle=False) | |
| bad = [] | |
| checked = 0 | |
| for s in view_ds: | |
| subject, expr, env, cam = view_key_parts(s["__key__"]) | |
| scene_key = f"{subject}/{expr}_{env}" | |
| checked += 1 | |
| if not s["__key__"].startswith(scene_key + "/"): | |
| bad.append(s["__key__"]) | |
| if scene_key not in mesh_keys: | |
| bad.append((s["__key__"], "no matching mesh key")) | |
| print(f" checked {checked} view samples against {len(mesh_keys)} mesh keys") | |
| print(" OK: prefix relationship holds" if not bad else f" FAILURES: {bad[:10]}") | |
| def check_groupby(view_shards): | |
| print("\n" + "=" * 60) | |
| print("4. itertools.groupby scene (30-view) and subject assembly") | |
| print(" (single-process, no shuffle, sequential read)") | |
| print("=" * 60) | |
| ds = wds.WebDataset(view_shards, shardshuffle=False) | |
| def scene_key(sample): | |
| subject, expr, env, cam = view_key_parts(sample["__key__"]) | |
| return f"{subject}/{expr}_{env}" | |
| def subject_key(sample): | |
| subject, expr, env, cam = view_key_parts(sample["__key__"]) | |
| return subject | |
| scene_sizes = [] | |
| for key, group in itertools.groupby(ds, key=scene_key): | |
| scene_sizes.append((key, len(list(group)))) | |
| print(f" found {len(scene_sizes)} scene groups") | |
| bad_scenes = [(k, n) for k, n in scene_sizes if n != 30] | |
| print(" OK: every scene has exactly 30 views" if not bad_scenes | |
| else f" FAILURES (expected 30 views each): {bad_scenes}") | |
| ds2 = wds.WebDataset(view_shards, shardshuffle=False) | |
| subject_sizes = [] | |
| for key, group in itertools.groupby(ds2, key=subject_key): | |
| subject_sizes.append((key, len(list(group)))) | |
| print(f" found {len(subject_sizes)} subject groups: {[(k, n) for k, n in subject_sizes]}") | |
| if __name__ == "__main__": | |
| view_shards, mesh_shards, flame_shards = check_decode_both_loaders() | |
| check_flame_join(view_shards, flame_shards) | |
| check_scene_mesh_prefix(view_shards, mesh_shards) | |
| check_groupby(view_shards) | |
| print("\nAll checks completed.") | |