"""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.")