Update to 2026-09-17 pipeline snapshot; add weights, L20 assets and recording via Git LFS

Source: RGB-D -> Dyn-HaMR -> L20 retargeting -> FoundationPose -> reference repair -> SPIDER, documented in docs/PIPELINE_LATEST.md and docs/SETUP_AND_WEIGHTS.md. Adds FoundationPose and nvdiffrast upstream snapshots, requirements/pipeline_venv.txt and the FoundationPose weight manifest/downloader. Assets (Git LFS): weights/ (WiLoR detector, HandFlow denoiser, UniDepth-L), FoundationPose checkpoints, HaMeR checkpoint, Dyn-HaMR HMP model and BMC constraints, L20 URDF/meshes, the 20260915_171525 D405 recording and the two box CADs. MANO models are not redistributed (third_party/hamer/_DATA/data/mano/README.txt). Environments, caches and run outputs excluded. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-09-17 11:27:46 +08:00
parent 7e4ef6f98b
commit ae28d55f81
761 changed files with 55598 additions and 59 deletions
@@ -0,0 +1,122 @@
+#!/usr/bin/env python3
+"""Quick sanity checks for a local FoundationPose install (no inference)."""
+
+from __future__ import annotations
+
+import argparse
+import os
+import sys
+from pathlib import Path
+
+
+def main() -> int:
+  parser = argparse.ArgumentParser(description=__doc__)
+  parser.add_argument(
+    "--demo-data",
+    action="store_true",
+    help="Also check default paths used by run_demo.py (demo_data/mustard0).",
+  )
+  args = parser.parse_args()
+
+  repo_root = Path(__file__).resolve().parent
+  os.chdir(repo_root)
+  if str(repo_root) not in sys.path:
+    sys.path.insert(0, str(repo_root))
+
+  errors: list[str] = []
+  warnings: list[str] = []
+
+  print(f"Repository: {repo_root}")
+  print(f"Python: {sys.version.split()[0]}")
+
+  # --- PyTorch / CUDA ---
+  try:
+    import torch
+
+    print(f"PyTorch: {torch.__version__}")
+    print(f"CUDA available: {torch.cuda.is_available()}")
+    if torch.cuda.is_available():
+      print(f"CUDA device: {torch.cuda.get_device_name(0)}")
+  except Exception as e:
+    errors.append(f"torch: {e}")
+
+  # --- Core imports (same chain as run_demo / estimater) ---
+  modules = [
+    "pytorch3d",
+    "nvdiffrast.torch",
+    "trimesh",
+    "open3d",
+    "cv2",
+    "warp",
+  ]
+  for mod in modules:
+    try:
+      __import__(mod)
+      print(f"import {mod}: ok")
+    except Exception as e:
+      errors.append(f"import {mod}: {e}")
+
+  # --- Native extension ---
+  build_dir = repo_root / "mycpp" / "build"
+  so_files = list(build_dir.glob("mycpp*.so"))
+  if not so_files:
+    warnings.append(f"No mycpp extension found under {build_dir} (run bash build_all_conda.sh).")
+  else:
+    print(f"mycpp extension: {so_files[0].name}")
+
+  try:
+    sys.path.insert(0, str(build_dir))
+    import mycpp
+
+    print(f"import mycpp: ok ({mycpp})")
+  except Exception as e:
+    errors.append(f"import mycpp: {e}")
+
+  try:
+    import estimater
+
+    print("import estimater: ok")
+  except Exception as e:
+    errors.append(f"import estimater: {e}")
+
+  # --- Weights (hard-coded run names in learning/training/predict_*.py) ---
+  weight_sets = [
+    ("scorer", "2024-01-11-20-02-45"),
+    ("refiner", "2023-10-28-18-33-37"),
+  ]
+  weights_root = repo_root / "weights"
+  for label, stamp in weight_sets:
+    d = weights_root / stamp
+    ckpt = d / "model_best.pth"
+    cfg = d / "config.yml"
+    missing = [p.name for p in (ckpt, cfg) if not p.is_file()]
+    if missing:
+      warnings.append(
+        f"Weights ({label}, {stamp}): missing {', '.join(missing)} — download per readme Data prepare."
+      )
+    else:
+      print(f"Weights ({label}, {stamp}): ok")
+
+  # --- Optional demo bundle ---
+  if args.demo_data:
+    demo_scene = repo_root / "demo_data" / "mustard0"
+    demo_mesh = demo_scene / "mesh" / "textured_simple.obj"
+    if not demo_mesh.is_file():
+      warnings.append(f"run_demo demo scene: missing {demo_mesh}")
+    else:
+      print(f"run_demo demo_data: ok ({demo_mesh.relative_to(repo_root)})")
+
+  print()
+  for w in warnings:
+    print(f"WARNING: {w}")
+  for e in errors:
+    print(f"ERROR: {e}")
+
+  # Non-zero only when imports or core checks fail; missing weights/data still exit 0.
+  if errors:
+    return 1
+  return 0
+
+
+if __name__ == "__main__":
+  raise SystemExit(main())