dasha_f
0d32f32db0
Замкнутый контур "поток -> CV -> механика": товары идут по конвейеру с шагом 700 мм, класс определяется стереопайплайном во время движения, пушер и плуг реагируют физически. Состав: * control_test/ - ячейка и CV. run_sorting_cv.py + cv_worker.py (два процесса, потому что torch внутри Isaac роняет сцену), cell.py (физика лент, плуга, пушера), measure_plane.py (замер габаритов), README.md и .memory.md с замерами, проблемами и ловушками * robozon_sorter/ - модули симуляции, scripts/ - утилиты, scene/ - сцены * assets/ - меши товаров, плуг, объекты Objaverse Бейзлайн CV: DEFOM-Stereo vitl, вход 480, iters 24, кроп зоны осмотра, без сегментации. На потоке 700 мм - классы 8/9, габариты MAE 32.8 мм, 469 мс на товар при такте 700 мс. Веса моделей (4.5 ГБ) и пропсы конвейера NVIDIA (274 МБ) не включены - источники и команды скачивания в MODELS.md. Выход прогонов (captures/, runtime/) не включён: воспроизводится. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
77 lines
2.9 KiB
Python
77 lines
2.9 KiB
Python
#!/usr/bin/env python3
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"""Flatten the classified objects out of the working scene into assets/items/.
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/home/whatevenif/isaacsim/python.sh scripts/export_item_library.py
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The six meshes bundled in `assets/meshes/` are a smoke-test set, two per class. A sorting
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run wants the whole catalogue, and the classified objects live inside
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`robozon_conveyor_scaled.usd` under `/World/CVObjects`, referencing `.glb` files that are
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not in this repo. Each one is therefore *flattened* on export so the result carries its own
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geometry and composes anywhere - the recipe in CLAUDE.md, applied in bulk.
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Ground truth comes from `categories.json`: `zone` (B/C/D) and `obb_extents_m`, which the
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run harness reports predicted dimensions against. Objects larger than the 500 mm incoming
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envelope are skipped - they could never reach this conveyor.
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"""
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from __future__ import annotations
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import json
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import sys
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from pathlib import Path
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from pxr import Usd, UsdGeom
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ASSETS = Path("/home/dasha/isaac_assets")
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SCENE = ASSETS / "robozon_conveyor_scaled.usd"
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CATS = ASSETS / "categories.json"
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OUT = Path(__file__).resolve().parent.parent / "assets" / "items"
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ENVELOPE_MM = 500.0
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def main():
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if not SCENE.exists():
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sys.exit(f"{SCENE} not found")
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cats = json.loads(CATS.read_text())
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OUT.mkdir(parents=True, exist_ok=True)
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src = Usd.Stage.Open(str(SCENE))
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root = src.GetPrimAtPath("/World/CVObjects")
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if not root.IsValid():
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sys.exit("/World/CVObjects missing")
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present = {p.GetName() for p in root.GetChildren()}
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manifest, skipped = {}, []
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for name, meta in sorted(cats.items()):
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if name not in present:
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skipped.append((name, "not in scene"))
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continue
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ext_mm = [e * 1000.0 for e in meta["obb_extents_m"]]
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if max(ext_mm) > ENVELOPE_MM:
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skipped.append((name, f"oversize {max(ext_mm):.0f} mm"))
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continue
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ns = Usd.Stage.CreateInMemory()
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item = UsdGeom.Xform.Define(ns, "/Item")
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item.GetPrim().GetReferences().AddReference(str(SCENE), f"/World/CVObjects/{name}")
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ns.SetDefaultPrim(item.GetPrim())
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dst = OUT / f"{name}.usd"
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ns.Flatten().Export(str(dst))
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manifest[name] = dict(zone=meta["zone"],
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gt_dims_mm=[round(v) for v in sorted(ext_mm, reverse=True)],
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k_round=round(meta.get("k_round", 0.0), 3),
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label_ru=meta.get("label_ru", ""))
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print(f" {name:22s} {meta['zone']} {manifest[name]['gt_dims_mm']} "
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f"{dst.stat().st_size / 1024:.0f} KB")
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(OUT / "manifest.json").write_text(json.dumps(manifest, indent=2, ensure_ascii=False))
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from collections import Counter
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print(f"\nexported {len(manifest)} -> {OUT} "
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f"{dict(Counter(v['zone'] for v in manifest.values()))}")
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if skipped:
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print(f"skipped {len(skipped)}: " + ", ".join(f"{n} ({w})" for n, w in skipped[:8]))
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if __name__ == "__main__":
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main()
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