diff --git a/.gitattributes b/.gitattributes index bed0738c7eeb449bca98b5d2f33c89a1ee56349a..fbdd21095d62036d0b1cc34fee12af5f522479c6 100644 --- a/.gitattributes +++ b/.gitattributes @@ -58,3 +58,27 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text # Video files - compressed *.mp4 filter=lfs diff=lfs merge=lfs -text *.webm filter=lfs diff=lfs merge=lfs -text +obj_usd/unseen_000.usd filter=lfs diff=lfs merge=lfs -text +obj_usd/unseen_001.usd filter=lfs diff=lfs merge=lfs -text +obj_usd/unseen_002.usd filter=lfs diff=lfs merge=lfs -text +obj_usd/unseen_003.usd filter=lfs diff=lfs merge=lfs -text +obj_usd/unseen_004.usd filter=lfs diff=lfs merge=lfs -text +obj_usd/unseen_005.usd filter=lfs diff=lfs merge=lfs -text +obj_usd/unseen_007.usd filter=lfs diff=lfs merge=lfs -text +obj_usd/unseen_008.usd filter=lfs diff=lfs merge=lfs -text +obj_usd/unseen_009.usd filter=lfs diff=lfs merge=lfs -text +obj_usd/unseen_010.usd filter=lfs diff=lfs merge=lfs -text +obj_usd/unseen_011.usd filter=lfs diff=lfs merge=lfs -text +obj_usd/unseen_013.usd filter=lfs diff=lfs merge=lfs -text +obj_usd/unseen_014.usd filter=lfs diff=lfs merge=lfs -text +obj_usd/unseen_015.usd filter=lfs diff=lfs merge=lfs -text +obj_usd/unseen_016.usd filter=lfs diff=lfs merge=lfs -text +obj_usd/unseen_017.usd filter=lfs diff=lfs merge=lfs -text +obj_usd/unseen_018.usd filter=lfs diff=lfs merge=lfs -text +obj_usd/unseen_020.usd filter=lfs diff=lfs merge=lfs -text +obj_usd/unseen_023.usd filter=lfs diff=lfs merge=lfs -text +obj_usd/unseen_024.usd filter=lfs diff=lfs merge=lfs -text +obj_usd/unseen_025.usd filter=lfs diff=lfs merge=lfs -text +obj_usd/unseen_026.usd filter=lfs diff=lfs merge=lfs -text +obj_usd/unseen_027.usd filter=lfs diff=lfs merge=lfs -text +obj_usd/unseen_028.usd filter=lfs diff=lfs merge=lfs -text diff --git a/bundle_summary.json b/bundle_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..0fd6dcd381e718821a907d77fa781182b4ae5287 --- /dev/null +++ b/bundle_summary.json @@ -0,0 +1,19 @@ +{ + "bundle": "eval_unseen_sim_bundle", + "updated_utc": "2026-05-28T14:29:44.870023+00:00", + "format_version": "2.0", + "n_objects": 29, + "n_candidates_per_object": 500, + "candidates_status": "migrated from candidates", + "sim_z_yaw_deg": 0, + "object_list_source": "evaluation/configs/eval_unseen_all.csv", + "selection_criterion": "eval_unseen_all.csv (enabled=1)", + "datasets": { + "unseen": 29 + }, + "paths": { + "usd_meta": "obj_usd/{obj_id}.usd + {obj_id}_meta.json", + "candidates": "candidates/{obj_id}.json", + "index": "manifest.csv" + } +} diff --git a/candidates/README.md b/candidates/README.md new file mode 100644 index 0000000000000000000000000000000000000000..e7b6e8d5712a69a8b7ccee9439e222d5d6e9f050 --- /dev/null +++ b/candidates/README.md @@ -0,0 +1,23 @@ +# Candidates + +每物体 `{obj_id}.json`（format 2.0），默认 **500** 条、`sim_z_yaw_deg = 0`。 + +生成 pool HDF5： + +```bash +python evaluation/eval_pool.py \ + --obj-list evaluation/configs/eval_unseen_all.csv \ + --generate-candidate-each-trial \ + --candidates-only \ + --trials-per-obj-yaw 500 \ + --z-yaw-deg 0 \ + --result-dir output/evaluation/unseen_yaw0_n500_poolgen \ + --candidate-gpu-ids 0,1 \ + --candidate-workers 6 +``` + +写入本目录： + +```bash +python tools/migrate_eval_unseen_pool_candidates_to_bundle.py +``` diff --git a/candidates/unseen_000.json b/candidates/unseen_000.json new file mode 100644 index 0000000000000000000000000000000000000000..09b3ca3946c0f38689d52fbaf933aa013d88d55f --- /dev/null +++ b/candidates/unseen_000.json @@ -0,0 +1,12508 @@ +{ + "format_version": "2.0", + "obj_id": "unseen_000", + "n_candidates": 500, + "sim_z_yaw_deg": 0.0, + "candidates": { + "candidate_0": { + "position": [ + 0.003942034672945738, + 0.008885782212018967, + 0.07988838851451874 + ], + "rotation": [ + [ + 0.9573009610176086, + 0.05161947011947632, + -0.2844473123550415 + ], + [ + -0.0005455709178932011, + -0.9836053252220154, + -0.18033379316329956 + 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"/home/vision/Project/Affordance2Grasp/data_hub/RawData/Unseen/unseen_028.obj", + "up_axis": "Z", + "z_offset_m": 0.095761 +} diff --git a/scene_layout_reference.py b/scene_layout_reference.py new file mode 100644 index 0000000000000000000000000000000000000000..bfe03d4a07c40f949d9e7781ea11597ebd1daff7 --- /dev/null +++ b/scene_layout_reference.py @@ -0,0 +1,127 @@ +#!/usr/bin/env python3 +""" +场景布置与 grasp 位姿变换（本 bundle 配套，纯 numpy）。 + +示例: + python scene_layout_reference.py --obj-id A01006 + python scene_layout_reference.py --obj-id A01006 --candidate-index 0 +""" + +from __future__ import annotations + +import argparse +import json +from pathlib import Path + +import numpy as np + +ROBOT_POSITION = np.array([0.2, -0.05, 0.8], dtype=np.float64) +ROBOT_ORIENTATION_EULER_DEG = np.array([0.0, 0.0, 90.0], dtype=np.float64) +TABLE_POSITION = np.array([0.0, 1.0, 0.75], dtype=np.float64) +TABLE_SCALE = np.array([2.0, 2.0, 0.1], dtype=np.float64) +TABLE_TOP_Z = 0.80 +OBJECT_XY = np.array([0.0, 0.55], dtype=np.float64) +TCP_OFFSET = 0.105 +R_ADAPT = np.array([[0, 1, 0], [-1, 0, 0], [0, 0, 1]], dtype=np.float64) + + +def euler_xyz_deg_to_matrix(euler_deg: np.ndarray) -> np.ndarray: + rx, ry, rz = np.radians(np.asarray(euler_deg, dtype=np.float64)) + cx, sx = np.cos(rx), np.sin(rx) + cy, sy = np.cos(ry), np.sin(ry) + cz, sz = np.cos(rz), np.sin(rz) + Rx = np.array([[1, 0, 0], [0, cx, -sx], [0, sx, cx]], dtype=np.float64) + Ry = np.array([[cy, 0, sy], [0, 1, 0], [-sy, 0, cy]], dtype=np.float64) + Rz = np.array([[cz, -sz, 0], [sz, cz, 0], [0, 0, 1]], dtype=np.float64) + return Rz @ Ry @ Rx + + +def load_z_offset_m(bundle_dir: Path, obj_id: str) -> float: + meta_path = bundle_dir / "obj_usd" / f"{obj_id}_meta.json" + return float(json.loads(meta_path.read_text(encoding="utf-8"))["z_offset_m"]) + + +def resolve_object_world_placement( + obj_id: str, + bundle_dir: Path, + *, + sim_z_yaw_deg: float = 0.0, +) -> dict: + z_offset = load_z_offset_m(bundle_dir, obj_id) + euler = np.array([0.0, 0.0, float(sim_z_yaw_deg)], dtype=np.float64) + pos = np.array([OBJECT_XY[0], OBJECT_XY[1], TABLE_TOP_Z + z_offset], dtype=np.float64) + return { + "obj_id": obj_id, + "position_world": pos.tolist(), + "orientation_euler_deg": euler.tolist(), + "z_offset_m": z_offset, + "table_top_z": TABLE_TOP_Z, + "sim_z_yaw_deg": float(sim_z_yaw_deg), + } + + +def grasp_mesh_to_panda_hand_target( + position_mesh: np.ndarray, + rotation_mesh: np.ndarray, + placement: dict, +) -> tuple[np.ndarray, np.ndarray]: + T = np.eye(4, dtype=np.float64) + T[:3, :3] = euler_xyz_deg_to_matrix( + np.array(placement["orientation_euler_deg"], dtype=np.float64) + ) + T[:3, 3] = np.asarray(placement["position_world"], dtype=np.float64) + p = np.asarray(position_mesh, dtype=np.float64).reshape(3) + R = np.asarray(rotation_mesh, dtype=np.float64).reshape(3, 3) + pos_w = (T @ np.append(p, 1.0))[:3] + rot_w = T[:3, :3] @ R + rot_w = rot_w @ R_ADAPT + pos_w = pos_w - rot_w[:, 2] * TCP_OFFSET + min_z = TABLE_TOP_Z + 0.02 + if pos_w[2] < min_z: + pos_w = pos_w.copy() + pos_w[2] = min_z + return pos_w, rot_w + + +def load_candidate(bundle_dir: Path, obj_id: str, index: int = 0) -> dict: + doc = json.loads((bundle_dir / "candidates" / f"{obj_id}.json").read_text(encoding="utf-8")) + c = doc["candidates"][f"candidate_{index}"] + return { + "position": np.array(c["position"], dtype=np.float64), + "rotation": np.array(c["rotation"], dtype=np.float64), + "name": c.get("name", f"candidate_{index}"), + } + + +def main() -> None: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument("--bundle-dir", type=Path, default=Path(__file__).resolve().parent) + parser.add_argument("--obj-id", required=True) + parser.add_argument("--candidate-index", type=int, default=None) + args = parser.parse_args() + + placement = resolve_object_world_placement(args.obj_id, args.bundle_dir) + out = { + "table": {"position": TABLE_POSITION.tolist(), "top_z": TABLE_TOP_Z}, + "franka": { + "position": ROBOT_POSITION.tolist(), + "orientation_euler_deg": ROBOT_ORIENTATION_EULER_DEG.tolist(), + }, + "object": placement, + } + if args.candidate_index is not None: + cand = load_candidate(args.bundle_dir, args.obj_id, args.candidate_index) + pos_w, rot_w = grasp_mesh_to_panda_hand_target( + cand["position"], cand["rotation"], placement + ) + out["example"] = { + "candidate_index": args.candidate_index, + "name": cand["name"], + "position_mesh": cand["position"].tolist(), + "panda_hand_target_world": {"position": pos_w.tolist()}, + } + print(json.dumps(out, indent=2, ensure_ascii=False)) + + +if __name__ == "__main__": + main()