| |
| """ |
| GT trajectory helpers without importing torch / diffsynth / run_replay_loop_two_chunk. |
| Used by run_basic_replay_gt.sh to resolve VIDEO_NAME=AUTO without pulling train.py. |
| Logic must match run_replay_loop_two_chunk.build_gt_trajectory_actions. |
| """ |
| from __future__ import annotations |
|
|
| import os |
| import sys |
|
|
|
|
| def _repo_root_from_here() -> str: |
| _here = os.path.dirname(os.path.abspath(__file__)) |
| |
| return os.path.dirname(os.path.dirname(os.path.dirname(os.path.dirname(_here)))) |
|
|
|
|
| def _ensure_repo_path() -> None: |
| r = _repo_root_from_here() |
| if r not in sys.path: |
| sys.path.insert(0, r) |
|
|
|
|
| def load_pose_rt(json_file: str, frame_idx: int): |
| _ensure_repo_path() |
| from src.model_training.fov_retrieval import load_camera_pose, pose_to_rt |
| pose = load_camera_pose(json_file, int(frame_idx)) |
| if pose is None: |
| return None |
| return pose_to_rt(pose, constrain_to_xy=True) |
|
|
|
|
| def get_relative_rt(rt, ref_rt): |
| _ensure_repo_path() |
| from src.model_training.fov_retrieval import convert_rt_to_relative |
| if rt is None or ref_rt is None or len(rt) < 12 or len(ref_rt) < 12: |
| return None |
| out = convert_rt_to_relative([rt], ref_rt) |
| return out[0] if out else None |
|
|
|
|
| def build_gt_trajectory_actions(dataset_base, video_name, start_frame, chunk_frames, json_file=None): |
| if json_file is None: |
| json_file = os.path.join(dataset_base, "jsons", f"{video_name}.json") |
| if not os.path.isfile(json_file): |
| return None |
| try: |
| rt_list = [load_pose_rt(json_file, start_frame + i) for i in range(chunk_frames)] |
| if not rt_list or any(r is None or len(r) < 12 for r in rt_list): |
| return None |
| ref_rt = rt_list[0] |
| rel_actions = {str(i): get_relative_rt(rt_list[i], ref_rt) for i in range(chunk_frames)} |
| if any(v is None for v in rel_actions.values()): |
| return None |
| return rel_actions |
| except Exception: |
| return None |
|
|
