| |
| """Extract one mid-episode frame pair + run SmolVLA attention for missing tasks. |
| |
| docker exec rm65_dev2 bash -lc 'cd /home/sdznkj/zkx_ws/sendlerobot && \\ |
| HF_HUB_OFFLINE=1 PYTHONPATH=. python3 scripts/draw_missing_task_attn.py' |
| """ |
|
|
| from __future__ import annotations |
|
|
| import json |
| import subprocess |
| import sys |
| from pathlib import Path |
|
|
| import numpy as np |
|
|
| ROOT = Path(__file__).resolve().parents[1] |
| FRAME_ROOT = ROOT / "outputs/diag/attn_frames" |
|
|
| TASKS = [ |
| { |
| "name": "usb", |
| "ckpt": ROOT / "smolvla_rm65_usb_100ep_s40000", |
| "dataset": ROOT / "datasets/cleaned/rm65_usb_insert", |
| "cam2_key": "observation.images.mono", |
| "out": ROOT / "outputs/diag/smolvla_attn_usb_f074", |
| "frame": 74, |
| "episode": 0, |
| }, |
| { |
| "name": "cleanup", |
| "ckpt": ROOT / "smolvla_rm65_cleanup_47ep_s40000", |
| "dataset": ROOT / "datasets/cleaned/rm65_cleanup_the_desk", |
| "cam2_key": "observation.images.astra", |
| "out": ROOT / "outputs/diag/smolvla_attn_cleanup_f074", |
| "frame": 74, |
| "episode": 0, |
| }, |
| { |
| "name": "place", |
| "ckpt": ROOT / "smolvla_rm65_place_47ep_s40000", |
| "dataset": ROOT / "datasets/cleaned/rm65_place_to_slot", |
| "cam2_key": "observation.images.astra", |
| "out": ROOT / "outputs/diag/smolvla_attn_place_f074", |
| "frame": 74, |
| "episode": 0, |
| }, |
| ] |
|
|
|
|
| def extract_frame(mp4: Path, index: int) -> np.ndarray: |
| import av |
|
|
| container = av.open(str(mp4)) |
| for i, frame in enumerate(container.decode(video=0)): |
| if i == index: |
| rgb = frame.to_ndarray(format="rgb24") |
| container.close() |
| return rgb |
| container.close() |
| raise FileNotFoundError(f"{mp4} has no frame {index}") |
|
|
|
|
| def prepare_task(task: dict) -> dict: |
| import cv2 |
| import pandas as pd |
|
|
| ds = task["dataset"] |
| ep = int(task["episode"]) |
| frame = int(task["frame"]) |
| info = json.loads((ds / "meta/info.json").read_text()) |
| tasks = {} |
| for line in (ds / "meta/tasks.jsonl").read_text().splitlines(): |
| if line.strip(): |
| row = json.loads(line) |
| tasks[int(row["task_index"])] = row["task"] |
| chunk = ep // int(info.get("chunks_size", 1000)) |
| pq = ds / info["data_path"].format(episode_chunk=chunk, episode_index=ep) |
| df = pd.read_parquet(pq) |
| n = len(df) |
| if frame >= n: |
| frame = n // 2 |
| state = np.asarray(df["observation.state"].iloc[frame], dtype=np.float32)[:7] |
| task_str = tasks[int(df["task_index"].iloc[frame])] |
| front_p = ds / info["video_path"].format( |
| episode_chunk=chunk, episode_index=ep, video_key="observation.images.front" |
| ) |
| cam2_p = ds / info["video_path"].format( |
| episode_chunk=chunk, episode_index=ep, video_key=task["cam2_key"] |
| ) |
| front = extract_frame(front_p, frame) |
| cam2 = extract_frame(cam2_p, frame) |
| out_dir = FRAME_ROOT / task["name"] |
| out_dir.mkdir(parents=True, exist_ok=True) |
| cam1_jpg = out_dir / "camera1_front.jpg" |
| cam2_jpg = out_dir / "camera2.jpg" |
| cv2.imwrite(str(cam1_jpg), cv2.cvtColor(front, cv2.COLOR_RGB2BGR)) |
| cv2.imwrite(str(cam2_jpg), cv2.cvtColor(cam2, cv2.COLOR_RGB2BGR)) |
| meta = { |
| "task": task_str, |
| "state": state.tolist(), |
| "frame": frame, |
| "episode": ep, |
| "cam1": str(cam1_jpg), |
| "cam2": str(cam2_jpg), |
| } |
| (out_dir / "meta.json").write_text(json.dumps(meta, indent=2, ensure_ascii=False) + "\n") |
| print("prepared", task["name"], "frame", frame, "task=", task_str[:60]) |
| return meta |
|
|
|
|
| def run_attn(task: dict, meta: dict) -> None: |
| out = Path(task["out"]) |
| if (out / "lang2img_camera1.png").is_file() and (out / "action2img_denoise0.png").is_file(): |
| print("skip existing attn", out) |
| return |
| |
| state_csv = ",".join(f"{x:.6f}" for x in meta["state"]) |
| cmd = [ |
| sys.executable, |
| str(ROOT / "scripts/smolvla_diag_visualize.py"), |
| "--ckpt", |
| str(task["ckpt"]), |
| "--cam1", |
| meta["cam1"], |
| "--cam2", |
| meta["cam2"], |
| "--task", |
| meta["task"], |
| f"--state={state_csv}", |
| "--out", |
| str(out), |
| "--device", |
| "cuda", |
| ] |
| print("RUN", " ".join(cmd[:6]), "...", flush=True) |
| subprocess.check_call(cmd, cwd=str(ROOT)) |
| |
| pngs = sorted(out.glob("*.png")) |
| items = "".join(f"<li><a href='{p.name}'>{p.name}</a></li>" for p in pngs) |
| (out / "index.html").write_text( |
| f"<html><body style='background:#111;color:#eee;font-family:sans-serif'>" |
| f"<h3>attn {task['name']} f{meta['frame']:03d}</h3><ul>{items}</ul></body></html>\n", |
| encoding="utf-8", |
| ) |
|
|
|
|
| def main() -> None: |
| for task in TASKS: |
| meta = prepare_task(task) |
| run_attn(task, meta) |
| print("ALL_ATTN_OK") |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
