archive/old_scripts/video_process_v2.py

import tensorflow_datasets as tfds
import numpy as np
import json, imageio
from pathlib import Path
from tqdm import tqdm

FAILED_DIR = Path("./droid_failed")
FAILED_DIR.mkdir(exist_ok=True, parents=True)

def is_failed_episode(episode):
    """
    判断是否失败案例：
    - 找到最后一个 step（is_last == True）
    - is_terminal == False → 失败
    """
    last_step = None
    for step in episode["steps"].as_numpy_iterator():
        last_step = step
    return (bool(last_step["is_last"]) == True) and (bool(last_step["is_terminal"]) == False)

def save_failed_episode(episode, idx):
    frames = []
    meta = {
        "episode_id": idx,
        "language_instruction": None,
        "steps": []
    }

    for t, step in enumerate(episode["steps"].as_numpy_iterator()):
        if meta["language_instruction"] is None:
            instr = step.get("language_instruction", b"")
            meta["language_instruction"] = instr.decode("utf-8") if isinstance(instr, bytes) else str(instr)

        wrist = step["observation"]["wrist_image_left"]
        ext1 = step["observation"]["exterior_image_1_left"]
        frame = np.concatenate([wrist, ext1], axis=1)
        frames.append(frame)

        meta["steps"].append({
            "t": t,
            "action": step["action"].tolist(),
            "joint_position": step["action_dict"]["joint_position"].tolist(),
            "is_first": bool(step["is_first"]),
            "is_last": bool(step["is_last"]),
            "is_terminal": bool(step["is_terminal"]),
        })

    # Save video
    video_path = FAILED_DIR / f"failed_{idx:06d}.mp4"
    import imageio_ffmpeg
    writer = imageio.get_writer(video_path, fps=15, codec='libx264')
    for f in frames:
        writer.append_data(f)
    writer.close()

    # Save metadata
    json_path = FAILED_DIR / f"failed_{idx:06d}.json"
    with open(json_path, "w") as f:
        json.dump(meta, f, indent=2)

    print(f"[FAIL] Saved → {video_path}")

# ---- Load full dataset (streaming) ----
ds = tfds.load("droid", data_dir="/playpen-ssd/dataset/", split="train", shuffle_files=False)

num_total = ds.cardinality().numpy() if hasattr(ds, "cardinality") else None

count = 0
for idx, episode in tqdm(enumerate(ds), total=num_total, desc="Scanning Episodes"):
    if is_failed_episode(episode):
        save_failed_episode(episode, idx)
        count += 1

print(f"\n✅ Completed. Extracted {count} failed episodes.")

# import tensorflow_datasets as tfds
# import numpy as np
# import json, imageio
# from pathlib import Path

# FAILED_DIR = Path("./droid_failed")
# FAILED_DIR.mkdir(exist_ok=True, parents=True)

# def is_failed_episode(episode):
#     """
#     判断是否失败案例：
#     - 找到最后一个 step（is_last == True）
#     - is_terminal == False → 表示执行结束但失败
#     """
#     for step in episode["steps"].as_numpy_iterator():
#         pass  # iterate to last step
#     return (bool(step["is_last"]) == True) and (bool(step["is_terminal"]) == False)

# def extract_failed_episode(episode, idx):
#     frames = []
#     meta = {
#         "episode_id": idx,
#         "language_instruction": None,
#         "steps": []
#     }

#     steps_iter = episode["steps"].as_numpy_iterator()

#     for t, step in enumerate(steps_iter):
#         if meta["language_instruction"] is None:
#             instr = step.get("language_instruction", b"")
#             meta["language_instruction"] = (
#                 instr.decode("utf-8") if isinstance(instr, bytes) else str(instr)
#             )

#         wrist = step["observation"]["wrist_image_left"]
#         ext1 = step["observation"]["exterior_image_1_left"]
#         frame = np.concatenate([wrist, ext1], axis=1)
#         frames.append(frame)

#         meta["steps"].append({
#             "t": t,
#             "action": step["action"].tolist(),
#             "joint_position": step["action_dict"]["joint_position"].tolist(),
#             "is_first": bool(step["is_first"]),
#             "is_last": bool(step["is_last"]),
#             "is_terminal": bool(step["is_terminal"]),
#         })

#     # Save FAILED video + metadata
#     video_path = FAILED_DIR / f"failed_{idx:06d}.mp4"
#     json_path = FAILED_DIR / f"failed_{idx:06d}.json"

#     import imageio_ffmpeg
#     writer = imageio.get_writer(video_path, fps=15, codec='libx264')
#     for f in frames:
#         writer.append_data(f)
#     writer.close()

#     with open(json_path, "w") as f:
#         json.dump(meta, f, indent=2)

#     print(f"[FAIL] Saved → {video_path}")
#     return video_path, json_path


# # ---- Run ----
# ds = tfds.load("droid_100", data_dir="/playpen-ssd/dataset/", split="train")

# count = 0
# for idx, episode in enumerate(ds):
#     if is_failed_episode(episode):
#         extract_failed_episode(episode, idx)
#         count += 1

# print(f"\n✅ Done. Found and extracted {count} failed episodes.")