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0000000000000000000000000000000000000000..0d952502b0bf4629720960c8c3a934709bc7679b --- /dev/null +++ b/.backup/meta/tasks.parquet @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:d42d6667a74fc5702bcc25e73fdd66afd8e92f88387467967fab69254c0a0d0f +size 2253 diff --git a/README.md b/README.md new file mode 100644 index 0000000000000000000000000000000000000000..06b91fd7231baa133a86f41f53e73ec99231ebd6 --- /dev/null +++ b/README.md @@ -0,0 +1,169 @@ +--- +license: apache-2.0 +task_categories: +- robotics +tags: +- LeRobot +configs: +- config_name: default + data_files: data/*/*.parquet +--- + +This dataset was created using [LeRobot](https://github.com/huggingface/lerobot). + + + + + + + + +## Dataset Description + + + +- **Homepage:** [More Information Needed] +- **Paper:** [More Information Needed] +- **License:** apache-2.0 + +## Dataset Structure + +[meta/info.json](meta/info.json): +```json +{ + "codebase_version": "v3.0", + "robot_type": "omx_follower", + "total_episodes": 103, + "total_frames": 96245, + "total_tasks": 1, + "chunks_size": 1000, + "data_files_size_in_mb": 100, + "video_files_size_in_mb": 200, + "fps": 30, + "splits": { + "train": "0:103" + }, + "data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet", + "video_path": "videos/{video_key}/chunk-{chunk_index:03d}/file-{file_index:03d}.mp4", + "features": { + "action": { + "dtype": "float32", + "names": [ + "shoulder_pan.pos", + "shoulder_lift.pos", + "elbow_flex.pos", + "wrist_flex.pos", + "wrist_roll.pos", + "gripper.pos" + ], + "shape": [ + 6 + ] + }, + "observation.state": { + "dtype": "float32", + "names": [ + "shoulder_pan.pos", + "shoulder_lift.pos", + "elbow_flex.pos", + "wrist_flex.pos", + "wrist_roll.pos", + "gripper.pos" + ], + "shape": [ + 6 + ] + }, + "observation.images.wrist": { + "dtype": "video", + "shape": [ + 480, + 640, + 3 + ], + "names": [ + "height", + "width", + "channels" + ], + "info": { + "video.height": 480, + "video.width": 640, + "video.codec": "av1", + "video.pix_fmt": "yuv420p", + "video.is_depth_map": false, + "video.fps": 30, + "video.channels": 3, + "has_audio": false + } + }, + "observation.images.top": { + "dtype": "video", + "shape": [ + 480, + 640, + 3 + ], + "names": [ + "height", + "width", + "channels" + ], + "info": { + "video.height": 480, + "video.width": 640, + "video.codec": "av1", + "video.pix_fmt": "yuv420p", + "video.is_depth_map": false, + "video.fps": 30, + "video.channels": 3, + "has_audio": false + } + }, + "timestamp": { + "dtype": "float32", + "shape": [ + 1 + ], + "names": null + }, + "frame_index": { + "dtype": "int64", + "shape": [ + 1 + ], + "names": null + }, + "episode_index": { + "dtype": "int64", + "shape": [ + 1 + ], + "names": null + }, + "index": { + "dtype": "int64", + "shape": [ + 1 + ], + "names": null + }, + "task_index": { + "dtype": "int64", + "shape": [ + 1 + ], + "names": null + } + } +} +``` + + +## Citation + +**BibTeX:** + +```bibtex +[More Information Needed] 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sha256:23477db97113af3a8f4042637e47497758dc9f99a26407bbdf77ec8ced69d970 +size 643042 diff --git a/fix_episode_indices.py b/fix_episode_indices.py new file mode 100644 index 0000000000000000000000000000000000000000..9b8ab2fba7f54c3cbedd19a11d2a7493529f3fa3 --- /dev/null +++ b/fix_episode_indices.py @@ -0,0 +1,227 @@ +"""Renumber episode_index so every recording becomes a unique, contiguous episode. + +See README / chat context. Operates in-place on ./data, ./meta, ./meta/info.json. +Run from the dataset root. Backup is made under ./.backup. +""" + +from __future__ import annotations + +import glob +import json +import os +from pathlib import Path + +import pyarrow as pa +import pyarrow.parquet as pq + +ROOT = Path(__file__).resolve().parent +DATA_DIR = ROOT / "data" +META_EP_DIR = ROOT / "meta" / "episodes" +INFO_PATH = ROOT / "meta" / "info.json" + + +def read_all_episode_meta(): + """Return list of dict rows across every meta/episodes file (small number of columns).""" + cols = [ + "episode_index", + "length", + "data/chunk_index", + "data/file_index", + "dataset_from_index", + "dataset_to_index", + ] + rows = [] + for f in sorted(glob.glob(str(META_EP_DIR / "chunk-*" / "*.parquet"))): + t = pq.read_table(f, columns=cols) + d = t.to_pydict() + for i in range(t.num_rows): + rows.append({ + "episode_index": d["episode_index"][i], + "length": d["length"][i], + "chunk_index": d["data/chunk_index"][i], + "file_index": d["data/file_index"][i], + "dataset_from_index": d["dataset_from_index"][i], + "dataset_to_index": d["dataset_to_index"][i], + "meta_file": f, + }) + return rows + + +def build_mapping(rows): + """Sort rows by (chunk_index, file_index, dataset_from_index) and assign new ids 0..N-1. + + Also compute the new compact `index` range per (chunk, file, old_ep) so we can + update the data parquet `index` column. The meta's dataset_from/to_index already + lives in the compact space and matches this ordering, so we use it directly. + """ + rows_sorted = sorted( + rows, + key=lambda r: (r["chunk_index"], r["file_index"], r["dataset_from_index"]), + ) + mapping = {} # (chunk, file, old_ep) -> dict(new_ep, new_from, new_to, old_from, old_to) + for new_ep, r in enumerate(rows_sorted): + key = (r["chunk_index"], r["file_index"], r["episode_index"]) + assert key not in mapping, f"duplicate key {key}" + mapping[key] = { + "new_ep": new_ep, + "new_from": r["dataset_from_index"], + "new_to": r["dataset_to_index"], + "old_from": r["dataset_from_index"], # placeholder; we fill real old_from below + "old_to": r["dataset_to_index"], + "length": r["length"], + } + return mapping, rows_sorted + + +def fix_data_files(mapping): + """Rewrite every data parquet: remap episode_index and re-number index column. + + `index` for each data file starts at `cumulative_frames` seen so far (chronological, + numeric file order), matching the meta's compact `dataset_from_index` space. + """ + data_files = sorted(glob.glob(str(DATA_DIR / "chunk-*" / "*.parquet"))) + cum = 0 + for df in data_files: + # Parse chunk/file from path + chunk = int(Path(df).parent.name.split("-")[1]) + file_idx = int(Path(df).stem.split("-")[1]) + + table = pq.read_table(df) + schema = table.schema + d = table.to_pydict() + n = table.num_rows + + # New index column: cum .. cum + n - 1 + new_index = list(range(cum, cum + n)) + + # New episode_index: map each row's old ep -> new ep using (chunk, file, old_ep) + old_eps = d["episode_index"] + new_eps = [] + for old_ep in old_eps: + key = (chunk, file_idx, old_ep) + m = mapping[key] + new_eps.append(m["new_ep"]) + + d["index"] = new_index + d["episode_index"] = new_eps + + new_table = pa.Table.from_pydict(d, schema=schema) + pq.write_table(new_table, df, compression="zstd") + print( + f"data/chunk-{chunk:03d}/file-{file_idx:03d}.parquet: " + f"rows={n} index={cum}..{cum + n - 1} eps={sorted(set(new_eps))[0]}..{sorted(set(new_eps))[-1]}" + ) + cum += n + + return cum + + +def fix_meta_files(mapping): + """For each meta/episodes parquet file, update episode_index and index-related stats.""" + meta_files = sorted(glob.glob(str(META_EP_DIR / "chunk-*" / "*.parquet"))) + index_stat_cols = [ + "stats/index/min", + "stats/index/max", + "stats/index/mean", + "stats/index/q01", + "stats/index/q10", + "stats/index/q50", + "stats/index/q90", + "stats/index/q99", + # std is invariant to translation, count is invariant + ] + + for mf in meta_files: + chunk = int(Path(mf).parent.name.split("-")[1]) + # meta file index: derive file_index from the data/file_index column of the first row + table = pq.read_table(mf) + schema = table.schema + d = table.to_pydict() + n = table.num_rows + + new_ep_col = [] + # Stats: translate index stats by (new_from - old_from). All rows in this file + # may correspond to different data files in theory, but in practice each meta file + # maps 1:1 to a data file. Regardless, we translate per-row. + for i in range(n): + old_ep = d["episode_index"][i] + ch = d["data/chunk_index"][i] + fi = d["data/file_index"][i] + key = (ch, fi, old_ep) + m = mapping[key] + new_ep_col.append(m["new_ep"]) + + # Translate index-based stats + # old_start = stats/index/min[i][0] + # new_start = m["new_from"] + old_start = d["stats/index/min"][i][0] + new_start = m["new_from"] + delta = new_start - old_start + if delta != 0: + for col in index_stat_cols: + v = d[col][i] + # v is a list with one element (or possibly a scalar inside) + d[col][i] = [v[0] + delta] + + # Replace episode_index stats with the single new value + for col, val in [ + ("stats/episode_index/min", [new_ep_col[-1]]), + ("stats/episode_index/max", [new_ep_col[-1]]), + ("stats/episode_index/mean", [float(new_ep_col[-1])]), + ("stats/episode_index/q01", [float(new_ep_col[-1])]), + ("stats/episode_index/q10", [float(new_ep_col[-1])]), + ("stats/episode_index/q50", [float(new_ep_col[-1])]), + ("stats/episode_index/q90", [float(new_ep_col[-1])]), + ("stats/episode_index/q99", [float(new_ep_col[-1])]), + ]: + if col in d: + d[col][i] = val + # std=0 and count=length are already correct (single-valued per episode) + + d["episode_index"] = new_ep_col + + # Sort rows within the meta file by new episode_index for cleanliness + order = sorted(range(n), key=lambda k: new_ep_col[k]) + for col in list(d.keys()): + d[col] = [d[col][k] for k in order] + + new_table = pa.Table.from_pydict(d, schema=schema) + pq.write_table(new_table, mf, compression="zstd") + print( + f"meta/episodes/chunk-{chunk:03d}/{Path(mf).name}: " + f"rows={n} new_eps={d['episode_index'][0]}..{d['episode_index'][-1]}" + ) + + +def update_info_json(total_episodes: int, total_frames: int): + with open(INFO_PATH) as f: + info = json.load(f) + info["total_episodes"] = total_episodes + info["total_frames"] = total_frames + info["splits"] = {"train": f"0:{total_episodes}"} + with open(INFO_PATH, "w") as f: + json.dump(info, f, indent=4) + print(f"info.json updated: total_episodes={total_episodes} total_frames={total_frames}") + + +def main(): + os.chdir(ROOT) + rows = read_all_episode_meta() + print(f"Loaded {len(rows)} episode metadata rows") + + mapping, rows_sorted = build_mapping(rows) + print(f"Built mapping for {len(mapping)} unique (chunk, file, old_ep) triples") + + # Sanity preview + preview = [(r["chunk_index"], r["file_index"], r["episode_index"], mapping[(r["chunk_index"], r["file_index"], r["episode_index"])]["new_ep"]) for r in rows_sorted[:5]] + print("First 5 (chunk, file, old_ep, new_ep):", preview) + preview_end = [(r["chunk_index"], r["file_index"], r["episode_index"], mapping[(r["chunk_index"], r["file_index"], r["episode_index"])]["new_ep"]) for r in rows_sorted[-5:]] + print("Last 5 (chunk, file, old_ep, new_ep):", preview_end) + + total_frames = fix_data_files(mapping) + fix_meta_files(mapping) + update_info_json(total_episodes=len(mapping), total_frames=total_frames) + + +if __name__ == "__main__": + main() diff --git a/meta/episodes/chunk-000/file-000.parquet b/meta/episodes/chunk-000/file-000.parquet new file mode 100644 index 0000000000000000000000000000000000000000..71bcb4a4d4de0749ab108a068eed4b754567086e --- /dev/null +++ b/meta/episodes/chunk-000/file-000.parquet @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:896514f0912a59cf1a0d076ad436110f0be0ef79fdc310f7044ee8aa11c4a073 +size 65954 diff --git a/meta/episodes/chunk-000/file-001.parquet b/meta/episodes/chunk-000/file-001.parquet new file mode 100644 index 0000000000000000000000000000000000000000..5e5490990913a200c0b4759f7453fcf37ff55bf2 --- /dev/null +++ b/meta/episodes/chunk-000/file-001.parquet @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:ca03501e54ce4404d8a94d66f5f6d35ac9f29e8251932aa709516104bb4f8c46 +size 57490 diff --git a/meta/episodes/chunk-000/file-002.parquet b/meta/episodes/chunk-000/file-002.parquet 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