diff --git a/README.md b/README.md index 68480b9cfaedb828e3ec03f0a51aeac1cdc388ae..efc9d4e6403d11f19331ea8ade06eab36b50878f 100644 --- a/README.md +++ b/README.md @@ -22,53 +22,57 @@ A benchmark for evaluating 3D point motion in video, covering egocentric and thi Benchmark data provided in this repository include annotations, captions, indices, and scripts created by Ai2 that correspond to the source datasets. -```bash -# pip install huggingface_hub -# If the download stalls near completion: HF_HUB_DISABLE_XET=1 huggingface-cli download ... -huggingface-cli download allenai/PointMotionBench \ - --repo-type dataset --local-dir $POINTMOTIONBENCH_ROOT -``` - ---- - -### Step 2 — DAVIS: Download Videos -DAVIS videos should be reconstructed from the source data at the [official source](https://davischallenge.org/davis2017/code.html). Download **Trainval 2017 - Images (480p)** and **Annotations**, then convert frames to mp4 (requires `ffmpeg`): - -```bash -python davis/reconstruct_davis.py \ - --davis-root /path/to/DAVIS \ - --output-dir davis/videos/input_480p +```python +# pip install huggingface_hub +# If the download stalls near completion: HF_HUB_DISABLE_XET=1 python your_script.py +from huggingface_hub import snapshot_download +snapshot_download( + repo_id="allenai/PointMotionBench", + repo_type="dataset", + local_dir=".", +) ``` --- -### Step 3 — HOT3D: Download Videos +### Step 2 — HOT3D: Download Videos -HOT3D videos should be reconstructed from the source data at [bop-benchmark/hot3d](https://huggingface.co/datasets/bop-benchmark/hot3d) (HuggingFace). +We do not share videos from HOT3D. Users should access the videos from the source dataset at [bop-benchmark/hot3d](https://huggingface.co/datasets/bop-benchmark/hot3d) (HuggingFace). -**Requirements:** `huggingface_hub`, `imageio[ffmpeg]`, `imageio-ffmpeg`, `opencv-python-headless`, `numpy` +**Requirements:** `imageio[ffmpeg]`, `imageio-ffmpeg`, `opencv-python-headless`, `numpy` ```bash -python hot3d/reconstruct_hot3d.py \ - --workdir /path/to/hot3d_work \ - --output-dir hot3d/rgbs +# 1. download train_aria TARs (~1,516 clips) +# to download only the 1,272 clips needed for PointMotionBench, add: +# --captions hot3d/hot3d_annotations.json +python hot3d/download_train_aria.py --output /path/to/train_aria + +# 2. extract undistorted upright RGB videos (one mp4 per TAR) +python hot3d/extract_rgbs.py \ + --clips_dir /path/to/train_aria \ + --output_dir /path/to/rgbs + +# 3. trim to PointMotionBench windows +python hot3d/trim_hot3d_clips.py \ + --src_dir /path/to/rgbs \ + --captions hot3d/hot3d_annotations.json \ + --output_dir hot3d/videos ``` -This runs all three stages (download TARs → extract RGB → trim to PointMotionBench windows). -For large-scale extraction, run the three scripts individually — `extract_rgbs.py` supports sharding: +For large-scale extraction, `extract_rgbs.py` supports sharding: ```bash python hot3d/extract_rgbs.py \ - --clips_dir /path/to/hot3d_work/train_aria \ - --output_dir /path/to/hot3d_work/rgbs \ + --clips_dir /path/to/train_aria \ + --output_dir /path/to/rgbs \ --shard_idx 0 \ --num_shards 8 ``` --- -### Step 4 — WorldTrack: Reconstruct Clips +### Step 3 — WorldTrack: extract clips Download the WorldTrack source data (WorldTrack benchmark, introduced in St4RTrack, Feng et al., ICCV 2025 — dataset download available at [HavenFeng/St4RTrack](https://github.com/HavenFeng/St4RTrack)). The source data should have this layout: @@ -83,7 +87,7 @@ WorldTrack/ Then extract PointMotionBench clips using the index map from Step 1: ```bash -python worldtrack/reconstruct_worldtrack.py \ +python worldtrack/extract_worldtrack_clips.py \ --index_map worldtrack/worldtrack_index_map.json \ --src_dir /path/to/WorldTrack \ --output_dir worldtrack @@ -107,16 +111,3 @@ Such videos and data are provided by the owners of the source datasets above, an license terms and use restrictions. Users who access videos and data from these sources are responsible for reviewing and confirming that their use complies with the terms and conditions. -## Citation - -```bibtex -@misc{zhang2026molmomotionforecastingpointtrajectories, - title={MolmoMotion: Forecasting Point Trajectories in 3D with Language Instruction}, - author={Jianing Zhang and Chenhao Zheng and Yajun Yang and Max Argus and Rustin Soraki and Winson Han and Taira Anderson and Chun-Liang Li and Shuo Liu and Jiafei Duan and Zhongzheng Ren and Jieyu Zhang and Ranjay Krishna}, - year={2026}, - eprint={2606.18558}, - archivePrefix={arXiv}, - primaryClass={cs.CV}, - url={https://arxiv.org/abs/2606.18558}, -} -``` \ No newline at end of file diff --git a/davis/reconstruct_davis.py b/davis/reconstruct_davis.py deleted file mode 100644 index 7223de6abd582b8547828ced0d9211066f3a244f..0000000000000000000000000000000000000000 --- a/davis/reconstruct_davis.py +++ /dev/null @@ -1,141 +0,0 @@ -#!/usr/bin/env python3 -""" -Reconstruct DAVIS PointMotionBench videos from DAVIS 2017 Trainval frames. - -Download Trainval 2017 - Images (480p) and Annotations from -https://davischallenge.org/davis2017/code.html, then run this script. - -The DAVIS root should have this layout after extraction: - / - └── JPEGImages/ - └── 480p/ - └── / - ├── 00000.jpg - ├── 00001.jpg - └── ... - -Example: - python davis/reconstruct_davis.py \ - --davis-root /path/to/DAVIS \ - --output-dir davis/videos/input_480p \ - --captions davis/davis_captions.json -""" - -import argparse -import json -import os -import shutil -import subprocess -import sys -from pathlib import Path - -TARGET_FPS = 24 - - -def ffmpeg_exe(): - if shutil.which("ffmpeg"): - return "ffmpeg" - try: - import imageio_ffmpeg - return imageio_ffmpeg.get_ffmpeg_exe() - except Exception: - raise RuntimeError( - "ffmpeg not found; install a system ffmpeg or `pip install imageio-ffmpeg`." - ) - - -def encode_sequence(ffmpeg, frames_dir, dst, fps): - frames = sorted(frames_dir.glob("*.jpg")) - if not frames: - raise RuntimeError(f"no .jpg frames found in {frames_dir}") - - dst.parent.mkdir(parents=True, exist_ok=True) - tmp = dst.with_suffix(".tmp.mp4") - cmd = [ - ffmpeg, "-y", "-loglevel", "error", - "-framerate", str(fps), - "-i", str(frames_dir / "%05d.jpg"), - "-vf", "crop=trunc(iw/2)*2:trunc(ih/2)*2", - "-c:v", "libx264", "-crf", "18", "-preset", "fast", - "-pix_fmt", "yuv420p", "-an", - str(tmp), - ] - res = subprocess.run(cmd, capture_output=True) - if res.returncode != 0: - if tmp.exists(): - tmp.unlink() - raise RuntimeError(res.stderr.decode(errors="replace").strip() or "ffmpeg failed") - os.replace(tmp, dst) - - -def main(): - parser = argparse.ArgumentParser( - description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter - ) - parser.add_argument( - "--davis-root", required=True, type=Path, - help="DAVIS 2017 root dir containing JPEGImages/480p/" - ) - parser.add_argument( - "--output-dir", type=Path, - default=Path(__file__).resolve().parent / "videos" / "input_480p", - help="Output directory for mp4 files (default: davis/videos/input_480p/)", - ) - parser.add_argument( - "--captions", type=Path, - default=Path(__file__).resolve().parent / "davis_captions.json", - help="davis_captions.json (default: alongside this script)", - ) - parser.add_argument("--fps", type=int, default=TARGET_FPS) - parser.add_argument("--overwrite", action="store_true", help="Re-encode even if output exists") - args = parser.parse_args() - - frames_root = args.davis_root / "JPEGImages" / "480p" - if not frames_root.exists(): - print(f"ERROR: {frames_root} does not exist — check --davis-root points to the DAVIS 2017 root.") - sys.exit(1) - - captions = json.load(open(args.captions)) - sequences = sorted(captions.keys()) - args.output_dir.mkdir(parents=True, exist_ok=True) - ffmpeg = ffmpeg_exe() - - print(f"[reconstruct] {len(sequences)} sequences | davis-root={args.davis_root} | out={args.output_dir}") - - done = skipped = failed = 0 - missing = [] - - for i, seq in enumerate(sequences, 1): - dst = args.output_dir / f"{seq}.mp4" - if dst.exists() and not args.overwrite: - skipped += 1 - continue - - frames_dir = frames_root / seq - if not frames_dir.exists(): - missing.append(seq) - print(f"[{i}/{len(sequences)}] MISSING {seq}") - failed += 1 - continue - - try: - encode_sequence(ffmpeg, frames_dir, dst, args.fps) - print(f"[{i}/{len(sequences)}] OK {seq}") - done += 1 - except Exception as e: - print(f"[{i}/{len(sequences)}] ERROR {seq}: {e}") - failed += 1 - - print(f"\n===== summary =====") - print(f"encoded ok : {done}") - print(f"skipped (exists) : {skipped}") - print(f"missing upstream : {len(missing)}") - print(f"failed : {failed}") - for seq in missing[:20]: - print(f" [MISSING] {seq}") - if missing or failed: - sys.exit(1) - - -if __name__ == "__main__": - main() diff --git a/davis/videos/input_480p/bear.mp4 b/davis/videos/input_480p/bear.mp4 new file mode 100644 index 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b/davis/videos/vipe_rgb/tractor-sand.mp4 new file mode 100644 index 0000000000000000000000000000000000000000..5f92db4c4eedb7364d099716a946a41f7f54e6c4 --- /dev/null +++ b/davis/videos/vipe_rgb/tractor-sand.mp4 @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:39181d7f927113e4874f58f3feb5e3ed09c162b0f665bcc32dd8ea4fcd319e09 +size 486006 diff --git a/davis/videos/vipe_rgb/train.mp4 b/davis/videos/vipe_rgb/train.mp4 new file mode 100644 index 0000000000000000000000000000000000000000..44cca477805d56841c9cebafca7db421a35b8a65 --- /dev/null +++ b/davis/videos/vipe_rgb/train.mp4 @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:efb8a09e8d6395c014224057f10855708ad2b21d39f27844daf79325d6c3ee0c +size 819613 diff --git a/davis/videos/vipe_rgb/tuk-tuk.mp4 b/davis/videos/vipe_rgb/tuk-tuk.mp4 new file mode 100644 index 0000000000000000000000000000000000000000..fc9369bafeadfdf5aacacca3e10825ad149a9dd2 --- /dev/null +++ b/davis/videos/vipe_rgb/tuk-tuk.mp4 @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:369d82ce35f7fb892576d91c0f32fcd61d48803d4dbf657ae59907d589177051 +size 969322 diff --git a/davis/videos/vipe_rgb/upside-down.mp4 b/davis/videos/vipe_rgb/upside-down.mp4 new file mode 100644 index 0000000000000000000000000000000000000000..7c50c20f4213348d654f7afb8f92aa1cf9bc3d0f --- /dev/null +++ b/davis/videos/vipe_rgb/upside-down.mp4 @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e391b7b7981e658b2941ab816c0dd8f39addeaaacd2944e76284cdd6ad829df8 +size 1010652 diff --git a/davis/videos/vipe_rgb/varanus-cage.mp4 b/davis/videos/vipe_rgb/varanus-cage.mp4 new file mode 100644 index 0000000000000000000000000000000000000000..29f6f1093dddc99c8a31d37e79315da91b076eb0 --- /dev/null +++ b/davis/videos/vipe_rgb/varanus-cage.mp4 @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:36f5d5a1224ac9220b1ba4b83b22828232cc12e564447caad6cbcfa5d7df9ac4 +size 674268 diff --git a/davis/videos/vipe_rgb/walking.mp4 b/davis/videos/vipe_rgb/walking.mp4 new file mode 100644 index 0000000000000000000000000000000000000000..af7b8207339c69bcdeb60deed8de031cc471289b --- /dev/null +++ b/davis/videos/vipe_rgb/walking.mp4 @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:72b81e61ff58f827e7820c73c9a496e3966a095674d3f3a186ae23c8df97a8bc +size 932316 diff --git a/hot3d/reconstruct_hot3d.py b/hot3d/reconstruct_hot3d.py deleted file mode 100644 index 88ad68047ee75901958b9368ac4c4940fdbd3446..0000000000000000000000000000000000000000 --- a/hot3d/reconstruct_hot3d.py +++ /dev/null @@ -1,106 +0,0 @@ -#!/usr/bin/env python3 -""" -Reconstruct HOT3D PointMotionBench videos in one step. - -Runs all three stages sequentially: - 1. Download train_aria TARs from bop-benchmark/hot3d (HuggingFace) - 2. Extract undistorted RGB videos from each TAR - 3. Trim to PointMotionBench frame windows - -Requirements: huggingface_hub, imageio[ffmpeg], imageio-ffmpeg, opencv-python-headless, numpy - -Usage: - python hot3d/reconstruct_hot3d.py \ - --workdir /path/to/hot3d_work \ - --output-dir hot3d/rgbs - - # Pass a HuggingFace token if the dataset is gated: - --token hf_... - - # Resume a partial run (skip steps already completed): - --skip-download # TARs already in /train_aria/ - --skip-extract # RGB videos already in /rgbs/ -""" - -import argparse -import subprocess -import sys -from pathlib import Path - -SCRIPTS_DIR = Path(__file__).resolve().parent - - -def run_step(script_name, *args): - cmd = [sys.executable, str(SCRIPTS_DIR / script_name), *args] - print(f"\n{'=' * 60}") - print(f"[reconstruct_hot3d] {script_name}") - print(f"{'=' * 60}") - result = subprocess.run(cmd) - if result.returncode != 0: - print(f"\nERROR: {script_name} exited with code {result.returncode}") - sys.exit(result.returncode) - - -def main(): - parser = argparse.ArgumentParser( - description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter - ) - parser.add_argument( - "--workdir", required=True, type=Path, - help="Working directory for intermediate files (TARs and full RGB videos)", - ) - parser.add_argument( - "--output-dir", type=Path, - default=Path(__file__).resolve().parent / "rgbs", - help="Output directory for final trimmed clips (default: hot3d/rgbs/)", - ) - parser.add_argument( - "--captions", type=Path, - default=Path(__file__).resolve().parent / "hot3d_annotations.json", - help="hot3d_annotations.json (default: alongside this script)", - ) - parser.add_argument( - "--token", default=None, - help="HuggingFace access token for bop-benchmark/hot3d (if gated)", - ) - parser.add_argument( - "--skip-download", action="store_true", - help="Skip step 1 — TARs already in /train_aria/", - ) - parser.add_argument( - "--skip-extract", action="store_true", - help="Skip step 2 — RGB videos already in /rgbs/", - ) - args = parser.parse_args() - - train_aria_dir = args.workdir / "train_aria" - rgbs_dir = args.workdir / "rgbs" - - if not args.skip_download: - download_args = [ - "--output", str(train_aria_dir), - "--captions", str(args.captions), - ] - if args.token: - download_args += ["--token", args.token] - run_step("download_train_aria.py", *download_args) - - if not args.skip_extract: - run_step( - "extract_rgbs.py", - "--clips_dir", str(train_aria_dir), - "--output_dir", str(rgbs_dir), - ) - - run_step( - "trim_hot3d_clips.py", - "--src_dir", str(rgbs_dir), - "--captions", str(args.captions), - "--output_dir", str(args.output_dir), - ) - - print(f"\n[reconstruct_hot3d] Done. Clips written to {args.output_dir}") - - -if __name__ == "__main__": - main() diff --git a/hot3d/trim_hot3d_clips.py b/hot3d/trim_hot3d_clips.py index c3bf97c622bb57baeeec8fdb81ea56258c0d6694..7d0180ea1e992e4b0b6281f13bbd093bc54f7ed7 100644 --- a/hot3d/trim_hot3d_clips.py +++ b/hot3d/trim_hot3d_clips.py @@ -15,7 +15,7 @@ Usage: python hot3d/trim_hot3d_clips.py \ --src_dir /path/to/rgbs \ --captions hot3d/hot3d_annotations.json \ - --output_dir hot3d/rgbs + --output_dir hot3d/videos Dependencies: imageio[ffmpeg] (pip install imageio[ffmpeg]) """ @@ -67,8 +67,8 @@ def main(): help='Directory containing clip-NNNNNN_rgb.mp4 source files') parser.add_argument('--captions', default=str(Path(__file__).parent / 'hot3d_annotations.json'), help='Path to hot3d_annotations.json (default: alongside this script)') - parser.add_argument('--output_dir', default=str(Path(__file__).parent / 'rgbs'), - help='Output directory for trimmed video clips (default: hot3d/rgbs/)') + parser.add_argument('--output_dir', default=str(Path(__file__).parent / 'videos'), + help='Output directory for trimmed video clips (default: ./videos/ alongside this script)') parser.add_argument('--clip_ids', default=None, help='Comma-separated PMB clip IDs to process (default: all)') args = parser.parse_args() diff --git a/worldtrack/reconstruct_worldtrack.py b/worldtrack/extract_worldtrack_clips.py similarity index 98% rename from worldtrack/reconstruct_worldtrack.py rename to worldtrack/extract_worldtrack_clips.py index 83016d724011ffd52456dbf4bca36d9abb5dcd73..2eae98aed9307873780395a5c47cd6ffeee4622b 100644 --- a/worldtrack/reconstruct_worldtrack.py +++ b/worldtrack/extract_worldtrack_clips.py @@ -1,5 +1,5 @@ """ -reconstruct_worldtrack.py +extract_worldtrack_clips.py Reconstructs the PointMotionBench worldtrack clips from the original WorldTrack source NPZs, using the index map (worldtrack_index_map.json). @@ -13,7 +13,7 @@ Output: written to: ///.npz Usage: - python worldtrack/reconstruct_worldtrack.py \ + python worldtrack/extract_worldtrack_clips.py \ --index_map worldtrack/worldtrack_index_map.json \ --src_dir /path/to/WorldTrack \ --output_dir worldtrack