denseworld-115k / reconstruct.py
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Metadata-only reconstruction release: sources + manifest + reconstruct.py (videos not redistributed)
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#!/usr/bin/env python3
"""
Reconstruct DENSEWORLD-115k clips from YouTube.
DENSEWORLD-115k is a METADATA-ONLY dataset. We do NOT redistribute the source videos:
they are downloaded from YouTube and remain under their creators' copyright. This script
re-downloads the 714 source videos listed in `sources.json` and regenerates the 115,687
clips deterministically, reproducing the exact pipeline used to build the dataset.
`data/data_prep/clip_durations.json` is the ground-truth manifest used for verification.
This file is dual-use: it is version-controlled in the FactorJEPA repo (src/hf_denseworld_115k/)
AND shipped verbatim as the root of the Hugging Face `denseworld-115k` dataset repo, so it is
intentionally self-contained (no repo imports; the pipeline constants below are inlined rather
than read from configs/pipeline.yaml, and mirror it exactly).
PIPELINE (identical to the DENSEWORLD-115k build; constants mirror configs/pipeline.yaml):
1. Download each source video at 480p (yt-dlp; pipeline.yaml data.download_resolution)
2. Detect scene boundaries (PySceneDetect ContentDetector, threshold=15.0)
3. Greedy-split into 4-10 s clips at scene boundaries (scene_detection.clip_{min,max}_duration)
4. Encode each clip (ffmpeg libx264 CRF 28, aac 128k, +faststart)
Output: <out>/<section>/<video_id>-<NNN>.mp4 (e.g. goa/walking/04YKvC8kAgI-000.mp4)
NOTE: 3 very long videos (see sources.json "chunked_videos") were originally processed in
fixed windows rather than whole-video scene detection; this script scene-detects them like the
rest, so their clip boundaries may differ slightly (<1% of the dataset). The verify step reports
any per-section clip-count mismatch against the manifest.
REQUIREMENTS:
pip install -r requirements.txt # yt-dlp, scenedetect[opencv]
ffmpeg + ffprobe on PATH # brew install ffmpeg / apt-get install ffmpeg
USAGE:
python reconstruct.py --out ./denseworld_clips # rebuild all 714 videos
python reconstruct.py --out ./denseworld_clips --limit 1 # smoke test: first video only
python reconstruct.py --out ./denseworld_clips --only 04YKvC8kAgI # one specific YouTube ID
python reconstruct.py --out ./denseworld_clips --verify-only # check existing clips vs manifest
"""
import argparse
import json
import subprocess
import sys
from pathlib import Path
# ---- pipeline constants (inlined; mirror configs/pipeline.yaml so this file runs standalone) ----
CLIP_MIN_DURATION = 4.0 # pipeline.yaml scene_detection.clip_min_duration
CLIP_MAX_DURATION = 10.0 # pipeline.yaml scene_detection.clip_max_duration
REENCODE_CRF = 28 # pipeline.yaml reencode_crf (libx264)
SCENE_THRESHOLD = 15.0 # PySceneDetect ContentDetector threshold
DOWNLOAD_RES = 480 # pipeline.yaml data.download_resolution (yt-dlp max height)
HERE = Path(__file__).resolve().parent
SOURCES_JSON = HERE / "sources.json"
MANIFEST_JSON = HERE / "data" / "data_prep" / "clip_durations.json"
def download_video(video_id: str, url: str, dst: Path, res: int = DOWNLOAD_RES) -> bool:
"""Download one YouTube video at <=res p (mp4). Returns True on success, False if unavailable."""
if dst.exists() and dst.stat().st_size > 0:
return True
fmt = (f"bestvideo[height<={res}][ext=mp4]+bestaudio[ext=m4a]/"
f"bestvideo[height<={res}]+bestaudio/best[height<={res}]/best")
cmd = ["yt-dlp", "-f", fmt, "-o", str(dst), "--merge-output-format", "mp4",
"--no-warnings", "--no-progress", url]
try:
r = subprocess.run(cmd, capture_output=True, text=True, timeout=1800)
if r.returncode != 0:
last = r.stderr.strip().splitlines()[-1] if r.stderr.strip() else "unknown error"
print(f" yt-dlp failed for {video_id}: {last}")
return dst.exists() and dst.stat().st_size > 0
except FileNotFoundError:
sys.exit("ERROR: yt-dlp not found. pip install yt-dlp")
except subprocess.TimeoutExpired:
print(f" yt-dlp timeout for {video_id}")
return False
def get_duration(path: Path) -> float:
"""Duration in seconds via ffprobe."""
cmd = ["ffprobe", "-v", "error", "-show_entries", "format=duration",
"-of", "default=noprint_wrappers=1:nokey=1", str(path)]
try:
out = subprocess.run(cmd, capture_output=True, text=True, timeout=60).stdout.strip()
return float(out) if out else 0.0
except (ValueError, subprocess.SubprocessError):
return 0.0
def detect_boundaries(path: Path, video_dur: float) -> list:
"""PySceneDetect ContentDetector(threshold=15) -> sorted interior boundary seconds."""
from scenedetect import open_video, SceneManager
from scenedetect.detectors import ContentDetector
video = open_video(str(path))
sm = SceneManager()
sm.add_detector(ContentDetector(threshold=SCENE_THRESHOLD))
sm.detect_scenes(video, show_progress=False)
boundaries = set()
for start, end in sm.get_scene_list():
for t in (start.get_seconds(), end.get_seconds()):
if 0 < t < video_dur:
boundaries.add(t)
return sorted(boundaries)
def greedy_split_plan(video_duration: float, boundaries: list,
min_dur: float, max_dur: float) -> list:
"""Verbatim from the build pipeline: contiguous [4,10]s greedy cut at scene boundaries."""
if video_duration <= 0:
return []
if video_duration <= max_dur:
return [(0.0, video_duration)]
clips, pos = [], 0.0
while pos < video_duration:
remaining = video_duration - pos
if remaining < min_dur:
if clips:
prev_start, _ = clips[-1]
clips[-1] = (prev_start, video_duration)
else:
clips.append((0.0, video_duration))
break
window_start, window_end = pos + min_dur, pos + max_dur
candidates = [x for x in boundaries if window_start <= x <= min(window_end, video_duration)]
cut = max(candidates) if candidates else min(window_end, video_duration)
if 0 < (video_duration - cut) < min_dur:
cut = video_duration
clips.append((pos, cut))
pos = cut
return clips
def encode_clip(src: Path, start: float, duration: float, dst: Path) -> bool:
"""Encode one clip: libx264 CRF 28, aac 128k, +faststart. -ss before -i for fast seek."""
cmd = ["ffmpeg", "-y", "-ss", str(start), "-i", str(src), "-t", str(duration),
"-c:v", "libx264", "-crf", str(REENCODE_CRF), "-preset", "medium",
"-c:a", "aac", "-b:a", "128k", "-movflags", "+faststart",
"-loglevel", "error", str(dst)]
try:
return subprocess.run(cmd, capture_output=True, timeout=120).returncode == 0 and dst.exists()
except subprocess.SubprocessError:
return False
def process_video(v: dict, out_root: Path, work: Path) -> int:
"""Download + scene-detect + split + encode one source video. Returns clip count."""
vid, url = v["id"], v["url"]
section = v["sections"][0] if v.get("sections") else "unsorted"
clip_dir = out_root / section
clip_dir.mkdir(parents=True, exist_ok=True)
src = work / f"{vid}.mp4"
print(f" [{vid}] downloading ({section}) ...")
if not download_video(vid, url, src):
print(f" [{vid}] SKIP (download failed / video unavailable)")
return 0
dur = get_duration(src)
boundaries = detect_boundaries(src, dur)
plan = greedy_split_plan(dur, boundaries, CLIP_MIN_DURATION, CLIP_MAX_DURATION)
n = 0
for i, (s, e) in enumerate(plan):
dst = clip_dir / f"{vid}-{i:03d}.mp4"
if dst.exists() and dst.stat().st_size > 0:
n += 1
continue
if encode_clip(src, s, e - s, dst):
n += 1
print(f" [{vid}] {n} clips (manifest expects {v['n_clips']})")
return n
def verify(out_root: Path, manifest: dict) -> None:
"""Compare on-disk clip counts to clip_durations.json per section."""
print("\n=== VERIFY vs clip_durations.json ===")
exp_total = manifest["summary"]["total_clips"]
got_total, mism = 0, 0
for section, sd in manifest["sections"].items():
expected = sum(len(c) for c in sd.get("videos", {}).values())
got = len(list((out_root / section).glob("*.mp4"))) if (out_root / section).exists() else 0
got_total += got
if got != expected:
mism += 1
if mism <= 20:
print(f" MISMATCH {section}: got {got}, expected {expected}")
print(f"\n total clips: got {got_total:,} / expected {exp_total:,} | section mismatches: {mism}")
def main() -> None:
ap = argparse.ArgumentParser(description="Reconstruct DENSEWORLD-115k clips from YouTube.")
ap.add_argument("--out", required=True, help="output root for reconstructed clips")
ap.add_argument("--work", default=None, help="scratch dir for source videos (default: <out>/_sources)")
ap.add_argument("--limit", type=int, default=0, help="process only the first N videos (smoke test)")
ap.add_argument("--only", default=None, help="process only this base YouTube ID")
ap.add_argument("--verify-only", action="store_true", help="only verify existing clips vs the manifest")
args = ap.parse_args()
out_root = Path(args.out)
manifest = json.load(open(MANIFEST_JSON))
if args.verify_only:
verify(out_root, manifest)
return
out_root.mkdir(parents=True, exist_ok=True)
work = Path(args.work) if args.work else out_root / "_sources"
work.mkdir(parents=True, exist_ok=True)
videos = json.load(open(SOURCES_JSON))["videos"]
if args.only:
videos = [v for v in videos if v["id"] == args.only]
if args.limit:
videos = videos[:args.limit]
print(f"Reconstructing {len(videos)} source video(s) -> {out_root}")
total = 0
for j, v in enumerate(videos, 1):
print(f"[{j}/{len(videos)}]")
total += process_video(v, out_root, work)
print(f"\nDONE: {total:,} clips reconstructed.")
verify(out_root, manifest)
if __name__ == "__main__":
main()