| """Cut SEMANTIX TED gesture clips from your own local copies of the 10 TED talks. |
| |
| SEMANTIX does not redistribute TED video (each row links to TED's official YouTube upload instead). |
| If you have obtained copies of the talks listed in data/ted_talks.csv from TED for your own |
| non-commercial research use, save each as <talk_dir>/<talk_id>.mp4 (e.g. t0001.mp4) and run: |
| |
| python scripts/extract_ted_clips.py --ted-csv data/ted.csv --talks-csv data/ted_talks.csv \ |
| --talk-dir /path/to/talks --out-dir ted_clips [--pad 0.0] |
| |
| Timestamps refer to the talk videos used to build the dataset (TED's official YouTube uploads, which |
| begin with TED's intro sequence). Their durations are listed in data/ted_talks.csv |
| (source_video_duration_sec); if your copy has a different duration, its timeline may be offset and |
| clips should be checked before use. |
| |
| Requires ffmpeg on PATH (or pass --ffmpeg). |
| """ |
|
|
| import argparse |
| import csv |
| import re |
| import subprocess |
| from pathlib import Path |
|
|
|
|
| def duration(ffmpeg: str, path: Path) -> float: |
| err = subprocess.run([ffmpeg, "-hide_banner", "-i", str(path)], capture_output=True, text=True).stderr |
| h, m, s = re.search(r"Duration: (\d+):(\d+):([\d.]+)", err).groups() |
| return int(h) * 3600 + int(m) * 60 + float(s) |
|
|
|
|
| def main() -> None: |
| parser = argparse.ArgumentParser(description="Cut SEMANTIX TED clips from local talk videos.") |
| parser.add_argument("--ted-csv", default="data/ted.csv") |
| parser.add_argument("--talks-csv", default="data/ted_talks.csv") |
| parser.add_argument("--talk-dir", required=True, help="Folder with t0001.mp4 ... t0010.mp4") |
| parser.add_argument("--out-dir", default="ted_clips") |
| parser.add_argument("--pad", type=float, default=0.0, help="Seconds of context added on each side") |
| parser.add_argument("--ffmpeg", default="ffmpeg") |
| args = parser.parse_args() |
|
|
| talk_dir, out_dir = Path(args.talk_dir), Path(args.out_dir) |
| out_dir.mkdir(parents=True, exist_ok=True) |
| with open(args.talks_csv, newline="", encoding="utf-8") as fh: |
| talks = {row["talk_id"]: row for row in csv.DictReader(fh)} |
|
|
| lengths = {} |
| for talk_id, talk in talks.items(): |
| path = talk_dir / f"{talk_id}.mp4" |
| if not path.exists(): |
| print(f"missing {path} ({talk['ted_url']}); its clips will be skipped") |
| continue |
| lengths[talk_id] = duration(args.ffmpeg, path) |
| expected = float(talk["source_video_duration_sec"]) |
| if abs(lengths[talk_id] - expected) > 1.0: |
| print(f"warning: {path} lasts {lengths[talk_id]:.1f}s, the dataset's source lasted {expected:.1f}s; " |
| "timestamps may be offset for this talk") |
|
|
| with open(args.ted_csv, newline="", encoding="utf-8") as fh: |
| rows = list(csv.DictReader(fh)) |
| done = 0 |
| for row in rows: |
| talk_id = row["talk_id"] |
| if talk_id not in lengths: |
| continue |
| start = max(0.0, float(row["start_sec"]) - args.pad) |
| end = min(lengths[talk_id], float(row["end_sec"]) + args.pad) |
| subprocess.run([ |
| args.ffmpeg, "-y", "-loglevel", "error", "-ss", f"{start:.3f}", "-i", str(talk_dir / f"{talk_id}.mp4"), |
| "-t", f"{end - start:.3f}", "-c:v", "libx264", "-crf", "18", "-c:a", "aac", |
| "-movflags", "+faststart", str(out_dir / f"{row['id']}.mp4"), |
| ], check=True) |
| done += 1 |
| print(f"wrote {done} clips to {out_dir}") |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
