ilia
6a78c84bcd
- capture/: frame sampling at configurable fps, ffmpeg audio extraction (WAV, whisper-ready) - vision/: changed-pixel motion scoring, stable/moving segmentation, contour + perspective document detection, Laplacian sharpness scoring, optional CLAHE enhancement - pipeline: two-pass detect (motion timeline, then best-frame crop per stable window) writing crops, debug frames, report.json, and motion_scores.csv - CLI: probe / detect / extract-audio subcommands - config.yaml with tunable thresholds; placeholder packages for events, transcribe, ocr, naming, pdf, review_cli - synthetic sample video generator + 16 unit tests
115 lines
3.7 KiB
Python
115 lines
3.7 KiB
Python
"""PaperPod command-line interface.
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Usage:
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python -m paperpod probe <video>
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python -m paperpod detect <video> [--out DIR] [--config config.yaml]
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python -m paperpod extract-audio <video> [--out FILE] [--config config.yaml]
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"""
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from __future__ import annotations
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import argparse
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import sys
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from pathlib import Path
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from paperpod.capture.audio import extract_audio
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from paperpod.capture.video import probe_video
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from paperpod.config import load_config
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from paperpod.pipeline import run_detection
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def _add_config_arg(parser: argparse.ArgumentParser) -> None:
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parser.add_argument(
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"--config",
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default=None,
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help="Path to config.yaml (defaults to ./config.yaml if present)",
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)
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def _resolve_config(arg: str | None):
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if arg is not None:
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return load_config(arg)
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default = Path("config.yaml")
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return load_config(default if default.exists() else None)
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def cmd_probe(args: argparse.Namespace) -> int:
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meta = probe_video(args.video)
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print(f"path: {meta.path}")
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print(f"fps: {meta.fps:.3f}")
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print(f"frames: {meta.frame_count}")
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print(f"duration: {meta.duration_s:.2f}s")
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print(f"size: {meta.width}x{meta.height}")
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return 0
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def cmd_detect(args: argparse.Namespace) -> int:
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cfg = _resolve_config(args.config)
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out_dir = Path(args.out or Path(cfg.output.dir) / Path(args.video).stem)
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print(f"Analyzing {args.video} -> {out_dir}")
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report = run_detection(args.video, cfg, out_dir)
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windows = report["stable_windows"]
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found = [w for w in windows if w["document_found"]]
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print(f"\nVideo: {report['video_meta']['duration_s']}s, "
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f"{len(report['motion_events'])} motion events, "
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f"{len(windows)} stable windows, "
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f"{len(found)} documents detected\n")
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header = f"{'win':>3} {'start':>7} {'end':>7} {'sharp':>8} {'doc':>4} crop"
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print(header)
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print("-" * len(header))
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for w in windows:
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print(
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f"{w['window_id']:>3} "
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f"{w['t_start']:>7.2f} "
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f"{w['t_end']:>7.2f} "
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f"{w.get('sharpness', 0):>8.1f} "
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f"{'yes' if w['document_found'] else 'no':>4} "
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f"{w.get('crop_path', '-')}"
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)
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print(f"\nFull report: {out_dir / 'report.json'}")
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print(f"Motion scores (for threshold tuning): {out_dir / 'motion_scores.csv'}")
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return 0
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def cmd_extract_audio(args: argparse.Namespace) -> int:
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cfg = _resolve_config(args.config)
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out = Path(args.out or Path(cfg.output.dir) / (Path(args.video).stem + ".wav"))
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wav = extract_audio(args.video, out, sample_rate=cfg.audio.sample_rate)
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print(f"Audio written to {wav}")
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return 0
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def main(argv: list[str] | None = None) -> int:
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parser = argparse.ArgumentParser(
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prog="paperpod",
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description="Convert an overhead video of documents into cropped, named PDFs.",
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)
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sub = parser.add_subparsers(dest="command", required=True)
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p_probe = sub.add_parser("probe", help="Print video metadata")
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p_probe.add_argument("video")
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p_probe.set_defaults(func=cmd_probe)
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p_detect = sub.add_parser(
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"detect", help="Detect stable windows and document candidates"
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)
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p_detect.add_argument("video")
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p_detect.add_argument("--out", default=None, help="Output directory")
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_add_config_arg(p_detect)
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p_detect.set_defaults(func=cmd_detect)
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p_audio = sub.add_parser("extract-audio", help="Extract audio track as WAV")
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p_audio.add_argument("video")
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p_audio.add_argument("--out", default=None, help="Output WAV path")
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_add_config_arg(p_audio)
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p_audio.set_defaults(func=cmd_extract_audio)
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args = parser.parse_args(argv)
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return args.func(args)
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if __name__ == "__main__":
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sys.exit(main())
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