62 lines
3.7 KiB
Python
62 lines
3.7 KiB
Python
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"""Prepare real CPU-decoded media candidates after verifying frozen labels.
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No generated captions, placeholder vectors, or model calls occur in preparation.
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"""
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import argparse
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import hashlib
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import json
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from pathlib import Path
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import subprocess
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def verify(root):
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fixture_path = root / "fixture.json"
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lock = json.loads((root / "labels.lock.json").read_text())
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assert hashlib.sha256(fixture_path.read_bytes()).hexdigest() == lock["fixture_sha256"], "Frozen labels changed"
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fixture = json.loads(fixture_path.read_text(encoding="utf-8"))
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for asset in fixture["assets"]:
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path = (root / asset["path"]).resolve()
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assert path.is_relative_to(root.resolve()), "Asset escaped corpus root"
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assert path.stat().st_size == asset["bytes"], asset["id"]
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assert hashlib.sha256(path.read_bytes()).hexdigest() == asset["sha256"], asset["id"]
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return fixture
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def main():
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parser = argparse.ArgumentParser()
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parser.add_argument("--root", type=Path, default=Path("fixtures/media"))
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parser.add_argument("--ffmpeg", type=Path, required=True)
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parser.add_argument("--ffprobe", type=Path, required=True)
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args = parser.parse_args()
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root = args.root.resolve()
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fixture = verify(root)
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derived = root / "derived"
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derived.mkdir(exist_ok=True)
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candidates = []
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for asset in fixture["assets"]:
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source = root / asset["path"]
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if asset["kind"] == "image":
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candidates.append(dict(asset=asset["id"], path=str(source), modality="image", token_budget=140))
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continue
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probe = json.loads(subprocess.check_output([str(args.ffprobe), "-v", "error", "-show_format", "-show_streams", "-of", "json", str(source)], text=True))
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duration = float(probe["format"]["duration"])
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if asset["kind"] == "video":
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for stamp in range(0, int(duration) + 1, 2):
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output = derived / f"{asset['id']}-frame-{stamp:04}.png"
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subprocess.run([str(args.ffmpeg), "-hide_banner", "-loglevel", "error", "-hwaccel", "none", "-threads", "1", "-ss", str(stamp), "-i", str(source), "-frames:v", "1", "-vf", "scale=480:-1", "-threads", "1", "-y", str(output)], check=True)
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if output.is_file():
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candidates.append(dict(asset=asset["id"], path=str(output), modality="image", token_budget=70, start_s=stamp, end_s=min(stamp + 2, duration)))
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if any(stream["codec_type"] == "audio" for stream in probe["streams"]):
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for stamp in range(0, int(duration) + 1, 30):
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output = derived / f"{asset['id']}-audio-{stamp:04}.f32"
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subprocess.run([str(args.ffmpeg), "-hide_banner", "-loglevel", "error", "-hwaccel", "none", "-threads", "1", "-ss", str(stamp), "-i", str(source), "-t", "30", "-vn", "-ac", "1", "-ar", "16000", "-f", "f32le", "-threads", "1", "-y", str(output)], check=True)
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if output.stat().st_size:
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assert output.stat().st_size <= 480000 * 4, "Audio exceeds worker budget"
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candidates.append(dict(asset=asset["id"], path=str(output), modality="audio", start_s=stamp, end_s=min(stamp + 30, duration)))
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manifest = dict(fixture_sha256=hashlib.sha256((root / "fixture.json").read_bytes()).hexdigest(), ffmpeg_version=subprocess.check_output([str(args.ffmpeg), "-version"], text=True).splitlines()[0], policy="CPU-only dense reference: photos140/video70 tokens, uniform2s frames, mono16kHz30s PCM", candidates=candidates)
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(derived / "candidates.json").write_text(json.dumps(manifest, indent=2), encoding="utf-8")
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print(json.dumps(dict(candidates=len(candidates), images=sum(item["modality"] == "image" for item in candidates), audio=sum(item["modality"] == "audio" for item in candidates))))
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if __name__ == "__main__":
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main()
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