98381d2893
- HSV-aware _trim_to_content (white ratio 30-97%) - pHash cluster dedup: dHash 32x32(1024bit), max_hamming=20 - Panoramic stitching: template matching scroll offset detection - 4-stage pipeline: MSE -> Panorama -> pHash - 1080p download priority + MAX_FRAME_WIDTH=1280 cap - test_pipeline.py with YouTube URLs and --download mode - 3 new known-issues documented - devlog + STATUS.md updated
34 lines
1.1 KiB
Python
34 lines
1.1 KiB
Python
"""원본 프레임 덤프 — 각 영상에서 5개 프레임을 랜덤 추출"""
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import sys
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if sys.platform == "win32":
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sys.stdout.reconfigure(encoding="utf-8", errors="replace")
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import cv2
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import numpy as np
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from pathlib import Path
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output = Path("output")
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dump_dir = output / "raw_dump"
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dump_dir.mkdir(exist_ok=True)
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mp4s = sorted(output.glob("*.mp4"))
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for vi, mp4 in enumerate(mp4s):
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cap = cv2.VideoCapture(str(mp4))
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total = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
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fps = cap.get(cv2.CAP_PROP_FPS)
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w = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
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h = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
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print(f"Video {vi+1}: {mp4.name[:30]}... ({w}x{h}, {fps:.0f}fps, {total} frames)")
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# 균등 간격으로 5개 프레임
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indices = np.linspace(total * 0.1, total * 0.9, 5, dtype=int)
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for i, idx in enumerate(indices):
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cap.set(cv2.CAP_PROP_POS_FRAMES, idx)
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ret, frame = cap.read()
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if ret:
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path = dump_dir / f"v{vi+1}_raw_{i}.png"
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cv2.imwrite(str(path), frame)
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print(f" frame {idx} → {path.name} ({frame.shape})")
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cap.release()
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print(f"\n덤프 완료: {dump_dir}")
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