69 lines
2.2 KiB
Python
69 lines
2.2 KiB
Python
import cv2
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import pickle
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from pathlib import Path
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# TemporalTracker already saved the video chunks? No.
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# I will use fast_verify.py's frames but run process_pages directly and print all its output.
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import fast_verify
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from youtube_tab_to_pdf import extract_unique_scroll
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# Actually, I will just write a wrapper around ScoreExtractor to print to file
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import sys
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def main():
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cap = cv2.VideoCapture("output/サカナクション／新宝島(エレキギターTAB) 難易度★★★ sakanaction shintakarajima.mp4")
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# Quick dynamic crop
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ret, initial = cap.read()
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scale = 1280 / initial.shape[1]
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from youtube_tab_to_pdf import _find_white_tab_strip
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crop_top, crop_bottom = 0, int(initial.shape[0] * scale)
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cap.set(cv2.CAP_PROP_POS_FRAMES, 500)
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ret, check_frame = cap.read()
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if ret:
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resized_check = cv2.resize(check_frame, (1280, int(check_frame.shape[0] * scale)))
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bounds = _find_white_tab_strip(resized_check)
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if bounds:
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crop_top, crop_bottom = bounds
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cap.set(cv2.CAP_PROP_POS_FRAMES, 0)
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# We don't want to load ALL 15000 frames into memory. Use TemporalTracker directly!
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from video_cv_tracker import TemporalTracker
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tracker = TemporalTracker(diff_threshold=0.05)
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count = 0
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cap.set(cv2.CAP_PROP_POS_FRAMES, 0)
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while True:
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ret, frame = cap.read()
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if not ret: break
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if count % 4 == 0:
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resized = cv2.resize(frame, (1280, int(frame.shape[0] * scale)))
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tracker.process_frame(resized[crop_top:crop_bottom, :])
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count += 1
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unique_pages = tracker.get_unique_pages()
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print(f"Got {len(unique_pages)} unique pages from tracker.")
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from score_extractor import ScoreExtractor
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extractor = ScoreExtractor()
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# We will hook print
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original_print = print
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with open("score_log.txt", "w") as f:
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def my_print(*args, **kwargs):
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text = " ".join(map(str, args))
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f.write(text + "\n")
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original_print(*args, **kwargs)
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import builtins
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builtins.print = my_print
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extractor.process_pages(unique_pages)
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builtins.print = original_print
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if __name__ == "__main__":
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main()
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