53 lines
1.8 KiB
Python
53 lines
1.8 KiB
Python
import cv2
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import numpy as np
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def find_white_tab_bounds(video_path):
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cap = cv2.VideoCapture(video_path)
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cap.set(cv2.CAP_PROP_POS_FRAMES, 30 * cap.get(cv2.CAP_PROP_FPS))
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ret, frame = cap.read()
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cap.release()
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if not ret: return None
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scale = 1280 / frame.shape[1]
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frame = cv2.resize(frame, (1280, int(frame.shape[0] * scale)))
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gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
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# Calculate row-wise mean brightness
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row_means = np.mean(gray, axis=1)
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# We are looking for the white paper background which has brightness > 230 on average
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# Wait, notes and black lines reduce the mean of a row.
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# A single black horizontal line on white reduces mean by (255 - 0) * (width/width) -> It drops to ~180 if it's thick.
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# Let's say any row with mean > 180 is part of the white strip.
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is_white_row = row_means > 180
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# Find contiguous blocks of True
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# Pad with False to handle edges cleanly
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padded = np.concatenate(([False], is_white_row, [False]))
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diffs = np.diff(padded.astype(int))
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starts = np.where(diffs == 1)[0]
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ends = np.where(diffs == -1)[0]
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best_start, best_end, max_len = 0, 0, 0
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for s, e in zip(starts, ends):
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length = e - s
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if length > max_len:
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max_len = length
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best_start = s
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best_end = e
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return best_start, best_end, frame.shape[0]
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if __name__ == "__main__":
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video_path = "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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bounds = find_white_tab_bounds(video_path)
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if bounds:
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s, e, h = bounds
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print(f"Mathematically found White Tab Strip: Y_START={s}, Y_END={e}. Total Height={h}")
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else:
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print("Failed to find bound")
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