improved cut detection
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0f482ac8c4
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afa51f7971
1 changed files with 16 additions and 12 deletions
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@ -329,17 +329,21 @@ def average_color(prefix, start=0, end=0):
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color = list(map(float, color))
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return ox.image.getHSL(color)
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def average_volume(prefix, start=0, end=0):
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#FIXME: actually compute volume
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return 0
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def get_distance(rgb0, rgb1):
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# rgb distance, normalized so that black/white equals 1
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dst = math.sqrt(pow(rgb0[0] - rgb1[0], 2) + pow(rgb0[1] - rgb1[1], 2) + pow(rgb0[2] - rgb1[2], 2))
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return dst / math.sqrt(3 * pow(255, 2))
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def cuts(prefix):
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cuts = []
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distances = [0]
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fps = 25
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frames = 0
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height = 64
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@ -350,19 +354,19 @@ def cuts(prefix):
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timeline = Image.open(image)
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frames += timeline.size[0]
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pixels.append(timeline.load())
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for frame in range(0, frames):
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for frame in range(1, frames):
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x = frame % width
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if frame > 0:
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dst = 0
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image0 = int((frame - 1) / width)
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image1 = int(frame / width)
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for y in range(0, height):
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rgb0 = pixels[image0][(x - 1) % width, y]
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rgb1 = pixels[image1][x, y]
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dst += get_distance(rgb0, rgb1) / height
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#print frame / fps, dst
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if dst > 0.1:
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cuts.append(frame / fps)
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distance = 0
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image0 = int((frame - 1) / width)
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image1 = int(frame / width)
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for y in range(height):
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rgb0 = pixels[image0][(x - 1) % width, y]
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rgb1 = pixels[image1][x, y]
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distance += get_distance(rgb0, rgb1)
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distances.append(distance / height)
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for frame in range(1, frames):
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if distances[frame] >= 0.025 and abs(distances[frame] - distances[frame - 1]) >= 0.05:
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cuts.append(frame / fps)
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return cuts
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