Ukawka
60 lines
2.4 KiB
Python
60 lines
2.4 KiB
Python
#!/usr/bin/env python3
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"""Prepare a reference for feature matching without changing its artwork."""
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import argparse
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from pathlib import Path
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from PIL import Image
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import numpy as np
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import cv2
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def prepare_rgba(image, white_threshold=240):
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"""Keep existing alpha; remove only border-connected near-white background.
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No crop or rescale here: semantic coordinates must retain the full canvas.
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White regions enclosed by character outlines are deliberately preserved.
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"""
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rgba = np.array(image.convert('RGBA'))
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alpha = rgba[:, :, 3]
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method = 'existing_alpha'
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removed = 0
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if not np.any(alpha == 0):
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white = np.all(rgba[:, :, :3] >= white_threshold, axis=2).astype(np.uint8)
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_, labels = cv2.connectedComponents(white, connectivity=4)
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border = np.unique(np.concatenate((labels[0], labels[-1], labels[:, 0], labels[:, -1])))
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background = np.isin(labels, border[border != 0])
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removed = int(background.sum())
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rgba[background, 3] = 0
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method = 'border_connected_white'
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foreground = rgba[:, :, 3] > 0
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if not foreground.any():
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raise ValueError('Reference has no foreground after background removal')
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if foreground.all():
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raise ValueError('No transparent background or border-connected white background; supply a cutout RGBA PNG')
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return Image.fromarray(rgba), {
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'method': method, 'white_threshold': white_threshold,
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'removed_pixels': removed, 'foreground_pixels': int(foreground.sum()),
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'width': image.width, 'height': image.height,
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'needs_review': method != 'existing_alpha',
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}
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def main():
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p = argparse.ArgumentParser()
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p.add_argument('--input', required=True)
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p.add_argument('--output', required=True)
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p.add_argument('--target', type=int, default=1024)
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p.add_argument('--remove-background', action='store_true')
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a = p.parse_args()
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im = Image.open(a.input).convert('RGBA')
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if a.remove_background:
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im, _ = prepare_rgba(im)
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longest = max(im.width, im.height)
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if longest < a.target:
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scale = a.target / longest
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size = (max(1, round(im.width * scale)), max(1, round(im.height * scale)))
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# Nearest-neighbour preserves pixel-art edges and transparency.
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im = im.resize(size, Image.Resampling.NEAREST)
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im.save(a.output)
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print(f'Reference prepared: {im.width}x{im.height}')
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if __name__ == '__main__': main()
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