cmounce
cdfce3a4f8
- Remove old dither code from dither.py - Commit an old color-distance experiment
51 lines
1.7 KiB
Python
51 lines
1.7 KiB
Python
# Playing with measuring color distances
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# Cleaned-up transcript from an ipython session, mostly experimental.
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# The actual compression algorithm probably won't use this.
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from dither import *
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def distance(x, y):
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return 2.5*((x[0]-y[0])/255)**2 + 4*((x[1]-y[1])/255)**2 + 2.5*((x[2]-y[2])/255)**2
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distances = {(i,j): distance(PICO_RGB[i],PICO_RGB[j]) for i in range(len(PICO_RGB)) for j in range(len(PICO_RGB))}
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def rect_distance_sum(img1, img2, xy1, xy2):
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"""Returns summed color distance of two images, using a rectangular mask"""
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result = 0.0
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x1, y1 = xy1
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x2, y2 = xy2
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for y in range(y1, y2):
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for x in range(x1, x2):
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c1 = img1.getpixel((x, y))
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c2 = img2.getpixel((x, y))
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result += distances[(c1, c2)]
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return result
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# d = dithered version of resized (peacock image, RGB color)
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d = pattern_dither(resized, PICO_RGB[:16], amount=1)
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# s = nearest-color image
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s = Image.new(size=d.size, mode='P', color=1)
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s.putpalette([c for rgb in PICO_RGB[:16] for c in rgb])
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def solid_cost(img, xy1, xy2, color):
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"""Returns cost of approximating a rectangular region with a solid color"""
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x1, y1 = xy1
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x2, y2 = xy2
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result = 0.0
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for y in range(y1, y2):
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for x in range(x1, x2):
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p = img.getpixel((x, y))
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result += distances[(color, p)]
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return result
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# Downsample the dithered image with a given size of rectangles
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skip = 2
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for y in range(0, 128, skip):
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for x in range(0, 128, skip):
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_, i = min( (solid_cost(d, (x,y), (x+skip,y+skip), c), c) for c in range(16) )
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for x2 in range(x, x + skip):
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for y2 in range(y, y + skip):
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s.putpixel((x2,y2), i)
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# s.show()
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