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83 lines
2.8 KiB
Python
83 lines
2.8 KiB
Python
from tester import *
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from PIL import Image
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def test_extent():
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im = lena('RGB')
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(w,h) = im.size
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transformed = im.transform(im.size, Image.EXTENT,
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(0,0,
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w//2,h//2), # ul -> lr
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Image.BILINEAR)
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scaled = im.resize((w*2, h*2), Image.BILINEAR).crop((0,0,w,h))
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assert_image_similar(transformed, scaled, 10) # undone -- precision?
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def test_quad():
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# one simple quad transform, equivalent to scale & crop upper left quad
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im = lena('RGB')
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(w,h) = im.size
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transformed = im.transform(im.size, Image.QUAD,
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(0,0,0,h//2,
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w//2,h//2,w//2,0), # ul -> ccw around quad
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Image.BILINEAR)
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scaled = im.resize((w*2, h*2), Image.BILINEAR).crop((0,0,w,h))
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assert_image_equal(transformed, scaled)
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def test_mesh():
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# this should be a checkerboard of halfsized lenas in ul, lr
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im = lena('RGBA')
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(w,h) = im.size
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transformed = im.transform(im.size, Image.MESH,
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[((0,0,w//2,h//2), # box
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(0,0,0,h,
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w,h,w,0)), # ul -> ccw around quad
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((w//2,h//2,w,h), # box
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(0,0,0,h,
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w,h,w,0))], # ul -> ccw around quad
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Image.BILINEAR)
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#transformed.save('transformed.png')
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scaled = im.resize((w//2, h//2), Image.BILINEAR)
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checker = Image.new('RGBA', im.size)
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checker.paste(scaled, (0,0))
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checker.paste(scaled, (w//2,h//2))
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assert_image_equal(transformed, checker)
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# now, check to see that the extra area is (0,0,0,0)
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blank = Image.new('RGBA', (w//2,h//2), (0,0,0,0))
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assert_image_equal(blank, transformed.crop((w//2,0,w,h//2)))
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assert_image_equal(blank, transformed.crop((0,h//2,w//2,h)))
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def test_blank_fill():
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# attempting to hit
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# https://github.com/python-imaging/Pillow/issues/254 reported
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#
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# issue is that transforms with transparent overflow area
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# contained junk from previous images, especially on systems with
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# constrained memory. So, attempt to fill up memory with a
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# pattern, free it, and then run the mesh test again. Using a 1Mp
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# image with 4 bands, for 4 megs of data allocated, x 64. OMM (64
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# bit 12.04 VM with 512 megs available, this fails with Pillow <
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# a0eaf06cc5f62a6fb6de556989ac1014ff3348ea
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#
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# Running by default, but I'd totally understand not doing it in
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# the future
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foo = [Image.new('RGBA',(1024,1024), (a,a,a,a))
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for a in range(1,65)]
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# Yeah. Watch some JIT optimize this out.
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foo = None
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test_mesh()
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