50 lines
1.8 KiB
Python
50 lines
1.8 KiB
Python
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import os
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from PIL import Image, ImageFilter, ImageMath
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from scipy import ndimage
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import numpy as np
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JPGDIR = '/media/nfs/SRS/IMPAX/'
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def img_frombytes(data):
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size = data.shape[::-1]
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databytes = np.packbits(data, axis=1)
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return Image.frombytes(mode='1', size=size, data=databytes)
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for pid in sorted(os.listdir(JPGDIR)):
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PATDIR = os.path.join(JPGDIR, pid)
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for study in sorted(os.listdir(PATDIR)):
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if study.endswith('_100'):
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ST100_DIR = os.path.join(PATDIR, study)
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for jpg in sorted(os.listdir(ST100_DIR)):
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jpg_path = os.path.join(ST100_DIR, jpg)
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img = Image.open(jpg_path).convert('L')
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jpg_ndarray = np.array(img)
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# CC = (0xCB <= jpg_ndarray <= 0xCD)
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CC = np.logical_and(jpg_ndarray >= 0xCB, jpg_ndarray <= 0xCD)
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C0 = (jpg_ndarray <= 0x01)
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MASK = np.logical_or(CC, C0)
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MASK = np.roll(MASK, -1, 0)
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MASK = np.roll(MASK, -1, 1)
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# MASKED = np.logical_and(CC, MASK).astype('uint8') * 255
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MASKED = np.logical_and(CC, MASK).astype('uint8')
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FILTERD = ndimage.rank_filter(MASKED, rank=-2, size=3)
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FILTERD = np.minimum(MASKED, FILTERD)
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# im = Image.fromarray(FILTERD )
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im = img_frombytes(FILTERD)
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im.save ('/shares/Public/0/0.png')
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# print(CC)
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# print(CC.shape)
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# im = img_frombytes(FINAL)
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# imr = im.filter(ImageFilter.RankFilter(3, 3*3-2))
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# out = ImageMath.eval("min(a, b)", a=im, b=imr)
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# out.save ('/shares/Public/0/0.png')
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# img.save ('/shares/Public/0/0.png')
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exit()
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