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36 lines
1.2 KiB
36 lines
1.2 KiB
from PIL import Image
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import numpy as np
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# Location of the image
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img = Image.open("koko.jpg")
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# size of the image
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print(img.size)
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# format of the image
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print(img.format)
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# mode of the image
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xpixel = img.size[0]
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ypixel = img.size[1]
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#turn into editable list of colors
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data = np.asarray(img, dtype=np.uint8)
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data_new = np.zeros([ypixel, xpixel, 3], dtype=np.uint8)
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#apply sharpen convolution as SIMD/Vector instruction
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for y in range(data.shape[1]-1):
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#process all colors and the column convolution as vector operation
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#factors needed for type conversion to np.float64 to prevent integer overflow
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new_value = -1.0*data[:, y+1, :] + 2.5*data[:, y, :] - 1.0*data[:, y-1, :]
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new_value[new_value > 255] = 255
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new_value[new_value < 0] = 0
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data_new[:, y, :] = new_value
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for x in range(data.shape[0]-1):
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new_value = 1.0*data_new[x, :, :] - 1.0*data[x+1,:, :] + 2.5*data[x,:, :] - 1.0*data[x-1,:, :]
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new_value[new_value > 255] = 255
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new_value[new_value < 0] = 0
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data_new[x, :, :] = new_value
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#convert our new data into an image
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img_new = Image.fromarray(data_new)
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#the data and new image is 8-Bit unsigned integer per color -> PILLOW mode "RGB"
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img_new.convert("RGB")
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img_new.show() |