40 lines
1.5 KiB
Python
40 lines
1.5 KiB
Python
from PIL import Image
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def convolution(input_image, image_filter):
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width, height = input_image.size
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output_image = Image.new("RGB", (width, height))
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for x in range(width):
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for y in range(height):
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red, green, blue = 0, 0, 0
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div = 0
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filter_from = -int(len(image_filter[0])/2)
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filter_to = len(image_filter[0]) + filter_from
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for i in range(filter_from, filter_to):
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for j in range(filter_from, filter_to):
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if x + i > 0 and x + i < width-1 and y + j > 0 and y + j < height-1:
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neighbor_pixel = input_image.getpixel((x + i, y + j))
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red += image_filter[i + 1][j + 1] * neighbor_pixel[0]
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green += image_filter[i + 1][j + 1] * neighbor_pixel[1]
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blue += image_filter[i + 1][j + 1] * neighbor_pixel[2]
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div += image_filter[i + 1][j + 1]
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if div > 0:
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red = int(red/div)
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blue = int(blue/div)
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green = int(green/div)
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output_image.putpixel((x, y), (red, green, blue))
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output_image.save("moucha3.jpg")
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output_image.close()
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input_image.close()
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# moucha3.jpg
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odsumeni = [[1, 2, 1], [2, 5, 2], [1, 2, 1]]
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# moucha1.jpg
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sum = [[2, 4, 5, 4, 2], [4, 9, 12, 9, 4], [5, 12, 15, 12, 5], [4, 9, 12, 9, 4], [2, 4, 6, 4, 2]]
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# moucha2.jpg
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hrany = [[0, 1, 0], [1, -4, 1], [0, 1, 0]]
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# convolution(Image.open("pop.jpg"), sum)
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convolution(Image.open("moucha.jpg"), odsumeni)
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