44 lines
1.8 KiB
Python
44 lines
1.8 KiB
Python
"""
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Some code that will save virtual macbeth charts that show the difference between optimised matrices and non optimised matrices
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The function creates an image that is 1550 by 1050 pixels wide, and fills it with patches which are 200x200 pixels in size
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Each patch contains the ideal color, the color from the original matrix, and the color from the final matrix
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_________________
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| Ideal Color |
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|_______________|
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| Old | new |
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| Color | Color |
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|_______|_______|
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Nice way of showing how the optimisation helps change the colors and the color matricies
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"""
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import numpy as np
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from PIL import Image
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def visualise_macbeth_chart(macbeth_rgb, original_rgb, new_rgb, output_filename):
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image = np.zeros((1050, 1550, 3), dtype=np.uint8)
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colorindex = -1
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for y in range(6):
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for x in range(4): # Creates 6 x 4 grid of macbeth chart
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colorindex += 1
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xlocation = 50 + 250 * x # Means there is 50px of black gap between each square, more like the real macbeth chart.
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ylocation = 50 + 250 * y
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for g in range(200):
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for i in range(100):
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image[xlocation + i, ylocation + g] = macbeth_rgb[colorindex]
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xlocation = 150 + 250 * x
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ylocation = 50 + 250 * y
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for i in range(100):
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for g in range(100):
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image[xlocation + i, ylocation + g] = original_rgb[colorindex] # Smaller squares below to compare the old colors with the new ones
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xlocation = 150 + 250 * x
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ylocation = 150 + 250 * y
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for i in range(100):
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for g in range(100):
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image[xlocation + i, ylocation + g] = new_rgb[colorindex]
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img = Image.fromarray(image, 'RGB')
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img.save(str(output_filename) + 'Generated Macbeth Chart.png')
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