ykcheungab
54 lines
1.6 KiB
Python
54 lines
1.6 KiB
Python
#%%
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import numpy as np
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import cv2
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def generate_color_pattern(h, w, d, r):
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# Initialize the pattern with zeros
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pattern = np.zeros((h, w, 3))
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# Calculate the number of patches in each dimension
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num_patches_x = h // d
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num_patches_y = w // d
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# Maximum number of attempts to find a suitable color
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max_attempts = 1000
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# Iterate over the patches
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for i in range(num_patches_x):
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for j in range(num_patches_y):
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# Get the neighbors
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neighbors = []
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if i > 0:
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neighbors.append(pattern[(i-1)*d:i*d, j*d:(j+1)*d])
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if j > 0:
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neighbors.append(pattern[i*d:(i+1)*d, (j-1)*d:j*d])
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# Generate a new color
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for attempt in range(max_attempts):
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new_color = np.random.rand(3)
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if all(np.min((new_color - neighbor.mean(axis=(0, 1)))**2) >= r for neighbor in neighbors):
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break
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if attempt == max_attempts - 1:
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print(f"Warning: Could not find a suitable color for patch ({i}, {j}) after {max_attempts} attempts")
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# Apply the new color to the patch
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pattern[i*d:(i+1)*d, j*d:(j+1)*d] = new_color
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print('Patch ({}, {})'.format(i, j))
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return pattern
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# Test the function
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pattern = generate_color_pattern(162, 162, 3, 0.75)
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# Convert the pattern to a format suitable for display with OpenCV
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pattern_display = (pattern * 255).astype(np.uint8)
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# # Display the pattern
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# cv2.imshow('Pattern', pattern_display)
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# cv2.waitKey(0)
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# cv2.destroyAllWindows()
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# #%%
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cv2.imwrite('color_pattern.png', pattern_display)
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