Created
September 12, 2023 09:43
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Gaussian Blur (filter) example from scracth
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import numpy as np | |
import matplotlib.pyplot as plt | |
from scipy.signal import convolve2d | |
def build_filter(size, sigma): | |
# Construir matriz gaussiana 3x3 | |
x = np.arange(-size / 2 + 1, size / 2 + 1) | |
y = x[:, np.newaxis] | |
x0 = y0 = size // 2 | |
gauss = ( | |
(1 / (2 * np.pi * sigma**2)) | |
* np.exp(-((x - x0) ** 2 + (y - y0) ** 2) / (2 * sigma ** 2)) | |
) | |
# gauss /= np.sum(gauss) | |
return gauss | |
def build_image(size): | |
size = size | |
image = np.ones((size, size)) # 1 is Black | |
# Find center and paint around it | |
center = size // 2 | |
white = 0 | |
image[center, center] = white | |
image[center - 1, center - 1] = white | |
image[center + 1, center + 1] = white | |
image[center - 1, center] = white | |
image[center + 1, center] = white | |
image[center, center - 1] = white | |
image[center, center + 1] = white | |
return image | |
def plot(image, image_blur): | |
_, (ax1, ax2) = plt.subplots(1, 2) | |
ax1.imshow(image, cmap='gray') | |
ax2.imshow(image_blur, cmap='gray') | |
plt.show() | |
size = 3 | |
sigma = 5 | |
im_size = 10 | |
gauss = build_filter(size, sigma) | |
image = build_image(im_size) | |
print(f"filter: \n{gauss}") | |
print(f"image: \n{image}") | |
image_blur = convolve2d(image, gauss, mode='same') | |
plot(image, image_blur) |
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