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image convolution numpy python

_loganthx answered on May 12, 2023 Popularity 3/10 Helpfulness 1/10

answer image convolution numpy python

image convolution numpy python

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import numpy as np, cv2 as cv, matplotlib.pyplot as plt

input_image = cv.resize(cv.imread("YourImg.png", 0), (100, 100))
kernel = np.array([[-1,-1,-1], [-1, 8, -1], [-1, -1, -1]])

# Compute output shape
input_shape, kernel_shape = input_image.shape, kernel.shape
output_shape = (input_shape[0] - kernel_shape[0] + 2 * 0)//1 + 1, (input_shape[1] - kernel_shape[1] + 2 * 0)//1 + 1

# Apply convolution
output = np.zeros(output_shape)
for i in range(output_shape[0]):
    for j in range(output_shape[1]):
        output[i,j] = np.sum(input_image[i:i+kernel_shape[0], j:j+kernel_shape[1]] * kernel)

# Check output
print(output.shape)
axs = plt.subplots(1,2, figsize=(12, 4))[1]
axs[0].imshow(input_image, cmap='gray')
axs[1].imshow(output, cmap='gray')
plt.show()

Popularity 3/10 Helpfulness 1/10 Language python

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Tags: convolution image numpy python

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Contributed on May 12 2023

_loganthx

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