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import gradio as gr | |
import kornia as K | |
from kornia.core import Tensor | |
def edge_detection(filepath, detector): | |
img: Tensor = K.io.load_image(filepath, K.io.ImageLoadType.RGB32) | |
img = img[None] | |
x_gray = K.color.rgb_to_grayscale(img) | |
if detector == '1st order derivates in x': | |
grads: Tensor = K.filters.spatial_gradient(x_gray, order=1) | |
grads_x = grads[:, :, 0] | |
grads_y = grads[:, :, 1] | |
output = K.utils.tensor_to_image(1. - grads_x.clamp(0., 1.)) | |
elif detector == '1st order derivates in y': | |
grads: Tensor = K.filters.spatial_gradient(x_gray, order=1) | |
grads_x = grads[:, :, 0] | |
grads_y = grads[:, :, 1] | |
output = K.utils.tensor_to_image(1. - grads_y.clamp(0., 1.)) | |
elif detector == '2nd order derivatives in x': | |
grads: Tensor = K.filters.spatial_gradient(x_gray, order=2) | |
grads_x = grads[:, :, 0] | |
grads_y = grads[:, :, 1] | |
output = K.utils.tensor_to_image(1. - grads_x.clamp(0., 1.)) | |
elif detector == '2nd order derivatives in y': | |
grads: Tensor = K.filters.spatial_gradient(x_gray, order=2) | |
grads_x = grads[:, :, 0] | |
grads_y = grads[:, :, 1] | |
output = K.utils.tensor_to_image(1. - grads_y.clamp(0., 1.)) | |
elif detector == 'Sobel': | |
x_sobel: Tensor = K.filters.sobel(x_gray) | |
output = K.utils.tensor_to_image(1. - x_sobel) | |
elif detector == 'Laplacian': | |
x_laplacian: Tensor = K.filters.laplacian(x_gray, kernel_size=5) | |
output = K.utils.tensor_to_image(1. - x_laplacian.clamp(0., 1.)) | |
else: | |
x_canny: Tensor = K.filters.canny(x_gray)[0] | |
output = K.utils.tensor_to_image(1. - x_canny.clamp(0., 1.0)) | |
return output | |
title = "Tactile Graphic Generator" | |
description = "<p style='text-align: center'>To use it, simply upload your image. Press Enter, them click on the tactile graphic to download.</p>" | |
iface = gr.Interface(edge_detection, | |
[ | |
gr.Image(type="filepath"), | |
gr.Dropdown(choices=["1st order derivates in x", "1st order derivates in y", "2nd order derivatives in x", "2nd order derivatives in y", "Sobel", "Laplacian", "Canny"]) | |
], | |
"image", | |
title=title, | |
description=description, | |
) | |
iface.launch() | |