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Initial commit (change from personal space)
Browse files- .DS_Store +0 -0
- app.py +53 -0
- packages.txt +1 -0
- requirements.txt +4 -0
.DS_Store
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Binary file (6.15 kB). View file
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app.py
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# created with great guidance from https://github.com/NimaBoscarino
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import gradio as gr
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import kornia as K
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from kornia.core import Tensor
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def filters(file, box_blur, blur_pool2d, gaussian_blur2d, max_blur_pool2d, median_blur):
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# load the image using the rust backend
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img: Tensor = K.io.load_image(file.name, K.io.ImageLoadType.RGB32)
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img = img[None] # 1xCxHxW / fp32 / [0, 1]
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# apply tensor image enhancement
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x_out: Tensor = K.filters.box_blur(img, (int(box_blur), int(box_blur)))
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x_out = K.filters.blur_pool2d(x_out, int(blur_pool2d))
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x_out = K.filters.gaussian_blur2d(x_out,
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(int(gaussian_blur2d), int(gaussian_blur2d)),
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(float(gaussian_blur2d), float(gaussian_blur2d)))
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x_out = K.filters.max_blur_pool2d(x_out, int(max_blur_pool2d))
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x_out = K.filters.median_blur(x_out, (int(median_blur), int(median_blur)))
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return K.utils.tensor_to_image(x_out)
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examples = [
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["examples/ninja_turtles.jpg", 1, 1, 1, 1, 1],
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["examples/kitty.jpg", 1, 1, 1, 1, 1],
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]
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title = "Kornia Image Filters"
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description = "<p style='text-align: center'>This is a Gradio demo for Kornia's Image Filters.</p><p style='text-align: center'>To use it, simply upload your image, or click one of the examples to load them, and use the sliders to enhance! Read more at the links at the bottom.</p>"
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article = "<p style='text-align: center'><a href='https://kornia.readthedocs.io/en/latest/' target='_blank'>Kornia Docs</a> | <a href='https://github.com/kornia/kornia' target='_blank'>Kornia Github Repo</a> | <a href='https://kornia-tutorials.readthedocs.io/en/latest/image_enhancement.html' target='_blank'>Kornia Enhancements Tutorial</a></p>"
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iface = gr.Interface(
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filters,
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[
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gr.inputs.Image(type="file"),
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gr.inputs.Slider(minimum=1, maximum=10, step=1, default=1, label="Box Blur"),
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gr.inputs.Slider(minimum=1, maximum=10, step=1, default=1, label="Blur Pool"),
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gr.inputs.Slider(minimum=1, maximum=21, step=2, default=1, label="Gaussian Blur"),
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gr.inputs.Slider(minimum=1, maximum=20, step=1, default=1, label="Max Pool"),
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gr.inputs.Slider(minimum=1, maximum=5, step=2, default=1, label="Median Blur"),
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],
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"image",
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examples=examples,
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# title=title,
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# description=description,
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# article=article,
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live=True
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)
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iface.launch()
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packages.txt
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python3-opencv
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requirements.txt
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kornia
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kornia_rs
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opencv-python
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torch
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