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import gradio as gr | |
import os | |
os.system("git clone https://github.com/megvii-research/NAFNet") | |
os.system("mv NAFNet/* ./") | |
os.system("mv *.pth experiments/pretrained_models/") | |
os.system("python3 setup.py develop --no_cuda_ext --user") | |
def inference(image, task): | |
if not os.path.exists('tmp'): | |
os.system('mkdir tmp') | |
image.save("tmp/lq_image.png", "PNG") | |
if task == 'Denoising': | |
os.system("python basicsr/demo.py -opt options/test/SIDD/NAFNet-width64.yml --input_path ./tmp/lq_image.png --output_path ./tmp/image.png") | |
if task == 'Deblurring': | |
os.system("python basicsr/demo.py -opt options/test/REDS/NAFNet-width64.yml --input_path ./tmp/lq_image.png --output_path ./tmp/image.png") | |
return 'tmp/image.png' | |
title = "image deblurring" | |
description = " - performance on three tasks: image denoising, image deblurring. Here, we provide a demo for image denoise and deblur. " | |
article = "<p style='text-align: center'> | Ogunwale felix</p>" | |
examples = [['demo/noisy.png', 'Denoising'], | |
['demo/blurry.jpg', 'Deblurring']] | |
iface = gr.Interface( | |
inference, | |
[gr.inputs.Image(type="pil", label="Input"), | |
gr.inputs.Radio(["Denoising", "Deblurring"], default="Denoising", label='task'),], | |
gr.outputs.Image(type="file", label="Output"), | |
title=title, | |
description=description, | |
article=article, | |
enable_queue=True, | |
examples=examples | |
) | |
iface.launch(debug=True,enable_queue=True) |