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import os
import gradio as gr
from PIL import Image
os.system('wget https://github.com/FanChiMao/SRMNet-thesis/releases/download/v0.0/Deblurring_motionblur.pth -P experiments/pretrained_models')
os.system('wget https://github.com/FanChiMao/SRMNet-thesis/releases/download/v0.0/Dehaze_realworld.pth -P experiments/pretrained_models')
os.system('wget https://github.com/FanChiMao/SRMNet-thesis/releases/download/v0.0/Denoise_gaussian.pth -P experiments/pretrained_models')
os.system('wget https://github.com/FanChiMao/SRMNet-thesis/releases/download/v0.0/Denoise_realworld.pth -P experiments/pretrained_models')
os.system('wget https://github.com/FanChiMao/SRMNet-thesis/releases/download/v0.0/Deraining_raindrop.pth -P experiments/pretrained_models')
os.system('wget https://github.com/FanChiMao/SRMNet-thesis/releases/download/v0.0/Deraining_rainstreak.pth -P experiments/pretrained_models')
os.system('wget https://github.com/FanChiMao/SRMNet-thesis/releases/download/v0.0/LLEnhancement.pth -P experiments/pretrained_models')
os.system('wget https://github.com/FanChiMao/SRMNet-thesis/releases/download/v0.0/Retouching.pth -P experiments/pretrained_models')
def inference(img, model):
os.system('mkdir test')
img.save("test/1.png", "PNG")
if model == 'Denoising (gaussian)':
os.system('python main_test_SRMNet.py --input_dir test --task Deblurring_motionblur')
elif model == 'Denoising (real-world)':
os.system('python main_test_SRMNet.py --input_dir test --task Dehaze_realworld')
elif model == 'Deblurring (motion-blur)':
os.system('python main_test_SRMNet.py --input_dir test --task Denoise_gaussian')
elif model == 'Dehazing (dense haze)':
os.system('python main_test_SRMNet.py --input_dir test --task Denoise_realworld')
elif model == 'Deraining (rainstreak)':
os.system('python main_test_SRMNet.py --input_dir test --task Deraining_raindrop')
elif model == 'Deraining (raindrop)':
os.system('python main_test_SRMNet.py --input_dir test --task Deraining_rainstreak')
elif model == 'Low-light Enhancement':
os.system('python main_test_SRMNet.py --input_dir test --task LLEnhancement')
elif model == 'Retouching':
os.system('python main_test_SRMNet.py --input_dir test --task Retouching')
return 'result/1.png'
title = "[NCHU thesis] Image Restoration by Selective Residual Block on Improved Hierarchical Encoder-Decoder Networks"
description = ""
article = "<p style='text-align: center'><a href='https://' target='_blank'>Image Restoration by Selective Residual Block on Improved Hierarchical Encoder-Decoder Networks</a> | <a href='https://github.com/FanChiMao/SRMNet-thesis' target='_blank'>Github Repo</a></p> <center><img src='https://visitor-badge.glitch.me/badge?page_id=52Hz_SRMNet_thesis' alt='visitor badge'></center>"
examples = [
['figures/noise_1.png', 'Denoising (gaussian)'],
['figures/noise_2.png', 'Denoising (real-world)'],
['figures/blur.png', 'Deblurring (motion-blur)'],
['figures/haze.png', 'Dehazing (dense haze)'],
['figures/rainstreak.png', 'Deraining (rainstreak)'],
['figures/raindrop.png', 'Deraining (raindrop)'],
['figures/LL.png', 'Low-light Enhancement'],
['figures/nchu.png', 'Retouching'],
]
gr.Interface(
inference,
[gr.inputs.Image(type="pil", label="Input"), gr.inputs.Dropdown(choices=[
'Denoising (gaussian)',
'Denoising (real-world)',
'Deblurring (motion-blur)',
'Dehazing (dense haze)',
'Deraining (rainstreak)',
'Deraining (raindrop)',
'Low-light Enhancement',
'Retouching',
], type="value", default='Denoising (gaussian)', label="model")],
gr.outputs.Image(type="file", label="Output"),
title=title,
description=description,
article=article,
allow_flagging=False,
allow_screenshot=False,
examples=examples
).launch(debug=True) |