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ImageRestoration-Streamlit


Restore image using NAFNet model with streamlit dashboard

Dashboard

demo

Installtion

  1. Clone this Repo
git clone https://github.com/naseemap47/ImageRestoration-Streamlit.git
cd ImageRestoration-Streamlit
  1. Install Libraries

With pip

pip install torch==2.0.0+cu117 torchvision==0.15.1+cu117 torchaudio==2.0.1 --index-url https://download.pytorch.org/whl/cu117
pip install -r requirements.txt
pip install --upgrade --no-cache-dir gdown
python3 setup.py develop --no_cuda_ext
pip install streamlit

With conda (Recommended)

conda create -n app python=3.9 -y
conda activate app

# Linux and Windows
conda install pytorch==2.0.0 torchvision==0.15.0 torchaudio==2.0.0 pytorch-cuda=11.7 -c pytorch -c nvidia
# OSX
conda install pytorch==2.0.0 torchvision==0.15.0 torchaudio==2.0.0 -c pytorch

pip install -r requirements.txt
pip install --upgrade --no-cache-dir gdown
python3 setup.py develop --no_cuda_ext
pip install streamlit

Download pretrained models

python3 -c "import gdown;gdown.download('https://drive.google.com/uc?id=14D4V4raNYIOhETfcuuLI3bGLB-OYIv6X', './experiments/pretrained_models/', quiet=False)"

Run Dashboard

streamlit run app.py

User Guide

  1. Upload image - (Click -> Browse files)
  2. To restore image (Click -> Submit)
  3. Download restored image - (Click -> Download Image)

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Restore image using NAFNet model with streamlit dashboard

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