https://github.com/raphaelmeudec/deblur-gan

Keras implementation of "DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks"
https://github.com/raphaelmeudec/deblur-gan

gan generative-adversarial-networks image-deblurring keras

Last synced: 1 day ago
JSON representation

Keras implementation of "DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks"

• Host: GitHub
• URL: https://github.com/raphaelmeudec/deblur-gan
• Owner: RaphaelMeudec
• Created: 2018-02-12T13:57:22.000Z (almost 7 years ago)
• Default Branch: master
• Last Pushed: 2022-11-22T04:29:42.000Z (about 2 years ago)
• Last Synced: 2024-10-12T04:49:06.077Z (3 months ago)
• Topics: gan, generative-adversarial-networks, image-deblurring, keras
• Language: Python
• Size: 79.2 MB
• Stars: 585
• Watchers: 20
• Forks: 245
• Open Issues: 46
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# What is this repo ?

This repository is a Keras implementation of [Deblur GAN](https://arxiv.org/pdf/1711.07064.pdf). You can find a tutorial on how it works on [Medium](https://blog.sicara.com/keras-generative-adversarial-networks-image-deblurring-45e3ab6977b5). Below is a sample result (from left to right: sharp image, blurred image, deblurred image)

![Sample results](./sample/results0.png)

# Installation

```

virtualenv venv -p python3

. venv/bin/activate

pip install -r requirements/requirements.txt

pip install -e .

```

# Dataset

Get the [GOPRO dataset](https://drive.google.com/file/d/1H0PIXvJH4c40pk7ou6nAwoxuR4Qh_Sa2/view?usp=sharing), and extract it in the `deblur-gan` directory. The directory name should be `GOPRO_Large`.

Use:

```

python scripts/organize_gopro_dataset.py --dir_in=GOPRO_Large --dir_out=images

```

# Training

```

python scripts/train.py --n_images=512 --batch_size=16 --log_dir /path/to/log/dir

```

Use `python scripts/train.py --help` for all options

# Testing

```

python scripts/test.py

```

Use `python scripts/test.py --help` for all options

# Deblur your own image

```

python scripts/deblur_image.py --weight_path=/path/to/generator.h5 --input_dir=/path/to/image/dir --output_dir=/path/to/deblurred/dir

```