This is a project for image super resolution. In this project, we implemented some state-of-art methods for image super resolution. It contains the dataset preprocessing, model training, model evaluating. Every subdir contains the codes for training and testing of one specific method.
- Tensorflow 1.1.1
- Linux with Nvidia GPU + cuDNN
git clone git@github.com:BingzheWu/tf-sr-zoo.git
cd tf-sr-zoo
Then, chose the model you want to use, and get in the subdir to see more details.
| Date | Update |
|---|---|
| 20170720 | Collect all trace of Evaluation |
| 20170715 | Add attention Layer |
| 20170710 | Add Instance Normalization |
| 20170708 | Add evaluation module |
| 20170705 | Add gan based pix2pix model |
| 20170703 | Add LapSRN model |
| 20170628 | TFRecord Creator |
| 20170624 | Add Dataset Module |
- Dataset Module (Done)
- Lap-SRN Method (Done)
- Pix2Pix Method (Done)
- Perceptual-GAN (Done)
- Instance Normalization(Done)
- Add unify testing module for every datasets (Doing)
- Add vis Tools (To Do)
- Combine L2 + L1 + adversarial loss with weighted term(To Do)
- Build a Docker Image (To Do)