linchuming / ImageSR-Tensorflow

An image super-resolution implemented by Tensorflow

ImageSR for Tensorflow

Update

• 2019.11.25: We release Pytorch version for ImageSR ImageSR-Pytorch

Preparation

• Python 2.7/3.4/3.5/3.6 (recommend python 3.5/3.6)
• Tensorflow 1.4+ (utilize tf.data to read training data)

Training

• Prepare training dataset. Please download DIV2K dataset: link
• Move the training dataset to ./DIV2K/DIV2K_train_HR
• Check the config in train.py
• Run train.py > python train.py

Inference

We train two models: VDSR (only x4 scale) and EDSR (small version). Models are trained 50,000 steps with batch size 64.
Please download model ckpt files from Cloud:
BaiduYun:
link：https://pan.baidu.com/s/1eB0jY5cgp7j39M3Gt2ndqw password：4qm4
GoogleDrive:
line: https://drive.google.com/open?id=1IUKH4f0LzkobU4zktA3ZzEg86-ufrV1c

• Check the config in test.py
• Run test.py > python test.py

Performance

Using our models can achieve the performance as shown in below table data:

Dataset	Scale	Bicubic	VDSR	EDSR
Set5	x4-PSNR	28.43	31.43	31.90

x4 SR Visual Result

BICUBIC	VDSR	EDSR