Super-Resolution Implicit Model (SRIM) is a multi-modal image super-resoluition model. This repository contains two implementations of the model:

• One deep neural network featuring Residual-in-Residual Dense Block (RRDB)
• One legacy CNN based network derived from Caffe implementation

Code organization copied from [BasicSR]

• Python 3 (Recommend to use Anaconda)
• PyTorch >= 1.1
• NVIDIA GPU + CUDA
• Python packages: pip install -r requirements.txt

We use datasets in LDMB format for faster IO speed. Please refer to create_hr_lr_lmdb.py for more details.

To train model with RRDB, please refer to train_srim.sh To train legacy Caffe model, please refer to train_caffe.sh