ESRGAN-图像超分辨率-pytorch

# ESRGAN-pytorch This repository implements a deep-running model for super resolution. Super resolution allows you to pass low resolution images to CNN and restore them to high resolution. We refer to the following article. [ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks](https://arxiv.org/abs/1809.00219) ## architecture [Overall Architecture]  [Basic block]  ### Test Code ```bash python test.py --lr_dir LR_DIR --sr_dir SR_DIR ``` ## Prepare dataset ### Use Flicker2K and DIV2K ```bash cd datasets python prepare_datasets.py cd .. ``` ### custom dataset Make dataset like this; size of hr is 128x128 ans lr is 32x32 ``` datasets/ hr/ 0001.png sdf.png 0002.png 0003.png 0004.png ... lr/ 0001.png sdf.png 0002.png 0003.png 0004.png ... ``` ## how to train run main file ```bash python main.py --is_perceptual_oriented True --num_epoch=10 python main.py --is_perceptual_oriented False --epoch=10 ``` ## Sample we are in training on this code and train is not complete yet. this is intermediate result. <img src="image/lr.png" width="200"> <img src="image/hr.png" width="800">