readme: ---
  
  tags:
  - Keras
  
  license: mit
  
  metrics:
  - PSNR
  
  ---
  
  
  Here is a fully trained model of EDSR (Enhanced Deep Residual Networks for Single Image Super-Resolution) model. This model surpassed the performance of the current available SOTA models.
  
  Spaces link - https://huggingface.co/spaces/keras-io/EDSR
  
  Paper Link - https://arxiv.org/pdf/1707.02921
  
  Keras Example link - https://keras.io/examples/vision/edsr/
  
  It was trained for 500 epochs with 200 steps each.
  
  TODO:
  
  Hack to make this work for any image size. Currently the model takes input of image size 150 x 150.
  We pad the input image with transparant pixels so that it is a square image, which is a multiple of 150 x 150
  Then we chop the image into multiple 150 x 150 sub images
  Upscale it and stich it together.
  
  The output image might look a bit off, because each sub-image dosent have data about other sub-images.
  This approach assumes that the subimage has enough data about its surroundings
  