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title: EDSR Keras | |
emoji: π | |
colorFrom: pink | |
colorTo: yellow | |
sdk: gradio | |
sdk_version: 3.0.9 | |
app_file: app.py | |
pinned: false | |
license: mit | |
This space is the demo for the EDSR (Enhanced Deep Residual Networks for Single Image Super-Resolution) model. This model surpassed the performace of the current available SOTA models. | |
Paper Link - https://arxiv.org/pdf/1707.02921 | |
Keras Example link - https://keras.io/examples/vision/edsr/ | |
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 | |