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  1. README.md +25 -0
  2. requirements.txt +3 -0
  3. trained.h5 +3 -0
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  license: mit
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  ---
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+ title: EDSR Keras
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+ emoji: 🚀
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+ colorFrom: pink
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+ colorTo: yellow
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+ sdk: gradio
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+ sdk_version: 3.0.9
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+ app_file: app.py
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+ pinned: false
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  license: mit
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  ---
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+
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+ 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.
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+ Paper Link - https://arxiv.org/pdf/1707.02921
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+ Keras Example link - https://keras.io/examples/vision/edsr/
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+ TODO:
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+
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+ Hack to make this work for any image size. Currently the model takes input of image size 150 x 150.
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+ We pad the input image with transparant pixels so that it is a square image, which is a multiple of 150 x 150
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+ Then we chop the image into multiple 150 x 150 sub images
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+ Upscale it and stich it together.
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+
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+ The output image might look a bit off, because each sub-image dosent have data about other sub-images.
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+ This approach assumes that the subimage has enough data about its surroundings
requirements.txt ADDED
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+ scikit-image
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+ tensorflow
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+ keras
trained.h5 ADDED
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