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- ---
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- license: mit
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- ---
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-
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- ## Notes
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- * This model is a trained version of the Keras Tutorial [Image Super Resolution](https://keras.io/examples/vision/super_resolution_sub_pixel/)
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- * The model has been trained on inputs of dimension 100x100 and outputs images of 300x300.
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  [Link to a pyimagesearch](https://www.pyimagesearch.com/2021/09/27/pixel-shuffle-super-resolution-with-tensorflow-keras-and-deep-learning/) tutorial I worked on, where we have used Residual blocks along with the Efficient sub pixel net.
 
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+ ---
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+ license: mit
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+ tags:
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+ - image-to-image
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+ ---
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+
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+ ## Notes
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+ * This model is a trained version of the Keras Tutorial [Image Super Resolution](https://keras.io/examples/vision/super_resolution_sub_pixel/)
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+ * The model has been trained on inputs of dimension 100x100 and outputs images of 300x300.
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  [Link to a pyimagesearch](https://www.pyimagesearch.com/2021/09/27/pixel-shuffle-super-resolution-with-tensorflow-keras-and-deep-learning/) tutorial I worked on, where we have used Residual blocks along with the Efficient sub pixel net.