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Overview I'm trying to create a model that takes a "foot heatmap" (input image) and predicts a "shell heatmap" (true heatmap). My data contains foot heatmaps with a corresponding shell heatmap.

What I've done so far

  1. Basic Linear regression model using scikit-learn. The output is OK but I need it to be more precise.

Linear Regression Model

  1. Neural network model (really off) - I'm not sure why the predicted image looks more like the input image ... NN

My question/ help

How can I improve my model? How do I get a proper image output using a CNN?

Any comment/discussion is appreciated - I haven't found any projects similar to this

Please note that I'm not looking to make a hybrid of the two images but instead I want my model to produce a shell image based on a foot input image (so no Transfering Learning or StyleGAN or pix2pix)

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