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README.md

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 license: apache-2.0
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+Keras Embedding model that generates embeddings for CGI Classification. The model requires that the images be preprocessed by
+resizing to 256x256 and then converting to grayscale and then applying the Fourier transform. The process can be described as this:
+1. Resize to 256x256
+2. Convert to grayscale
+3. Apply the Fourier transform
+4. Feed into model input
 
-Keras Embedding model that generates embeddings for CGI Classification.
+The model will then transform the input transform into a 128-length embedding vector. These vectors are separable and can be used in classification models.
+The model doesn't enforce a specific classification model, prototypical networks, XGBoost, and other classifiers can be used to classify.