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:
- Resize to 256x256
- Convert to grayscale
- Apply the Fourier transform
- Feed into model input
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. For more detailed instructions refer to Kaggle.
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