This is my implementation of a special Variational Autoencoder under TF 2.0, which make it possible to squeeze N images to generate one single representation of all the dataset with colors segmentation of the difference objects
This VAE has the ability to generate from within the distribution of satellites images a new image.
| Hyperparameters | Values |
|---|---|
| Epochs | 2 |
| batch size | 32 |
| learning rate | 1e-4 |
| dropout | 0.5 |
| mse_weight | 1 |
| KLDiv_weight | 1e-3 |
| Hidden activation | SeLU |
| Latent activation | Sigmoid |
Data represents satellites images of cities with multiples objects.
The resulted image shows interesting result, where objects are segmented with a specific color which make us able to distinguish an item from another.
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