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Compressing images using Autoencoders and transferring them over the network

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AutoEncoded_Image_Transfer

Compressing images using Autoencoders and transferring them over the network. Currently supports colour image transfer at 256x256 image resolution. The encoder and decoder have been separated after training to deploy on different systems.

Results:

  • Compression ratio of 12:1
  • Image transfer times 10 times faster

image

Training Dataset: Stanford Dogs Dataset, Animals-10

Directories

1. Image_Transfer_Scripts

Contains 2 sub directories With_AE which houses the python scripts containing the model along image transfer across network. Also contains directory Without_AE housing python scripts without containing the model but only image transfer across network.

2. AutoEncoder_Weights

- There are 3 subdirectories

  • Working : Contains the most stable and usable autoencoder weights (Currently for the 1M architecture).
  • Experimental : Contains unstable autoencoder weights (Currently for the 9M architecture). At the moment has highly variable results.
  • Legacy : Contains older versions of the autoencoder weights (Unsupported versions, 1M with less training cycles).

3. Train-Test_Notebooks

Results notebook for different batch sizes : Batch_Tests.ipynb The rest are training notebooks

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Compressing images using Autoencoders and transferring them over the network

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