https://www.robots.ox.ac.uk/~vgg/data/pets/
O. M. Parkhi, A. Vedaldi, A. Zisserman, C. V. Jawahar
Cats and Dogs
IEEE Conference on Computer Vision and Pattern Recognition
A U-Net based neural network was trained from scratch using Pytorch Lightning wrapper over the Pytorch Framework.
The dropout probability was varied to optimise the network.
Adam with the default learning rate of 1-3.
Cross Entropy Loss of classified pixel labels and ground data.
Early Stopping , Best Validation loss checkpoints.
Datasets folder contain the Train / Validation / Test split on the dataset.
The tester.ipynb contain the testing notebook and can be used to generate more test samples. Some of the best test examples are in Sample Images folder.
| Sample1 | Sample 2 |
|---|---|
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Loss values can be found in the tensorboard logs.
tensorboard --logdir runs/
Model weight checkpoints are saved in CKPT folder