Classifies an image as containing either a dog or a cat (using Kaggle's public dataset), but could easily be extended to other image classification problems.
- PyTorch / Torchvision
- Numpy
- PIL
- CUDA
The data directory structure I used was:
- project
- data
- train
- dogs
- cats
- validation
- dogs
- cats
- test
- test
- train
- data
The result of the notebook in this repo produced a log loss score on Kaggle's hidden dataset of 0.04988 -- further gains can probably be achieved by creating an ensemble of classifiers using this approach.