Learnt how to create dataloaders, models and training code in PyTorch. The following models were created and analysis carried out:
- With Batch Norm
- Adding new layers
- With Dropout
- Different activation functions at the end
- Different pooling strategies
- Different optimizers
- Basic Augmentation like Rotation, Translation, Color Change
It is available here. There are approximately 9233 images in train and 484 images in test set.
The submission is for this challenge on ai-crowd portal. This was done using a resnet-50 pre-trained model.