Image classification using deeper networks like ResNet, VGG, GoogLeNet etc.,
- Run pip install -r requirements.txtfrom the project directory to install the requirements.
- Data will be stored in wandb, so it should be installed and account has to be created. Also get the api key from wandb account online and addWANDB_API_KEYto the environment variables.
- 
To trainthe model, runpython main.py train -r <data_path> -d <dataset_name> -m <model_name> -s <model_save_path> Models Implemented: resnet18, resnet34, resnet50, resnet101, resnet152, vgg11, vgg13, vgg16, vgg19, GoogLeNet 
 Datasets Included: mnist, cifar10, cifar100
 Note: Download MNIST dataset manually and place it in the data_path as it's website is closed down.
- 
To testthe model on the test data, runpython main.py test -r <data_path> -d <dataset_name> -m <model_name> -s <model_save_path> Models Implemented: resnet18, resnet34, resnet50, resnet101, resnet152, vgg11, vgg13, vgg16, vgg19, GoogLeNet 
 Datasets Included: mnist, cifar10, cifar100