data_setup.py

"""
Contains functionality for creating Pytorch DataLoaders for
image classification data.
"""

import os

from torchvision import datasets, transforms
from torch.utils.data import DataLoader

NUM_WORKERS = os.cpu_count()

def create_dataloaders(
    train_dir: str,
    test_dir: str,
    transform: transforms.Compose,
    batch_size: int,
    num_workers: int=NUM_WORKERS
):
    """
    Creates training and testing DataLoaders
    """
    
    # Use ImageFolder to create Datasets
    train_data = datasets.ImageFolder(train_dir, transform=transform)
    test_data = datasets.ImageFolder(test_dir, transform=transform)
    
    # Get class names
    class_names = train_data.classes
    
    # Turn images into data loaders
    train_dataloader = DataLoader(
        train_data,
        batch_size=batch_size,
        shuffle=True,
        num_workers=num_workers,
        pin_memory=True
    )
    test_dataloader = DataLoader(
        test_data,
        batch_size=batch_size,
        shuffle=True,
        num_workers=num_workers,
        pin_memory=True
    )
    
    return train_dataloader, test_dataloader, class_names