PyTorch Tutorial: ImageFolder with Code Examples
In this tutorial, we'll explore how to use the ImageFolder dataset in PyTorch, a popular deep learning library, to load and preprocess image data for training a neural network. The ImageFolder dataset is useful when dealing with image data organized in a specific folder structure, where each class has its own folder containing images. Dataset Structure Before diving into code examples, let's understand the required folder structure for using ImageFolder : data/ ├── train/ | ├── class_1/ | | ├── image_1.jpg | | └── image_2.jpg | ├── class_2/ | | ├── image_3.jpg | | └── image_4.jpg | └── ... ├── val/ | ├── class_1/ | | ├── image_5.jpg | | └── image_6.jpg | ├── class_2/ | | ├── image_7.jpg | | └── image_8.jpg | └── ... In this example, the images are categorized into classes, and the train and validation sets are organized in separate folders. Code Exampl...