plant-disease-vit

Plant Leaf Disease Classification using Vision Transformer

A Vision Transformer (ViT) built from scratch using PyTorch for classifying plant leaf diseases.

The model takes a 64×64 RGB image as input and predicts one of 39 plant disease classes.

Model Performance

The model achieved approximately:

• 99.16% Test Accuracy
• Input resolution: 64 × 64
• Number of classes: 39
• Architecture: Vision Transformer
• Framework: PyTorch

Test accuracy may vary slightly depending on the training configuration and dataset split.

Model Architecture

This implementation uses a custom Vision Transformer rather than a pretrained ViT.

Patch Embedding

Images are divided into 8 × 8 patches.

For a 64 × 64 image:

64 / 8 = 8