agriculture-crop-disease-detection

OverView of Crop Disease Detection Transformer

This model is a Vision Transformer (ViT) fine-tuned with LoRA to detect plant diseases in crops, aimed at enabling precision farming. It can classify diseases in crops such as corn, potato, rice, and wheat, helping farmers and agronomists identify issues early for better crop management.

Crops

• Sugarcane
• Corn
• Potato
• Rice
• Wheat

Model description

This Vision Transformer has been fine-tuned using LoRA adapters on a diverse dataset of plant images, covering multiple disease categories. The model can identify diseases such as rust, blight, leaf spots, and others across major crops including corn, potato, rice, and wheat. It outputs disease classification labels from input crop images.

• Developed by: Lisha
• Model type: Vision Transformer (ViT) with LoRA
• Architecture: Vision Transformer (ViT)
• Task: Image Classification
• Format: Safetensors

Diseases Detected by Model

Sugarcane: Bacterial Blight, Red Rot, Healthy
Corn: Common Rust, Gray Leaf Spot, Leaf Blight, Healthy
Potato: Early Blight, Late Blight, Healthy
Rice: Bacterial Blight, Blast, Brown Spot, False Smut Disease, Leaf Blast, Healthy
Wheat: Brown Rust, Yellow Rust, Healthy

Training Data

Images(RGB) of Sugarcane,Corn,Potato,Rice,Wheat

Intended Use

This model is intended for:

• Agricultural disease detection
• Research and educational use
• AI-powered farming tools

Limitations

Predictions may be inaccurate for low-quality or unseen crop images.