Plant Disease Classifier
About PlantVillage Dataset
The PlantVillage dataset contains over 54,000 images of healthy and diseased crop leaves, categorized into 38 classes. This comprehensive dataset covers 14 crop species and 26 diseases, making it ideal for training robust plant disease detection models.
- Project Type: Deep Learning / Computer Vision
- Model Architecture: Custom CNN with Transfer Learning
Key Features:
- High-accuracy disease classification (achieved 98.7% test accuracy)
- Support for multiple crop species (tomato, potato, pepper, etc.)
- Real-time image processing capability
- Web interface for easy user interaction
- Detailed disease information and treatment suggestions
Project Description:
This deep learning project leverages the PlantVillage dataset to create a robust plant disease detection system. Using convolutional neural networks (CNNs) with transfer learning techniques, the model can accurately identify various plant diseases from leaf images.
The system was developed to help farmers and agricultural professionals quickly diagnose plant health issues, enabling early intervention. The web interface allows users to upload images of plant leaves and receive instant diagnoses along with treatment recommendations.