AI & Machine Learning
AI Plant Disease Detector
High-Accuracy Crop Health Analysis for Farmers
The Problem
Farmers and agriculturalists often struggle with the early and accurate identification of plant diseases, leading to potential crop loss and inefficient use of treatments.
The Solution
I built and deployed a user-friendly web application that leverages a Convolutional Neural Network (CNN) to identify over 30 plant diseases with a 98% training and 97% validation accuracy. The system is enhanced with a Generative AI (Gemini) integration to provide farmers with immediate, actionable advice and preventive guidance, turning a powerful model into a practical tool.
Tech Stack
PythonTensorFlowCNNsGemini APIStreamlit
Status & Links
Completed
Key Features & Contributions
High-Performance CNN Model
Engineered a deep learning model with TensorFlow, achieving a 97% validation accuracy on the PlantVillage dataset, demonstrating robust and reliable classification.
Generative AI Guidance
Integrated the classification output with the Gemini LLM to provide clear, context-aware treatment and prevention strategies in natural language.
Interactive Web Interface
Developed a simple and accessible front-end with Streamlit, allowing for easy image uploads and instant, understandable results for non-technical users.
End-to-End Deployment
Managed the complete project lifecycle from model training and validation to deployment as a publicly accessible web application.