This is a web application built using Streamlit that allows users to upload images and detect diseases or nutrient deficiencies present in the images. The application utilizes a Convolutional Neural Network (CNN) model trained on relevant data to make predictions.
Upload images for analysis
Detect diseases or nutrient deficiencies from the uploaded images
Easy-to-use interface powered by Streamlit
The CNN model used for prediction is trained on a dataset of images containing examples of various diseases and nutrient deficiencies. The model has been trained to recognize patterns indicative of these conditions in images.
🔸Machine Learning: Convolutional Neural Networks (CNNs)
🔸Web Development: Streamlit for creating the web application
🔸Data Collection: Dataset of plant leaves with annotated labels for different deficiencies and diseases from Kaggle
🔸Programming Languages: Python
