The project focuses on the development of an advanced system for fruit classification using deep learning techniques, specifically leveraging Convolutional Neural Network (CNN) architecture. The primary objective is to create a robust model capable of accurately identifying various types of fruits and their ripeness class (Rotten or Good quality). The significance of this project lies in its potential applications across agriculture and food industries, enabling automated sorting and quality control processes. The CNN model is trained on a diverse dataset of fruit images, encompassing different species. The project's outcomes showcase the model's effectiveness in almost accurately categorizing fruits and their ripeness, offering a promising solution for enhancing efficiency and precision in fruit processing and distribution systems.
Note: Currently the project classifies only 6 categories of fruits which are mentioned in the web-app. Providing any other images may lead to false classification
Open the Streamlit app
Upload one of the fruits image. Then click Submit button.
The prediction will be shown below the image.
