Fruit Image Classification using CNN

A Supervised Deep Learning project that trains a Convolutional Neural Network (CNN) to classify fruit images into two categories: Apple and Watermelon using TensorFlow/Keras.

Features

• Trained a CNN model for binary image classification
• Image preprocessing and data augmentation
• Model training and validation
• Save and load trained model for inference
• Predict fruit classes on unseen images

Tech Stack

• Python
• TensorFlow / Keras
• NumPy

Project Structure

• imageclassification.py – Model training
• testimgclass.py – Model testing and prediction
• model.json & model.weights.h5 – Trained model architecture and weights

Future Improvements

• Train on a larger dataset
• Support multiple fruit categories
• Deploy as a web application