Image Classification Project

Overview

Welcome to the Image Classification Project! This project focuses on building a Convolutional Neural Network (CNN) for image classification and object recognition using a carefully curated dataset. The goal is to create a model that can effectively categorize images into predefined classes.

Project Structure

• data/: This directory contains the dataset, split into training and testing sets.
• notebooks/: Explore the Jupyter notebooks used for data exploration, preprocessing, and model training.
• src/: Source code files reside here.
  • train.py: Script for training the CNN.
  • predict.py: Script for making predictions on new images.
• models/: Save your model weights in this directory.
• requirements.txt: Includes the list of project dependencies.
• README.md: The document you are currently reading, providing an overview, instructions, and documentation.

Setup

1. Clone the repository:

   git clone <repository_url>
   cd image-classification-project

2. Install dependencies: pip install -r requirements.txt
3. Usage: Training the Model- -Navigate to the src/ directory: cd src/ -Run the training script: python train.py
4. Results: Model Accuracy: 95.45%