CIFAR-10 Classifier 📷🤖

As a way to sharpen my Python skills and work on Machine Learning I made a Classifier!

This project implements a Convolutional Neural Network (CNN) for classifying images from the CIFAR-10 dataset. The model is trained to recognize 10 different classes of images, such as airplanes, automobiles, cats, and more.

Features ✨

• Image Classification: Classifies images into one of 10 classes (airplane, automobile, bird, cat, deer, dog, frog, horse, ship, truck).
• Web Application: A Flask web app that allows users to upload images and get predictions based on the trained model.

Prerequisites ⚙️

Before running the project, you need to have Python 3.6+ installed. You also need to install the required Python libraries.

Installation 🛠️

1. Clone the repository

2. Create a virtual environment (recommended)

3. Install dependencies

   This will install the necessary libraries, including Flask, TensorFlow, and Keras.

Usage 🚀

1. Run the Flask web application:

   Once the dependencies are installed and the model is ready, you can start the web application:

   python app.py

2. Access the application:

   Open a web browser and navigate to:

   http://127.0.0.1:5000
   

   You will be able to upload images, and the app will predict the class of the image using the trained model.

See it in Action!! 🌸

2024-11-12_22-01-32.mov