catalinalopera / ObjectClassification-

This project demonstrates how to build and train a Convolutional Neural Network (CNN) using TensorFlow and Keras to classify images as pizza or not pizza. The model uses image augmentation techniques to improve generalization and prevent overfitting, and is suitable for beginner-level computer vision tasks.

🍕 Pizza vs No Pizza - Image Classification with CNN

📌 About

This project demonstrates how to build and train a Convolutional Neural Network (CNN) using TensorFlow and Keras to classify images as pizza or not pizza. It applies basic image augmentation techniques to improve generalization and prevent overfitting. This is an ideal beginner-friendly computer vision project.

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🚀 Features

• Binary image classification: pizza vs no pizza
• Image augmentation using ImageDataGenerator
• CNN model with dropout to reduce overfitting
• Live visualization of training accuracy and loss
• Easily extendable to other binary classification problems

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🧰 Technologies Used

• Python 3.x
• TensorFlow / Keras
• NumPy
• Matplotlib
• Google Colab / Jupyter Notebook / VSCode / Kaggle

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🗂️ Dataset Structure

The dataset should be organized as follows:

data/ train/ pizza/ no_pizza/ test/ pizza/ no_pizza/