Pet Face Classification using CNN

Overview

This project implements a Convolutional Neural Network (CNN) to classify pet face images. The model is trained using TensorFlow and demonstrates the complete deep learning workflow, including image preprocessing, model training, evaluation, and prediction.

The project provides hands-on experience in image classification and computer vision using deep learning techniques.

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Features

• Pet face image classification
• Image preprocessing
• CNN model training
• Model evaluation
• Prediction on unseen images

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Technologies Used

• Python
• TensorFlow
• Keras
• NumPy
• Matplotlib

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Project Structure

project-folder/
│
├── dataset/
├── model/
├── train.py
├── predict.py
├── requirements.txt
└── README.md

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Installation

Clone the repository

git clone https://github.com/YOUR_USERNAME/pet-face-classification-cnn.git

Move into the folder

cd pet-face-classification-cnn

Install dependencies

pip install -r requirements.txt

Run the training

python train.py

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Learning Outcomes

• Deep Learning
• Convolutional Neural Networks
• TensorFlow
• Image Classification
• Dataset Preprocessing
• Model Evaluation

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Future Improvements

• Improve model accuracy
• Add more pet categories
• Deploy as a web application
• Mobile application integration

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Author

Meer

B.Tech Artificial Intelligence & Machine Learning Student