AI_Pet_Classifier

🐶 AI Pet Classifier using CNN

A deep learning application that classifies images of cats and dogs using a Convolutional Neural Network (CNN) built with TensorFlow and Keras.

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🐶🐱 AI Pet Classifier using Convolutional Neural Networks (CNN)

Overview

AI Pet Classifier is a deep learning project that classifies images as either Cat or Dog using a Convolutional Neural Network (CNN) built with TensorFlow and Keras. The model is trained on thousands of labeled pet images and predicts the class of unseen images with high accuracy.

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Features

• Binary Image Classification
• TensorFlow & Keras Implementation
• Data Augmentation
• Batch Normalization
• Image Preprocessing
• Model Saving & Loading
• Single Image Prediction
• Beginner-Friendly Notebook
• Google Colab Compatible

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Project Pipeline

Dataset
   │
   ▼
Image Preprocessing
   │
   ▼
Data Augmentation
   │
   ▼
CNN Model
   │
   ▼
Training
   │
   ▼
Evaluation
   │
   ▼
Prediction

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CNN Architecture

Input Layer (64×64×3)

↓

Conv2D (32 Filters)
↓

Batch Normalization
↓

MaxPooling

↓

Conv2D (64 Filters)
↓

MaxPooling

↓

Conv2D (128 Filters)
↓

MaxPooling

↓

Flatten

↓

Dense (128)

↓

Dense (1, Sigmoid)

↓

Prediction

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Technologies Used

• Python
• TensorFlow
• Keras
• NumPy
• Matplotlib
• Pillow
• Google Colab

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Dataset Structure

Data/

├── training_set/
│   ├── cats/
│   └── dogs/
│
└── test_set/
    ├── cats/
    └── dogs/

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Hyperparameters

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Training

The model uses image augmentation to improve generalization by applying:

• Rescaling
• Random Zoom
• Shear Transformation
• Horizontal Flip

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Prediction

The trained model predicts whether the uploaded image belongs to:

• 🐱 Cat
• 🐶 Dog

along with the prediction confidence.

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Future Improvements

• Early Stopping
• Model Checkpoint
• Transfer Learning (MobileNetV2 / EfficientNet)
• Confusion Matrix
• Classification Report
• Accuracy & Loss Curves
• Grad-CAM Visualization
• Streamlit & Hugging Face Deployment

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Repository Structure

├── CNN_Model.ipynb
├── cnn_model.keras
├── Data.zip
├── requirements.txt
├── README.md
└── LICENSE

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Author

Sudheer Muthyala

B.Tech (ECE)

Aspiring AI & Data Science Engineer

GitHub: https://github.com/M-Sudheer18

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License

This project is licensed under the MIT License.

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