---
title: AI Pet Classifier
emoji: 🐶
colorFrom: blue
colorTo: indigo
sdk: streamlit
sdk_version: "1.46.1"
app_file: app.py
pinned: false
license: mit
---

# 🐶 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.

...

# 🐶🐱 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.

---

## 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

---

## Project Pipeline

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

---

## 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
```

---

## Technologies Used

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

---

## Dataset Structure

```
Data/

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

---

## Hyperparameters

| Parameter | Value |
|------------|-------|
| Image Size | 64 × 64 |
| Batch Size | 32 |
| Epochs | 25 |
| Optimizer | Adam |
| Loss Function | Binary Crossentropy |
| Activation | ReLU |
| Output Activation | Sigmoid |

---

## Training

The model uses image augmentation to improve generalization by applying:

- Rescaling
- Random Zoom
- Shear Transformation
- Horizontal Flip

---

## Prediction

The trained model predicts whether the uploaded image belongs to:

- 🐱 Cat
- 🐶 Dog

along with the prediction confidence.

---

## Future Improvements

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

---

## Repository Structure

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

---

## Author

**Sudheer Muthyala**

B.Tech (ECE)

Aspiring AI & Data Science Engineer

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

---

## License

This project is licensed under the MIT License.

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