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README.md

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+---
+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.
+
+---
+
+⭐ If you found this project helpful, consider giving it a star.