Dog and Cat Image Classifier

This project is a machine learning model that detects images of dogs and cats and predicts the image as either a dog or a cat. It uses the Keras library on top of TensorFlow to create a convolutional neural network (CNN) model that can accurately classify the images.

Dataset

The dataset used in this project is the Dogs & Cats Dataset dataset from Kaggle. It consists of 30,000 labeled images of dogs and cats, with 15,000 images of each animal. The images are of different sizes and aspect ratios, and are in JPG format.

Tech Stack

• Flask
• Reactjs
• Python
• Keras
• TensorFlow
• NumPy

Deployment : Click here

Jupyter Notebook : Click Here

Usage

To run the application, clone this repository and install the required dependencies.

# To install Backend Dependencies
cd backend
pip install -r requirements.txt

# To install Frontend Dependencies
cd client
npm install

Run the Commands below in different terminals from the root directory to start the development server.

# To start the Flask Backend
npm run backend

# To start the React Frontend
npm run client

The trained model achieved an accuracy of 82.45% on the test set. Below are some sample demonstrations made by the model:

Video-Sat-Apr-29-2023-18-23-36.webm

😍 Valuable Contributors

Thanks to these wonderful people ✨

💙 Happy Contributions !! 💙

📝 Feedback

If you have any feedback, please reach out to me at pooranjoy@gmail.com

📜 License

Distributed under the MIT License. GNU