Confusion Matrix Generator

An open-source Streamlit web app to generate beautiful confusion matrices for multi-class machine learning models. Supports numeric and string labels, CSV upload, manual label entry, custom color maps, and displays evaluation metrics like Accuracy, Precision, Recall, and F1-score. Users can download the confusion matrix as an image.

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✨ Features

• Confusion matrices for binary & multi-class models
• Numeric and string label support
• CSV upload or manual input
• Custom color maps
• Accuracy, Precision, Recall & F1-score
• Downloadable matrix image
• Open-source Streamlit web app

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🚀 Live Demo

Try the app live here:

🔗 https://confusion-matrix-gen.streamlit.app

No installation required — simply upload a CSV file or enter labels manually and generate confusion matrices instantly.

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🖥️ Run the App Locally (Step-by-Step)

Follow these steps to run the Confusion Matrix Generator on your local machine.

Step 1: Clone the Repository

Open your terminal and run:

git clone https://github.com/pareshrnayak/confusion-matrix-generator.git

Step 2: Move into the Project Directory

cd confusion-matrix-generator

Step 3: Install Dependencies

Make sure Python and pip are installed before running this command.

pip install -r requirements.txt

Virtual Environments (venv) are optional. This works without creating one.

Step 4: Run the Streamlit App

python -m streamlit run app.py

Step 5: Open in Browser

Once the app starts, you will see a local URL like:

http://localhost:8501

Open it in your browser to use the app.

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Project Structure

confusion-matrix-generator/
├── app.py                 # Main Streamlit application
├── requirements.txt       # Python dependencies
├── README.md              # Project overview
├── assets/
│   └── mockup.png         # UI mockup image
├── .gitignore             # Ignored files
└── LICENSE                # MIT License

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🤝 Contributing

Contributions, issues, and feature requests are welcome!
Feel free to fork this repo and submit a pull request.

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🧩 Open Source

This project is open-source and free to use under the MIT License.