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https://github.com/samarthgarge/mnist_classification

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Host: GitHub
URL: https://github.com/samarthgarge/mnist_classification
Owner: SamarthGarge
Created: 2024-09-14T06:54:44.000Z (4 months ago)
Default Branch: main
Last Pushed: 2024-09-18T04:00:11.000Z (4 months ago)
Last Synced: 2024-09-18T07:01:33.932Z (4 months ago)
Language: Jupyter Notebook
Size: 3.53 MB
Stars: 0
Watchers: 1
Forks: 0
Open Issues: 0
Metadata Files:
- Readme: README.md

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README

        # 📷 MNIST Digit Classifier

Welcome to **MNIST Digit Classifier**, a digit classification app powered by advanced machine learning models.

## 🌟 Features

  

- **MNIST Digit Classifier**: Accurately predicts handwritten digits from 0 to 9. 🧮

- **Interactive & Intuitive UI**: 🖥️ A modern, sleek user interface designed for easy navigation and enhanced user experience, with a dark theme option and custom animations.

- **Real-time Predictions**: 💡 Upload your image and get an instant prediction with the corresponding confidence score.

- **Model Comparison**: 📊 Evaluate the performance of both models through accuracy metrics and confidence levels for each prediction.

- **Advanced Technology**: Leveraging cutting-edge machine learning algorithms including CNNs (Convolutional Neural Networks) for high accuracy image and digit predictions.

## 🔥 Live Demo

- **MNIST Digit Classifier**: [![Open in Streamlit](https://static.streamlit.io/badges/streamlit_badge_black_white.svg)](https://predictadigit.streamlit.app/)

## 🖼️ Preview

### MNIST Digit Classification

![DigiPic-Classifier Screenshot](https://github.com/user-attachments/assets/07b2da72-ab12-4b1e-a34a-eb7ea2a8f7e4)

![DigiPic-Classifier Screenshot](https://github.com/user-attachments/assets/5bd05631-063f-4a91-8a5c-6c17ea223734)

---

## 🚀 How to Use DigiPic-Classifier

---

### **MNIST Digit Classification App**

1. **Clone the Repository**:

   ```bash

   git clone https://github.com/SamarthGarge/MNIST_Classification.git

   ```

2. **Navigate to MNIST App Directory**:

   ```bash

   cd SamarthGarge/MNIST_Classification/mnist_classification

   ```

3. **Install the Required Dependencies**:

   ```bash

   pip install -r requirements.txt

   ```

4. **Run the MNIST Streamlit App**:

   ```bash

   streamlit run app.py

   ```

5. **Open the App**: Open your browser and go to `http://localhost:8501` to use the MNIST Digit Classification app. 

--- 

## 📈 Future Enhancements

- Adding more sophisticated image classification models.

- Deploying MNIST Classifier live for broader accessibility.

- Implementing additional UI improvements and advanced animations.