https://github.com/zephyrusblaze/digitrecognizer
This repository contains a deep learning project that utilizes Convolutional Neural Networks (CNN) to build a digit recognizer using the MNIST dataset.
https://github.com/zephyrusblaze/digitrecognizer
cnn-keras convolutional-neural-networks deep-learning flask
Last synced: about 2 months ago
JSON representation
This repository contains a deep learning project that utilizes Convolutional Neural Networks (CNN) to build a digit recognizer using the MNIST dataset.
- Host: GitHub
- URL: https://github.com/zephyrusblaze/digitrecognizer
- Owner: ZephyrusBlaze
- License: mit
- Created: 2024-01-18T08:45:49.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2024-10-27T15:38:35.000Z (over 1 year ago)
- Last Synced: 2025-10-29T16:50:50.053Z (8 months ago)
- Topics: cnn-keras, convolutional-neural-networks, deep-learning, flask
- Language: Jupyter Notebook
- Homepage: https://zephyrusblaze.github.io/DigitRecognizer/
- Size: 3.52 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# CNN Digit Recognizer 🔢
This repository houses an exciting deep learning project employing Convolutional Neural Networks (CNN) to construct a digit recognizer using the MNIST dataset. The MNIST dataset comprises a vast collection of handwritten digit images.
## Dependencies 🛠️
Ensure you have the following packages installed with the specified versions:
- `numpy`
- `matplotlib`
- `tensorflow`
- `keras`
- `pillow` or `opencv-python`
## Usage 🚀
1. **Clone the repository** to your local machine:
```bash
git clone https://github.com/ZephyrusBlaze/DigitRecognizer.git
```
2. **Install required packages**:
```bash
pip install -r requirements.txt
```
3. **Run the Flask server**:
```bash
python server.py
```
4. **Access the web interface**:
Visit `http://localhost:5000` in your web browser.
5. **Draw a digit**:
In the provided interface, draw a digit, and the trained model will predict the corresponding digit.
🌐 **Alternatively, use the pre-trained model**:
Access the model at [https://ZephyrusBlaze.github.io/DigitRecognizer/](https://ZephyrusBlaze.github.io/DigitRecognizer/).
## Model Training 🧠
The repository includes code for training the CNN model using the MNIST dataset. The model architecture comprises convolutional layers, pooling layers, dropout layers, and dense layers. Augmentation techniques are applied to generate augmented images for training.
## License 📜
This project is licensed under the [MIT License](LICENSE).