https://github.com/alihassanml/fashion-mnist-prediction
This repository contains a Streamlit web application for classifying Fashion MNIST images using a deep learning model. The app allows users to upload images, preprocesses them, and predicts the class using a trained convolutional neural network (CNN).
https://github.com/alihassanml/fashion-mnist-prediction
Last synced: 6 months ago
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This repository contains a Streamlit web application for classifying Fashion MNIST images using a deep learning model. The app allows users to upload images, preprocesses them, and predicts the class using a trained convolutional neural network (CNN).
- Host: GitHub
- URL: https://github.com/alihassanml/fashion-mnist-prediction
- Owner: alihassanml
- License: mit
- Created: 2024-08-17T09:13:40.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2024-08-17T09:39:04.000Z (about 1 year ago)
- Last Synced: 2025-02-16T01:12:45.412Z (8 months ago)
- Language: Jupyter Notebook
- Size: 8.13 MB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Fashion MNIST Image Classification
This repository contains a Streamlit web application for classifying Fashion MNIST images using a deep learning model. The app allows users to upload images, preprocesses them, and predicts the class using a trained convolutional neural network (CNN).
## Features
- **Upload an image:** Users can upload images in PNG, JPG, or JPEG format.
- **Image preprocessing:** The uploaded image is resized, converted to grayscale, normalized, and reshaped to match the input shape expected by the model.
- **Prediction:** The app uses a trained CNN model to classify the image into one of the Fashion MNIST classes.
- **Download processed image:** The app also allows users to download the preprocessed image.
## Demo
You can check out the app [here](#).
## Getting Started
### Prerequisites
- Python 3.x
- TensorFlow
- Streamlit
- PIL (Pillow)
- NumPy
### Installation
1. Clone the repository:
```bash
git clone https://github.com/alihassanml/Fashion-Mnist-Prediction.git
```
2. Install the required packages:
```bash
pip install -r requirements.txt
```
3. Run the Streamlit app:
```bash
streamlit run app.py
```
### Project Structure
```
fashion-mnist-prediction/
│
├── app.py # The main Streamlit app
├── requirements.txt # Python dependencies
└── README.md # Project documentation
```
### Usage
1. Upload an image through the Streamlit interface.
2. The app will preprocess the image and display it.
3. The app will predict the class of the image using the CNN model.
4. You can download the preprocessed image.
### Model
The model is a convolutional neural network trained on the [Fashion MNIST dataset](https://github.com/zalandoresearch/fashion-mnist). Ensure that the `model.h5` file is present in the root directory of the project.
### Acknowledgements
- [Fashion MNIST Dataset](https://github.com/zalandoresearch/fashion-mnist)
- [Streamlit](https://www.streamlit.io/)
## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.