https://github.com/smaranjitghose/image-classifier-ml5
A template for creating a client side image classification application with ML5.JS
https://github.com/smaranjitghose/image-classifier-ml5
css html image-classification javascript ml5
Last synced: 2 months ago
JSON representation
A template for creating a client side image classification application with ML5.JS
- Host: GitHub
- URL: https://github.com/smaranjitghose/image-classifier-ml5
- Owner: smaranjitghose
- License: mit
- Created: 2024-12-24T06:31:02.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-12-24T06:55:22.000Z (over 1 year ago)
- Last Synced: 2024-12-24T07:39:26.128Z (over 1 year ago)
- Topics: css, html, image-classification, javascript, ml5
- Language: JavaScript
- Homepage: https://img-m5-class.netlify.app/
- Size: 0 Bytes
- Stars: 5
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.MD
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
Awesome Lists containing this project
README
# 🖼️ Image Classifier using ML5.js
An interactive web application that uses ML5.js and MobileNet to classify images. The application features a modern dark theme and provides real-time image classification with confidence scores.
## 🌟 Features
- Real-time image classification using MobileNet
- Drag and drop file upload support
- Modern dark theme interface
- Visual confidence scores
- Responsive design
- Support for multiple image formats
- Interactive loading states
## 🚀 Demo
[Live Demo](https://img-m5-class.netlify.app/)
**Input**
**Output**
## 🛠️ Technologies Used
- HTML5
- CSS3
- JavaScript
- ML5.js
- MobileNet Model
## 📦 Installation
1. Clone the repository:
```bash
git clone https://github.com/your-username/Image-Classifier-ML5.git
```
2. Navigate to the project directory:
```bash
cd Image-Classifier-ML5
```
3. Open the project:
- Open `index.html` in your web browser
- Or use a local development server:
```bash
python -m http.server 8000
```
Then visit `http://localhost:8000`
## 💻 Usage
1. Wait for the MobileNet model to load
2. Upload an image by:
- Clicking the upload button
- Dragging and dropping an image
3. View the classification results with confidence scores
4. Use the "Try Another Image" button to classify more images
## 🤝 Contributing
Contributions, issues, and feature requests are welcome! Feel free to check the [issues page](https://github.com/smaranjitghose/image-classifier-ml5/issues).
## 📝 License
This project is [MIT](LICENSE) licensed.
## 👤 Author
Your Name
- GitHub: [@smaranjitghose](https://github.com/smaranjitghose)
- LinkedIn: [Smaranjit Ghose](https://www.linkedin.com/in/smaranjitghose/)