https://github.com/wassimoubaziz/image-classifier
This is a simple web application that allows users to upload an image and classify its contents using the MobileNet machine learning model.
https://github.com/wassimoubaziz/image-classifier
classification image image-classification machine-learning ml5 ml5js oubaziz wassim
Last synced: 3 months ago
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This is a simple web application that allows users to upload an image and classify its contents using the MobileNet machine learning model.
- Host: GitHub
- URL: https://github.com/wassimoubaziz/image-classifier
- Owner: wassimOubaziz
- License: mit
- Created: 2024-02-17T05:16:50.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-02-17T05:24:00.000Z (over 1 year ago)
- Last Synced: 2025-01-20T01:27:09.940Z (5 months ago)
- Topics: classification, image, image-classification, machine-learning, ml5, ml5js, oubaziz, wassim
- Language: HTML
- Homepage: https://wassimoubaziz.github.io/image-classifier/
- Size: 353 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Image Classification Web App
This is a simple web application that allows users to upload an image and classify its contents using the MobileNet machine learning model.
## Features
- Allows users to upload an image file.
- Utilizes the MobileNet model from the ml5.js library to classify the contents of the uploaded image.
- Displays the uploaded image and the classification result.
## Demo
You can try out the live demo [here](https://wassimoubaziz.github.io/image-classifier/).
## Installation
1. Open `index.html` in your web browser or host the files on a web server.
## Usage
1. Open `index.html` in your web browser.
2. Click on the "Choose File" button and select an image file.
3. Wait for the classification result to appear.
## Dependencies
- Bootstrap 5
- ml5.js
- [Placeholder Image](./raccoon.jpg)
## License
This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.
## Acknowledgements
- ml5.js for providing the MobileNet model.
- Bootstrap for the responsive CSS framework.
## Contact
Feel free to connect with me on LinkedIn: [Wassim Oubaziz](https://www.linkedin.com/in/wassim-oubaziz/)
wassim oubaziz