https://github.com/wassimoubaziz/object-detection
Welcome to the Object Detection Web App! This project leverages the power of machine learning to detect objects in images using the ml5.js library. 🖼️🤖
https://github.com/wassimoubaziz/object-detection
ai artificial-intelligence js machine-learning object-detection oubaziz wassim
Last synced: 3 months ago
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Welcome to the Object Detection Web App! This project leverages the power of machine learning to detect objects in images using the ml5.js library. 🖼️🤖
- Host: GitHub
- URL: https://github.com/wassimoubaziz/object-detection
- Owner: wassimOubaziz
- License: mit
- Created: 2024-02-18T19:16:44.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-02-18T19:29:21.000Z (over 1 year ago)
- Last Synced: 2025-01-20T01:27:11.633Z (5 months ago)
- Topics: ai, artificial-intelligence, js, machine-learning, object-detection, oubaziz, wassim
- Language: JavaScript
- Homepage: https://wassimoubaziz.github.io/object-detection/
- Size: 85 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Object Detection Web App
Welcome to the Object Detection Web App! This project leverages the power of machine learning to detect objects in images using the ml5.js library. 🖼️🤖
## Overview
The Object Detection Web App utilizes advanced algorithms to analyze images and identify various objects present within them. Whether you're exploring computer vision or building intelligent applications, this app provides an interactive platform to understand object detection techniques. 💡👀
### Key Features:
- **Object Detection:** Automatically detects and labels objects within uploaded images.
- **Interactive Interface:** User-friendly interface for seamless interaction.
- **Powered by ml5.js:** Utilizes the ml5.js library for machine learning tasks.
- **Real-time Analysis:** Provides instant feedback on object detection results.
## Technologies Used:
- HTML
- CSS
- JavaScript (ml5.js)
## How to Use:
1. Upload an image using the "Upload" button.
2. Wait for the app to process the image and display the detected objects.
3. Explore the labeled objects and their corresponding confidence levels.
## Demo:
[Explore the Object Detection Web App](https://wassimoubaziz.github.io/object-detection/) - Add link to your deployed object detection app.
## Contribute:
Contributions are welcome! If you have ideas for improvements, additional features, or bug fixes, feel free to open an issue or submit a pull request. 🛠️
Wassim Oubaziz
## Feedback:
Share your experience using the Object Detection Web App. If you encounter any issues or have suggestions for enhancements, connect with me on [LinkedIn](#) or open an issue. 📈
Enjoy detecting objects with the Object Detection Web App! 🖼️🔍