Real-Time Object Detection Web Application

This web application demonstrates real-time object detection using TensorFlow.js and COCO-SSD (Common Objects in Context - Single Shot MultiBox Detector). It allows users to detect objects in live webcam feeds, uploaded images, or videos directly within their web browser.

Features

• Choose between webcam, image, or video input for object detection.
• Real-time detection of various objects with confidence scores.
• Capture screenshots of detected objects.
• Responsive design for different devices.

Demo

Include a GIF or screenshot of your web application in action here.

Technologies Used

• TensorFlow.js
• COCO-SSD model
• HTML/CSS/JavaScript
• (Add any other relevant technologies)

Getting Started

To run this application locally, follow these steps:

1. Clone this repository:

   git clone <repository-url>
   cd <repository-folder>

2. Open index.html in your web browser.

3. Choose the input type (webcam, image, or video) and click "Start Detection".

4. (Add any other necessary steps for setup/configuration)

Usage

• Select your preferred input type (webcam, image, or video).
• Click "Start Detection" to initiate object detection.
• Use the "Stop Detection" button to pause or stop detection.
• Capture screenshots using the "Capture Screenshot" button.

Contributing

Contributions are welcome! Please fork this repository and submit a pull request with your improvements.

License

This project is licensed under the MIT License.