Object Detection Streamlit

What is Object Detection Streamlit ?

Object Detection Streamlit is a Streamlit-based application designed to detect objects in images, videos, or live webcam feeds. It leverages cutting-edge AI models to provide real-time object tracking and detection capabilities.

Features

• Object Detection in Images: Analyze static images to identify and label objects. • Object Detection in Videos: Process video files to track objects across frames. • Live Webcam Feed Support: Detect objects in real-time using your device's webcam. • Customizable Models: Use pre-trained AI models or integrate custom models for specific use cases. • Cross-Platform Compatibility: Runs seamlessly on Windows, macOS, and Linux. • User-Friendly Interface: Intuitive UI for easy interaction and configuration.

How to use Object Detection Streamlit ?

1. Install the Streamlit App: Run pip install streamlit to install Streamlit and its dependencies.
2. Clone or Download the Repository: Access the Object Detection Streamlit codebase from its repository.
3. Run the Application: Execute the app using streamlit run your_script.py (replace with the actual script name).
4. Upload Media or Use Webcam: Choose an image, video file, or enable the webcam feed for detection.
5. View Results: The app will display detected objects with bounding boxes and labels in real-time.

Frequently Asked Questions

1. What formats of images and videos are supported?
Object Detection Streamlit supports common formats like JPG, PNG, and MP4. For videos, most codecs compatible with OpenCV are accepted.

2. Can I use my webcam for live detection?
Yes! Enable the webcam option in the app to detect objects in real-time. Ensure your browser or environment allows webcam access.

3. How can I customize the AI model for better accuracy?
You can integrate custom-trained models by modifying the model path in the code or using popular libraries like TensorFlow or PyTorch for advanced customization.