metadata

title: Line Follower PID
emoji: 🚁
colorFrom: blue
colorTo: indigo
sdk: streamlit
sdk_version: 1.41.1
app_file: app.py
pinned: false

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

Line Follower UI

A real-time line detection application using webcam input, built with Streamlit and OpenCV.

Description

This application provides a user-friendly interface for real-time line detection using your webcam. It leverages computer vision techniques to detect lines within a specified color range and offers multiple methods for line estimation. The application is built using Streamlit for the frontend and OpenCV for image processing.

Key features:

Real-time webcam video processing
Interactive HSV color range adjustment
Multiple line detection algorithms:
- Hough Lines
- Adaptive Hough Lines
- Rotated Rectangle
- Fit Ellipse
- RANSAC Line
Customizable region of interest
Confidence estimation for line detection
Display of processed video or binary mask

Installation

Clone this repository:

git clone https://github.com/yourusername/line_follower_ui.git
cd line_follower_ui

Install the required dependencies:

pip install -r requirements.txt

Usage

Run the Streamlit application:

streamlit run app.py

Allow access to your webcam when prompted.
Use the sidebar controls to:
- Adjust HSV color thresholds to isolate your line color
- Select the line detection method
- Modify the region of interest size
- Toggle between the processed image and the binary mask
Click "Apply Settings" to update the detector with your chosen parameters.

Adjusting HSV Values

The HSV color space consists of three components:

Hue: The color type (such as red, blue, or yellow)
Saturation: The vibrancy of the color (from gray to full color)
Value: The brightness of the color (from black to full brightness)

To detect a specific color:

Adjust the Hue sliders to select the color range
Adjust Saturation to set how pure the color should be
Adjust Value to set how bright the color should be
Use the "Show Mask" option to see which pixels are being detected

Line Detection Methods

The application offers various line detection methods, each with its own strengths:

Hough Lines: Standard method for detecting straight lines
Adaptive Hough Lines: Automatically adjusts parameters based on image conditions
Rotated Rectangle: Fits a minimum area rectangle to detected contours
Fit Ellipse: Fits an ellipse to detected contours, useful for curved lines
RANSAC Line: Robust method that handles outliers well, good for noisy images

Requirements

Python 3.7 or higher
Webcam
Dependencies listed in requirements.txt

Troubleshooting

If the webcam doesn't start, make sure you allow browser access to your camera
If you see "Failed to access webcam" error, check if another application is using your camera
For any line detection issues, try adjusting the HSV values or try different detection methods

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

OpenCV for image processing capabilities
Streamlit for the web interface
streamlit-webrtc for real-time video processing