LETR (Line Segment Detection)

What is LETR (Line Segment Detection) ?

LETR (Line Segment Detection) is a transformer-based model designed for detecting line segments in images. It leverages advanced deep learning techniques to identify and segment lines with high accuracy. This tool is particularly useful for applications in computer vision, image processing, and geometry analysis.

Features

• Transformer-Based Architecture: Utilizes the power of transformer models for accurate line detection. • High Accuracy: Detects both straight and curved lines with precision. • Real-Time Processing: Capable of processing images quickly for immediate results. • Multiple Line Support: Can detect and segment multiple lines within an image. • Image Format Compatibility: Works with various image formats, including JPEG, PNG, and BMP.

How to use LETR (Line Segment Detection) ?

1. Install the Package: Use pip to install the LETR library.

   pip install letr-library
   

2. Import LETR in Your Script:

   from letr import LineSegmentDetector
   

3. Load Your Image:

   image = cv2.imread("your_image.jpg")
   

4. Initialize and Detect Lines:

   detector = LineSegmentDetector()
   lines = detector.detect(image)
   

5. Visualize the Results:

   detector.draw_lines(image, lines)
   cv2.imshow("Result", image)
   cv2.waitKey(0)
   

Frequently Asked Questions

What makes LETR different from traditional line detection methods?
LETR uses a transformer-based architecture that captures global context in images, enabling better accuracy and robustness compared to traditional edge-based methods like Canny edge detection.

Which image formats does LETR support?
LETR supports JPEG, PNG, BMP, and other standard image formats. Ensure your image is in one of these formats for optimal performance.

Can LETR be used for real-time applications?
Yes, LETR is optimized for real-time processing with fast inference times, making it suitable for applications like ** OBJECT detection**, robotics, and autonomous systems.