laneatt

Name	laneatt JSON
Version	2.4.5 JSON
	download
home_page	https://github.com/PaoloReyes/RealTime-LaneATT
Summary	A package to detect lane lines in images and videos
upload_time	2024-11-23 06:43:55
maintainer	None
docs_url	None
author	Paolo Reyes
requires_python	None
license	MIT
keywords	lanes ai greenhouse regression machine learning laneatt delimitations
VCS
bugtrack_url
requirements	No requirements were recorded.
Travis-CI	No Travis.
coveralls test coverage	No coveralls.

            
  LaneATT is a Python library for detecting lanes from images or videos, utilizing a state-of-the-art deep neural network. It is designed to be efficient and accurate, making it suitable for real-world applications such as autonomous vehicles, robotics, and surveillance systems.

  Features:
      Lane Detection: Accurate lane detection using a cutting-edge deep learning model
      Image/Video Support: Supports both image and video input formats
      Configurable Model: Customize the model architecture through configuration files
      ModelCheckpointing: Automatically saves model checkpoints at regular intervals
      Inference Speed: Optimized for fast inference on GPUs, ideal for real-time applications

  Usage:
      LaneATT can be used in various scenarios, such as:
          Autonomous Vehicles: Lane detection is crucial for self-driving cars to navigate roads safely.
          Surveillance Systems: Lane detection can be used to improve the accuracy of traffic monitoring systems.
          Robotics: Lane detection can help robots navigate through environments with lanes.

  To install LaneATT, run:

  pip install laneatt

  For more information, please visit [github repo](https://github.com/PaoloReyes/RealTime-LaneATT).
  

            

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