Metadata-Version: 2.1
Name: laneatt
Version: 2.4.5
Summary: A package to detect lane lines in images and videos
Home-page: https://github.com/PaoloReyes/RealTime-LaneATT
Download-URL: https://github.com/PaoloReyes/RealTime-LaneATT/archive/refs/tags/LaneATT-v2.4.tar.gz
Author: Paolo Reyes
Author-email: paolo.alfonso.reyes@gmail.com
License: MIT
Keywords: Lanes,AI,Greenhouse,Regression,Machine Learning,LaneATT,Delimitations
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Build Tools
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.12
License-File: LICENSE
Requires-Dist: filelock
Requires-Dist: fsspec
Requires-Dist: Jinja2
Requires-Dist: joblib
Requires-Dist: MarkupSafe
Requires-Dist: mpmath
Requires-Dist: matplotlib
Requires-Dist: networkx
Requires-Dist: numpy
Requires-Dist: opencv-python
Requires-Dist: pillow
Requires-Dist: PyYAML
Requires-Dist: scikit-learn
Requires-Dist: scipy
Requires-Dist: setuptools
Requires-Dist: sympy
Requires-Dist: threadpoolctl
Requires-Dist: torch
Requires-Dist: torchaudio
Requires-Dist: torchvision
Requires-Dist: tqdm
Requires-Dist: typing_extensions
Requires-Dist: wheel


  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).
  
