Metadata-Version: 2.1
Name: pyransac
Version: 1.1.1
Summary: A general random sample consensus (RANSAC) package
Home-page: https://github.com/MeelonUsk/pyransac
Author: Adam Morrissett
Author-email: me@adamlm.com
License: UNKNOWN
Description: ![](https://github.com/MeelonUsk/pyransac/workflows/Continuous%20Integration/badge.svg)
        [![codecov](https://codecov.io/gh/MeelonUsk/pyransac/branch/master/graph/badge.svg)](https://codecov.io/gh/MeelonUsk/pyransac)
        [![Documentation Status](https://readthedocs.org/projects/pyransac/badge/?version=latest)](https://pyransac.readthedocs.io/en/latest/?badge=latest)
        
        # `pyransac` package
        This package is a general random sample consensus (RANSAC) framework. For
        convenience, some data models (such as a straight line) are already provided.
        However, you are free to define your own data models to remove outliers from
        arbitrary data sets using arbitrary data models.
        
        # General usage
        There are two main components to this package: the RANSAC estimator and a
        data model. When calling the estimation function `find_inliers`, you need to
        specify the model to which you expect your data to fit.
        
        A data model is class containing the model parameters and an error function 
        against which you can test your data. Each data model must implement the
        interface defined by the `Model` base class. In other words, you need to
        implement the `make_model` and `calc_error` functions.
        
        Additionally, you need to provide parameters for the RANSAC algorithm. These 
        parameters are contained in the `RansacParams` class.
Keywords: random sample consensus ransac
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7
Description-Content-Type: text/markdown
