Metadata-Version: 2.1
Name: oflibnumpy
Version: 1.0.0
Summary: Optical flow library using a custom flow class based on NumPy arrays
Home-page: https://github.com/RViMLab/oflibnumpy
Author: Claudio S. Ravasio
Author-email: claudio.s.ravasio@gmail.com
License: MIT
Project-URL: Documentation, https://oflibnumpy.rtfd.io
Project-URL: Source, https://github.com/RViMLab/oflibnumpy
Project-URL: Tracker, https://github.com/RViMLab/oflibnumpy/issues
Description: Introduction
        ============
        Oflibnumpy: a handy python **o**\ ptical **f**\ low **lib**\ rary, based on **NumPy** arrays, that enables the manipulation and
        combination of flow fields while keeping track of valid areas (see "Usage"). It is mostly code written from scratch,
        but also contains useful wrappers for specific functions from libraries such as OpenCV's ``remap``, to integrate them
        with the custom flow field class introduced by oflibnumpy. Features:
        
        - Provides a custom flow field class for both backwards and forwards ('source' / 'target' based) flow fields
        - Provides a number of class methods to create flow fields from lists of affine transforms, or a transformation matrix
        - Provides a number of functions to resize the flow field, visualise it, warp images, find necessary image padding
        - Allows for three different types of flow field combination operations
        - Keeps track of valid flow field areas through said operations
        
        Note there is an equivalent flow library called Oflibpytorch, mostly based on PyTorch tensors. Its
        `code is available on Github`_, and the `documentation is accessible on ReadTheDocs`_.
        
        .. _code is available on Github:  https://github.com/RViMLab/oflibpytorch
        .. _documentation is accessible on ReadTheDocs: https://oflibpytorch.rtfd.io
        
        
        Usage & Documentation
        ---------------------
        A user's guide as well as full documentation of the library is available at ReadTheDocs_. Some quick examples:
        
        .. _ReadTheDocs: https://oflibnumpy.rtfd.io
        
        .. code-block:: python
        
            import oflibnumpy as of
        
            # Make a flow field and display it
            shape = (300, 400)
            flow = of.Flow.from_transforms([['rotation', 200, 150, -30]], shape)
            flow.show()
        
        .. image:: https://raw.githubusercontent.com/RViMLab/oflibnumpy/main/docs/_static/flow_rotation.png
          :width: 200
          :alt: Visualisation of optical flow representing a rotation
        
        .. code-block:: python
        
            # Combine sequentially with another flow field, display the result
            flow_2 = of.Flow.from_transforms([['translation', 40, 0]], shape)
            result = of.combine_flows(flow, flow_2, mode=3)
            result.show(show_mask=True, show_mask_borders=True)
        
        .. image:: https://raw.githubusercontent.com/RViMLab/oflibnumpy/main/docs/_static/flow_translated_rotation.png
          :width: 200
          :alt: Visualisation of optical flow representing a rotation, translated to the right
        
        .. code-block:: python
        
            result.show_arrows(show_mask=True, show_mask_borders=True)
        
        .. image:: https://raw.githubusercontent.com/RViMLab/oflibnumpy/main/docs/_static/flow_translated_rotation_arrows.png
          :width: 200
          :alt: Visualisation of optical flow representing a rotation, translated to the right
        
        
        Installation
        ------------
        Oflibnumpy is based on Python>=3.7. Install it by running:
        
        .. code-block::
        
            pip install oflibnumpy
        
        
        Contribution & Support
        ----------------------
        - Source Code: https://github.com/RViMLab/oflibnumpy
        - Issue Tracker: https://github.com/RViMLab/oflibnumpy/issues
        
        
        License
        -------
        Copyright (c) 2021 Claudio S. Ravasio, PhD student at University College London (UCL), research assistant at King's
        College London (KCL), supervised by:
        
        - Dr Christos Bergeles, PI of the Robotics and Vision in Medicine (RViM) lab in the School of Biomedical Engineering &
          Imaging Sciences (BMEIS) at King's College London (KCL)
        - Prof Lyndon Da Cruz, consultant ophthalmic surgeon, Moorfields Eye Hospital, London UK
        
        This code is licensed under the `MIT License`_.
        
        .. _MIT License: https://opensource.org/licenses/MIT
Keywords: optical flow,flow,flow field,flow composition,flow combination,flow visualisation
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.7
Description-Content-Type: text/x-rst
