Introduction¶
Oflibnumpy: a handy python optical flow library, 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.
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.
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
Installation:
pip install oflibnumpy
Code example:
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()
# 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)
result.show_arrows(show_mask=True, show_mask_borders=True)
