Skip to main content
This is a pre-production deployment of Warehouse. Changes made here affect the production instance of PyPI (
Help us improve Python packaging - Donate today!

Computer Vision utilities, Cohen-Sutherland line clipping, OpenCV plot helpers for Optical Flow and Blob Analysis, AVI codec helpers

Project Description


Author:Michael Hirsch
Prereq:OpenCV 2 or OpenCV 3

Misc. algorithms useful for computer vision.


python develop

Fortran Build (optional)

If you want to use the Fortran Cohen-Sutherland line clipping modules directly (optional):

cd bin
cmake ..


The main difference with textbook implementations is that I return a sentinel value (NaN, None, nothing) if there’s no intersection of line with box.


import morecvutils.lineclipping as lc

x3,y3,x4,y4 = lc.cohensutherland((xmin, ymax, xmax, ymin, x1, y1, x2, y2)

If no intersection, (None, None, None, None) is returned.


lineclipping.f90 has two subroutines. Pick Ccohensutherland if you’re calling from C/C++/Python, which cannot tolerate assummed-shape arrays. It’s a slim wrapper to cohensutherland which is elemental (can handle scalar or any rank array).

Fortran programs will simply use

use lineclipping
call cohensutherland(xmin,ymax,xmax,ymin,x1,y1,x2,y2)

The arguments are:

xmin,ymax,xmax,ymin:  upper left and lower right corners of box (pixel coordinates)

in - endpoints of line
out - intersection points with box. If no intersection, all NaN


Simliar to Python, except nothing is returned if no intersection found.

cohensutherland(xmin, ymax, xmax, ymin, x1, y1, x2, y2)


function description
lineClipping.jl Cohen-Sutherland line clipping algorithm for Julia. Input scalars, output intersection length, or None if no intersection.
lineclipping.f90 Cohen-Sutherland line clipping algorithm for Fortran. Input scalars or arrays, output intersections. Cohen-Sutherland line clipping algorithm for Python. Input scalars, output intersection length, or None if no intersection.
draw_flow() given a 2-D complex Numpy array of optical flow flow, draw flow vectors with arrows
draw_hsv() make a colored HSV image corresponding to flow direction and intensity at each point given a binary image morphed and the blobdet from setupblob(), along with img, do connected components analysis using Horn-Schunck optical flow estimation with OpenCV in Python. Not so obvious from the docs, and with notes on how to make this match Matlab’s vision.opticalFlowHS method. Install Matlab Engine for Python

Release History

This version
History Node


History Node


History Node


Download Files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Filename, Size & Hash SHA256 Hash Help File Type Python Version Upload Date
(11.1 kB) Copy SHA256 Hash SHA256
Wheel 3.6 Feb 18, 2018
(7.4 kB) Copy SHA256 Hash SHA256
Source None Feb 18, 2018

Supported By

Elastic Elastic Search Pingdom Pingdom Monitoring Dyn Dyn DNS Sentry Sentry Error Logging CloudAMQP CloudAMQP RabbitMQ Heroku Heroku PaaS Kabu Creative Kabu Creative UX & Design Fastly Fastly CDN DigiCert DigiCert EV Certificate Google Google Cloud Servers