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            "Programming Language :: Python :: 3.7",
            "Programming Language :: Python :: 3.8",
            "Topic :: Scientific/Engineering :: Visualization"
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        "description": "[![image](https://zenodo.org/badge/19711552.svg)](https://zenodo.org/badge/latestdoi/19711552)\n\n[![Build Status](https://travis-ci.org/scivision/morecvutils.svg?branch=master)](https://travis-ci.org/scivision/morecvutils)\n[![Python versions (PyPI)](https://img.shields.io/pypi/pyversions/morecvutils.svg)](https://pypi.python.org/pypi/morecvutils)\n[![Downloads](https://pepy.tech/badge/morecvutils)](https://pepy.tech/project/morecvutils)\n\n# CVutils\n\nUses Python with\n[OpenCV](https://scivision.co/category/opencv/)\nin miscellaneous demos of algorithms useful for computer vision.\n\nNote: Line clipping was [moved to its own repo](https://github.com/scivision/lineclipping-python-fortran).\n\n## Install\n\n```sh\npython -m pip install -e .\n```\n\n## Functions\n\n* draw_flow()  given a 2-D complex Numpy array of optical flow `flow`, draw flow vectors with arrows\n* draw_hsv() make a colored HSV image corresponding to flow direction and intensity at each point\n* connectedComponents.py  given a binary image `morphed` and the `blobdet` from `setupblob()`, along with `img`, do connected components analysis\n* OpticalFlow_Matlab_vs_Python.py   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](https://scivision.co/opencv-cv-calcopticalflowhs-horn-schunck-smoothness-lambda-parameter/). [Install Matlab Engine for Python](https://scivision.co/matlab-engine-callable-from-python-how-to-install-and-setup/)",
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