https://github.com/vfdev-5/cv_interactive
Computer vision algorithms interactive with Jupyter Notebook
https://github.com/vfdev-5/cv_interactive
Last synced: about 1 year ago
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Computer vision algorithms interactive with Jupyter Notebook
- Host: GitHub
- URL: https://github.com/vfdev-5/cv_interactive
- Owner: vfdev-5
- Created: 2016-11-29T16:14:11.000Z (over 9 years ago)
- Default Branch: master
- Last Pushed: 2017-03-31T07:48:51.000Z (about 9 years ago)
- Last Synced: 2025-02-08T10:43:50.443Z (over 1 year ago)
- Language: Jupyter Notebook
- Size: 17.7 MB
- Stars: 0
- Watchers: 3
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Computer Vision interactive examples
A number of *jupyter notebooks* introducing basic computer vision algorithms and notions.
Some of notebooks are inspired by [OpenCV](https://github.com/opencv/opencv/blob/master/samples) samples and add an interactive part to get an intiution of how works a filter or algorithm.
## Requirements
* numpy
* matplotlib
* opencv3
* jupyter-notebook
**We use `interact` from jupyter, if there is no sliders in the interactive mode, see the warnings in your console.**
Click to the badge, to go into an interactive mode with [mybinder.org](http://mybinder.org) : [](http://mybinder.org:/repo/vfdev-5/cv_interactive)
## Content
* Gabor filter
* Image matching
* Deconvolution
* Geometric primitives