Facilitates computer vision research and prototyping using python and openCV
A python 3 computer vision library that complements OpenCV 3.x to add many useful features for developers and researchers alike. Pyvision provides utilities that help in these core areas: training data preparation, displaying results, and applying vision algorithms to video streams.
Training data preparation:
Apply affine transformations
Label points and polygons in images
Generate defined or random crops in images
Select good vs. bad tiles in a montage display
Easy and powerful image annotations of shapes, lines, text, and overlay masks
Compatible with shapely – annotate shapely polygons to images
Annotations are kept on a separate layer from the underlying image
Display the image and save images with or without annotations
Show results in an “image montage” – multiple images or tiles shown in a grid
Use image montage to select results (or to provide manual QA on the results)
Play back sequences of images like a video, with pause-and-play interface
Pyvision Video class makes it easy to view and process common video files (avi, mpg, etc.), directories of images, or live streams from USB or IP cameras.
Video objects are iterators. `for frame in vid: ...`
Create videos of your results, save a sequence of results as an avi file, for example. Simple and pythonic!
Apply background subtraction and motion detection to your video streams. Several common algorithms included or invent your own.
Video interface provides ability to buffer the video, to pause playback, to step through frame-by-frame, to resume playing with a certain per-frame delay, etc.
Video montage allows you to display multiple videos side-by-side in lockstep! And save the result as another video!
Register a call-back with a video object to allow you to process each frame with your own encapsulated code.
Create an image buffer from images or video
Treat image buffer as a 3D array of grayscale images, or display as a montage
Pyvision3 is intended to be a successor to Pyvision that takes advantage of OpenCV 3.x and Python 3.x features. Huge thanks to David Bolme for being the originator of Pyvision. Many of the ease-of-use and interface ideas from the original Pyvision are carried forward, albeit with new implementations for Pyvision3.
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