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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