pyvision3

A python3 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
• Draw/create points and polygons in images
• Generate defined or random rectangular crops/tiles in images
• Select good vs. bad tiles in a montage "tile picker" display

Displaying results:

• 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

Video processing:

• 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.

Installation

• python >= 3.6

Then install using pip:

pip install pyvision3

You may also clone the repo and install in development mode. After cloning, change to the project directory and install via:

pip install -e .

Examples

Please view the "examples" directory of the repository for several helpful examples.

The following are some simple code samples to give you the flavor of the library.

import pyvision3 as pv3

#load and display an image
img = pv3.Image("path/to/somefile.jpg")
img.show()

#annotate the image
img.annotate_text("Waldo was here", (254, 246), color=(0, 0, 255), bg_color=(255, 255, 255))
img.show()  # by default uses an opencv highgui window for display
img.imshow()  # will use a matplotlib figure, optional arguments are the same as img.show()

#annotations are on a separate layer, original data is still there
img.show(annotations=False)

#load and play a video or webcam
vid = pv3.Video("path/to/somevideo.mov")
vid.play()  #supports pausing and single-frame advance

#We can control the position of playback in the video
vid.play(start_frame=150, end_frame=400)

#or you can treat a video as an iterator
for img in vid:
	print(vid.current_frame_number)
	img.show(delay=25) #25ms delay between frames


#motion detection
md = pv3.MotionDetector(method=pv3.BG_SUBTRACT_FRAME_DIFF, buff_size=5, thresh=80)
for img in vid:
    md.detect(img)
    out = md.annotate_frame()
    if out is not None:
        out.show(delay=25)

Main Contributors to Pyvision3

Stephen O'Hara

Main Contributors to the original Pyvision

1. David Bolme
2. Stephen O'Hara

Backwards Compatibility

Pyvision3 is not (necessarily) designed to be backwards compatible to earlier versions of Python and OpenCV. For those developing with Python 2.7, I suggest continuing to use the original Pyvision code, which can be found on github.