opencv-pg 1.0.0

Qt5 GUI Application for realtime exploration of OpenCV functions

OpenCV Playground

The OpenCV Playground is a Qt5 application that brings together improved documentation alongside OpenCV functions with the ability to explore the effects of function parameters on an image in real time.

It also comes with a custom Pipeline Launcher that allows you to build and interact with your own sequence of image transformations.

Full documentation can be found on Read the Docs.

Demo

Installation

Currently tested with python 3.7.4 and opencv-headless-4.4.0.46

From PyPi:

pip install opencv-pg

From Github Repo:

pip install git+https://github.com/opencv-pg/opencv-pg

Usage

Playground

To launch the OpenCV Playground with:

• The built-in image:

opencvpg

• An image of your choice:

opencvpg --image <path-to-image.png>

• Without the documentation window:

opencvpg --no-docs

Custom Pipeline

The following is an example of building a custom Pipeline.

from opencv_pg import Pipeline, Window, launch_pipeline
from opencv_pg import support_transforms as supt
from opencv_pg import transforms as tf

if __name__ == '__main__':
    my_image = '/path/to/image.png'

    # Creates two windows
    pipeline = Pipeline([
        Window([
            supt.LoadImage(my_image),
            supt.CvtColor(),
            tf.InRange(),
            supt.BitwiseAnd(),
        ]),
        Window([
            tf.Canny(),
        ]),
    ])

    launch_pipeline(pipeline)

Then run the file.

Development

Installation

To install in development mode:

git clone https://github.com/opencv-pg/opencv-pg
pip install -e opencv-pg/[dev]

Running Tests

cd tests
pytest

Generating Docs

• Go into the top level docs directory
• run sphinx-apidoc -f -o source/ ../src/opencv_pg
• run make html

Output will be in the docs/build/html/ directory.

Changes

1.0.0

• Initial Release