Скачать или смотреть Using OpenCV and Python 3 for neuroscience 1.6: SEMI automatic detection with GUI interface.

In this series we will use Python and OpenCV to help analyse simple behavioural experiments that are commonly used in neuroscience research.

In this video I show how we can use a GUI window to coordinate the analysis of a typical behavioural experiment. I used QtDesigner (QtPy5 for Python) to create most of the GUI elements and set the layout. Once I created the widget (MainWindow), I then set about getting the video file and video parameters as we have seen in our previous videos in this series.

The user now has the ability to set the start position, analysis time increment and set a save file all from a single window. Additionally, the user is able to define special points of interest in their arena (in this case, the corners of the arena and the location of a visual cliff – which is not present in this particular setup). All of this information, as well as the animals X,Y position will be saved into the file they create.

The actual, step-by-step analysis of the position of the subject (beetle in this case) uses exactly the same mouse call back and event calls as the previous video.

Disclaimer.
This is not designed to be a complete Python or OpenCV programming course. However I hope it will be helpful to generate some ideas into how to approach behavioural experiment analyses. The solutions presented in these videos are not definitive, but rather identify one of many potential solutions. I encourage you to find better and more elegant solutions.

Software used in these videos
Python (for windows) : http://python.org
Opencv: https://opencv.org/ Using pip installer: https://pypi.org/project/opencv-python/
Psychopy: http://psychopy.org
Atom Editor: http://atom.io
I hope these videos are helpful.