This is the software for controlling the ant tracking setup, the work was done at the Murthy Lab at Harvard University.
conda install numpy pyqt qtpy h5py pyqtgraph pip install ScopeFoundry
PyDAQmx is used for controlling the National Instrument DAQ (which in turn controls the motors):
pip install PyDAQmx
OpenCV is used for loading avi video:
pip install opencv-python
You also need to install the driver and SDK, and Python binding PySpin for FLIR Point Grey cameras. They drivers, SDK and PySpin can be downloaded from the FLIR Spinnaker website
Clone this repository to your computer, modify the RunAntCam.bat file to
After you've modified the RunAntCam.bat, you can execute RunAntCam.bat to run the AntCam software with a command window, or execute RunAntCamQuiet.bat to run the software without a command window. You could create shortcut to these two files. The icon for AntCam is ant_icon.ico
To start AntCam, either start anaconda prompt, go to the directory of ant cam and type in
If you have more questions, please ask Hao Wu fullerene12 to get a tutorial of the software.
The analysis code was written in Jupyter Notebook. In Anaconda Prompt, type in:
To get the Jupyter Notebook server to start up.
In the base directory, use the notebook server to open video_analysis.ipynb, run the first cell, and set up the parameters in the second cell (e.g. file names and starting frame for data processing.). Output video will be saved at the same folder as the input data, in TIFF stacks.
There will be two output videos. zoomed_view.tif is the stablized closeup video of the moving ant. wide_view.tif is the video of the entire arena while tracking. The two video are synchronized.
- Hao Wu - Software Development - fullerene12
- Ryan Draft - hardware design and building, protocol design and testing
- Souvik Mandal - protocol design, testing and artwork
- Vikrant Kapoor - hardware design and building
This project is licensed under the MIT License - see the LICENSE.md file for details