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This project forked from shaliulab/ethoscope

1.0 1.0 0.0 82.41 MB

License: GNU General Public License v3.0

Python 71.37% Shell 1.73% CSS 8.61% HTML 8.28% JavaScript 7.15% R 0.39% Jupyter Notebook 0.12% C++ 1.61% Makefile 0.72%

ethoscope's Introduction

Documentation Status Documentation Status Ethoscope

This is the github repository of the software part of the ethoscope platform. All technical information regarding ethoscope is compiled in our documentation.

Organisation of the code

  • src contains the main python package named ethoscope. It is installed on video monitors (devices), but it can be used as a standalone off-line tracking tool.
  • node-src contains the software stack running on the 'node'. Node is a unique computer that syncs and controls devices.
  • prototypes contains (often unsuccessful) developmental trials.
  • scripts contains a toolbox of scripts. For instance to install the software on target device or to convert aquiered videos to a handy format.

Branching system

  • master is only used for hosting tested stable software.
  • dev is a fairly stable developmental used in @gilestrolab.

The workflow is to make issue branches from dev, test them as much a possible before merging them to dev. Then, we deploy them in dev, and update all devices in the @gilestrolab. If we experience no new critical issues over several weeks, we can merge dev to master, allowing the rest of the world to upgrade.

License

Ethoscope source code is licensed under the GPL3 (see license file).

Run offline

From the ./src/ethoscope/scripts folder run:

python device_server.py --rois-pickle-file PATH_TO_ROIS.pickle --input PATH_TO_VIDEO.mp4 --use-wall-clock --drop-each 1 --tracker RichAdaptiveBGModel --camera FSLVirtualCamera --name FLYSLEEPLAB_CV1 --address 192.169.123.10

*rois pickle file: A pickle file storing a list of instances of the ROI class. This is the output of the ROI builder algorithm executed upon start of the recording. If not provided, the software attempts to finding the ROIs from the video. Convenient because it allows for running the ROI builder algorithm at recording time, so issues can be fixed live.

  • use wall clock: will use the time of the video as reference for the analysis. This means t will be mapped to the time of the frame, and not the real time of the offline analysis. So for a video at 10 FPS, the third frame has time 0.3, no matter how long it takes to analyze the first two frames.

  • drop each: If not 1, it will drop every drop-each frame. Example: 2 will drop half the frames, 3 one third, etc. Useful for downsampling.

  • tracker: Name of the tracking class

  • name: Name of the offline ethoscope as displayed in the ethoscope node GUI

  • address: This argument is mandatory for now if you want to see the offline ethoscope appear on the GUI. This is because the code in charge of fetching the ip address of the ethoscopes does not work when running offline. With this argument the user can avert this issue.

ethoscope's People

Contributors

qgeissmann avatar antortjim avatar ggilestro avatar pepelisu avatar nazabic avatar a-r-j avatar jefferis avatar

Stargazers

Michael Ewnetu avatar

Watchers

James Cloos avatar

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