Awesome

A Cython-based Dynamic Vision Sensor (DVS) emulator. It can be used within a Python environment as demonstrated in the various test files.

This project is under the GPLv3 License (https://www.gnu.org/copyleft/gpl.html)

I added a C++ version of the basic algorithm using OpenCV.

A DVS is a camera-like sensor which emits per-pixel asynchronous Address-Event Representation (AER) packets. These are originated due to an intensity level change has reached a certain threshold.

This project emulates this behaviour using commodity hardware, that is a regular PC and camera. Modifications to the default behaviour where added, mainly: encoding of values using time, local inhibition and dynamic thresholds.

Fred Rotbart (https://github.com/fcr) has been kind enough to port to Python 3 and checked compatibility with MacOS Sierra, plus code clean-up!

Requirements:

• Cython
• Numpy
• OpenCV (with Python bindings)

Before using, compile the Cython modules by running

python setup.py build_ext --inplace

in the folder where pyDVS is installed.

Files:

• pydvs/:

  • generate_spikes.pyx - Cython backend library. Contains functions to generate spikes from a video feed.
  • external_dvs_emulator_device*.py - sPyNNaker class wrapper, it's compatible with OpenCV VideoCapture devices and VirtualCam.
  • virtual_cam.py - A camera emulator that feeds on images located in the users computer. It keeps images moving based on eye movements (e.g. micro saccades and saccades); there's a very simple attention model for the saccade mode.

• spynnaker_test.py - Demonstration script for sPyNNaker compatible frontend.

• stand_alone*.py - Demonstration scripts for the Cython backend, they come in single- and multi-threaded versions.

• virtual_cam_test.py - Demonstration script for the VirtualCam class, it requires images in a directory ("./mnist" by default)

The multithreaded versions require either Python 3.4 and above or Windows