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Project in the context of the IKT-442 class at the University of Agder. Allows to detect movements using a depth camera and a tensorflow model and to propagate inputs to a linux kernel. Our implementation is on a Raspberry pi 4.
Home Page: https://gitlab.com/reds-public/ihm3d
Shell 4.39%
C++ 2.91%
CMake 0.49%
C 31.79%
Python 56.08%
Jupyter Notebook 2.73%
Makefile 0.82%
SWIG 0.59%
Dockerfile 0.20%
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minority-report-project's Issues
Combine the driver code with the real time detection code in python
Add instalation explanation in readme, project presentation,...
Build an app for real time detection
Add the make module cmd to the C workflow
Do you have any videos of this project in action?
Add tests for the basic uinput api
Document all the old misc code used during development
I don't see a license file. Is this project open source like MIT? If so, I'll try to get it running on my RPi 5.
Thanks :)
Create the base of the api to access the uinput framework
Complete the setup file with all instructions for installing python and all related modules
Create the benchmark code that will be used to prouce the results for the article
Write the python module that will be used in the real time app
Centraliser les fichiers et mettre au propre le repo
The app could run on a PC using TCP communication between the Pi and the PC
Try to find a way using docker to launch the tensorflow machine learning algorithm in the remote environment provided by UIA