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1.2 Run the software
To run an application, you'll have to run a few services and take a few considerations first.
Please Run Docker (and make sure you've pulled bamos/openface
, see Installation for details).
The docker image will be started automatically and keep active, when running an application for the first time.
When you're done running applications and you don't need the OpenFace service anymore,
please open a terminal and run docker stop openface
.
This can also help when experiencing issues with Docker, which sometimes occurs when it starts automatically with the OS.
In that case, the classic reboot-x-and-try-again scheme, where x is Docker, works wonders.
In order to perform object detection, we make use of a COCO model within Tensorflow.
A COCO service has been implemented in and can be run from the pepper_tensorflow project.
Simply run pepper_tensorflow/object_recognition.py
(using Python 3) and the service will boot.
In oder to make face recognition possible, the people
directory needs to be populated with face-data.
The files should be named <Name of Person>.bin
and contain 1 or more 128-dimensional vectors of the person's face. These vectors are provided with the on_face
event. Due to privacy concerns, faces from our department have not been included in the Git repo. :)
Consider making two subdirectories in pepper/people
with the following layout:
pepper/
..
people/
friends/
friend1.bin
friend2.bin
new/
new1.bin
pepper/
..
The friends folder is where friends of the robot should reside, whereas new people should be put in the new folder automatically after meeting a person.
The global config file can be found under pepper/config.py
. Please modify this to your (performance) needs!
Running test/app/vebose_app.py
, will print out which events fire when and with what data.
If you manage to run this without any errors, dependencies are most likely installed correctly and other apps should work too!
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Start GraphDB Free
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Start Docker
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Start COCO (pepper_tensorflow -> object_recognition.py)
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Start any Application (from the apps/examples directory for example)
Enjoy (& Check settings in pepper/config.py
)!