Follow the instructions here to install the linux drivers.
Download the dataset from here.
Put the dataset in a folder called input, so that <project_root>/leapgestrecog/leapGestRecog
contains the folders 00
to 09
.
Install requirements using
pip install -r requirements.txt
Simply run
python training_nengo.py
to train and evaluate the nengo model.
Image size as well as the ensemble size can be set by setting the variables input_width
, input_height
as well as n_hid
.
The notebook
cnn_nengo_training.ipynb
can be used to train and tune a nengo cnn.
Image size can be set by setting the variables input_width
, input_height
. It is adviced to not create huge networks as the simulation is resource draining.
The notebook
cnn_small.ipynb, cnn_medium.ipynb or cnn_dropout_training.ipynb
can be used to train the different cnn models.
Image size can be set by setting the variables input_width
, input_height
. For the generator simply comment the according line.
First kill the leapd
process to get access to the cameras:
sudo killall leapd
Then run the UI using
python ui.py
When getting a timeout opening the camera, start leapd using
sudo leapd
After a few seconds press Ctrl+C
to stop the process again.
Once it is stopped, try to run the UI again.