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This is a tensorflow based framework for evaluating deep learning algorithms and streaming internal believe states out via ROS. It aims to be a flexible implemention that can be modified and inspected during runtime on live stream data. Eventually it will be used in conjunction with the OpenCog framework for integrated Artificial General Intelligence.
- This code is under heavy development and used for research purposes, so handle with care!
You can find documentation on the wiki tab. There are references for the network architecture and some high-level descriptions on how it works.
I've put todos and remaining tasks in the projects tab on Github. Feel free to collaborate or contact me if you have any suggestions!
Clone the repo into your catkin workspace, make it and run
roslaunch tensorflow_node mnist.launch
TF summaries are being written to outputs/summaries, if enabled in the config file, and they can be inspected via this command:
rosrun tensorflow_node tensorboard