Server node goes here…https://github.com/reelrbtx/MoveEyes, client stuff goes in SMACC Client Library

Big idea is to be able to import TensorFlow models, like… https://www.tensorflow.org/lite/models, or https://sthalles.github.io/deep_segmentation_network/, with deeplab as the default model.

Built on top of cppflow https://github.com/serizba/cppflow – Not really a library, more like the design pattern we’ll use, see TensorFlow C API.

Server also needs to supply an API so that the client can have it load different models, kind of like ros_control, move_group_interface.

Need to support 3 default image sources…
Point Clouds, Stereo Camera, rgb cameras: Color, Depth & Three point

Each model in the Server should have a corresponding component in the client, that contains code that translates the output of the MoveEyes model into information that can be used to make decisions (If you see a blue blob (a car), then run away). Component reads the names of the input, shape of the input, name the output, and shape of the output…

MSeg?

• https://discourse.ros.org/t/new-robust-pre-trained-semantic-segmentation-models-cvpr-20/15607
• https://github.com/mseg-dataset/mseg-semantic