I am trying to deploy various TensorFlow models (Object Detection, DeepLab) with TensorFlow C++ on the Drive PX2. Performance when deployed with TensorFlow is much slower (almost 4x as slow) than a similar setup on an x86 Linux system with a GTX1060.
Running the TensorRT samples gives good results so I assume that there are some issues with the way TensorFlow is managing the gpu processes. Since we only have TensorRT 4 on the PX2, it seems like these models are not easily converted to uff for deployment with TensorRT C++, if possible at all, which is why I am still trying to work with TensorFlow.
Will greatly appreciate any advice. Thanks.