is it possible to parse images from OpenGL directly to tensorflow without transmitting them from GPU (framebuffer or any other OpenGL buffer) to CPU and back to tensorflow (GPU) again? We would like to train a network by generated / rendered data and get a decision made by the neuronal network back. This decision changes the position / orientation of the next rendered image which is the input for the network again. This loop should be first used to train the tensorflow network and later to control a vehicle.
How can we achieve the transmission to tensorflow as fast as possible? Share GPU memory? Or combine OpenGL with OpenCL and OpenCL with CUDA and CUDA with tensorflow?