MVTec Software, a leading provider of innovative machine vision technologies, has made extensive deep learning functions available on embedded boards with NVIDIA Pascal architecture.
The deep learning inference in the new version 17.12 of the HALCON machine vision software was successfully tested on NVIDIA Jetson TX2 boards based on 64-bit Arm processors.
The company said that the deep learning inference, i.e. applying the trained CNN (convolutional neural network), almost reached the speed of a conventional laptop GPU (approximately five milliseconds).
It added: “This is an unusually high execution performance for an embedded device – compared to a standard PC. Users can thus enjoy all the benefits of deep learning on the popular NVIDIA Jetson TX2 embedded board. This is possible thanks to the availability of two pretrained networks that MVTec ships with HALCON 17.12. One of them (the so called “compact” network) is optimized for speed and therefore ideally suited for use on embedded boards. MVTec will provide interested customers with a software version for this architecture on request.”
MVTec’s Embedded Vision Product Manager Christoph Wagner said: “We have provided successful technological proof that allows us to offer advanced deep learning functions in the embedded vision segment. This will greatly benefit users. They can now utilize the extensive new HALCON 17.12 features on standard devices with NVIDIA Pascal architecture – at an extraordinary high speed for embedded technologies.”
Managing Director of MVTec Dr Olaf Munkelt added: “The rapidly growing market for embedded systems requires corresponding high-performing technologies. At the same time, AI-based methods such as deep learning and CNNs, are becoming more and more important in highly automated industrial processes. We are specifically addressing these two market requirements by combining HALCON 17.12 with the NVIDIA Pascal architecture.”