You can now develop solutions with TensorFlow for the Spresense microcontroller board from Sony. It’s a combination of a leading machine learning ecosystem with a high performance microcontroller running with super low power consumption. The Spresense board was designed with camera vision and hi-res audio inputs as core features, which opens the platform up for many use cases.

TensorFlow is Google’s open-source software library for machine learning that developers and researchers can use for a range of application areas. The well-known and widely spread library comes in different flavors ready to run on various operating systems and hardware. Specifically, the TensorFlow Lite for Microcontrollers (TFLM) version is designed to run on microcontroller systems where the hardware resources are more limited compared to larger computerized systems. The footprint of TFLM is typically in the order of only 10’s of kB.

Pete Warden, Research Engineer on Google’s TensorFlow team, says:

“It’s great to see this kind of compute capability tightly integrated into a low power sensor, the combination will help make machine learning accessible to developers in medical, agriculture, industrial monitoring and many other areas where a small form factor and energy are strong constraints”.

Arm’s engineers have worked closely with the TensorFlow team to develop optimized versions of the TensorFlow Lite kernels in the CMSIS-NN library, delivering extremely fast performance on Arm Cortex-M cores like Spresense.

See this page for more information and how to get started.