ST’s FP-AI-VISION1 for Edge Computer Vision Applications

ST’s FP-AI-VISION1 for Edge Computer Vision Applications

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Computer vision applications have tremendously increased since the progress in the field of machine learning and artificial intelligence. These applications come at the cost of high-end hardware or cloud support for advanced computations and processing. Hence, STMicroelectronics has announced a new AI software support along with the camera-module hardware, for building affordable applications. The system now supports Edge AI for operating computer-vision applications on the device itself, thus replacing the expensive cloud support for similar high-end applications.

ST’s FP-AI-VISION1 is a STM32Cube function pack that comes with various code instances. This can run computer-vision applications in the environment supporting convolutional neural networks for deep learning on STM32H747. The function pack is flexibly compatible with all STM32 MCUs. Hence, the developers need not start from scratch if they want to switch their STM-based hardware. The firmware also gives an option for using various neural networks with almost every dataset according to the choice of users. Although, the dataset needs to be manipulated so that it is compatible with the neural network.

Features of  ST’s FP-AI-VISION1

  • Complete software support on ROM to develop computer vision applications on STM32 microcontroller
  • Image pre-processing library, STM32_Image for initial stages of the applications
  • Neural Network library optimized for STM32 (STM32_AI_Runtime) generated by means of the X-CUBE-AI Expansion Package for STM32CubeMX
  • Food recognition and Person presence detection application based on Convolutional Neural Network
  • USB webcam application for computer vision enabling the STM32H747I-DISCO board to capture video when connected to a host’
  • It comes with libraries which allow the function such as testing, debugging and validation of the embedded application
  • It supports features like camera frame capture to allow image dataset collection, which is a precise way of extracting frames from a video.
  • Sample implementations are available for the STM32H747I-DISCO Discovery board connected to the B-CAMS-OMV camera module bundle
B-CAMS-OMV

The B-CAMS-OMV camera bundle is compatible with FP-AI-VISION1 firmware. It provides the hardware with optimized training and deployment features. The bundle also comes with ST’s MB1379 5-Mpixel OV5640 color camera module fitted to an adapter card. It can work with all STM32 Discovery and Evaluation boards with a ZIF connector. The software support of Waveshare and OpenMV connectors allows the users to connect multiple third-party infrared and visible-spectrum cameras to address a wider range of computer-vision applications

ST’s FP-AI-VISION1 firmware supports:

“various frame-buffer processing functions, camera drivers, and software for image capture, pre-processing, and neural-network inference. Several neural-network models are available, including a floating-point-based model and a quantized model generated by X-CUBE-AI, ST’s optimized C-code generator for artificial neural networks.”

The function pack is available for download on the STM website. The B-CAMS-OMV camera-module bundle is available for $56 on the website and other distributors. For more information visit the press release. Images and technical specifications have been taken from the product pages.

Saumitra Jagdale is a Backend Developer, Freelance Technical Author, Global AI Ambassador (SwissCognitive), Open-source Contributor in Python projects, Leader of Tensorflow Community India, and Passionate AI/ML Enthusiast

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