STMicroelectronics has launched an edge AI firmware pack and camera module based around its STM32 microcontrollers (MCUs).
The FP-AI-VISION1 contains several code examples demonstrating complete computer-vision applications running a convolutional neural network (CNN) on the STM32H747 microcontroller and easily portable on all STM32 MCUs. The firmware, part of the STM32Cube eco-system, includes several application examples but lets developers retrain the neural networks with their own data sets, giving freedom and flexibility to address a wide variety of use cases.
New features include support for USB VC camera (webcam mode), which allows simple image acquisition, and code examples for food classification and human-presence detection to create a convenient visual “wakeword” for reactivating a system from power-save mode.
The B-CAMS-OMV camera bundle is optimized for use with FP-AI-VISION1 and provides the hardware required for training and deployment. The bundle contains ST’s MB1379 5-Mpixel OV5640 colour camera module fitted to an adapter card compatible with all STM32 Discovery and Evaluation boards with a ZIF connector. The adapter card can also be used with the ST VG5661 automotive grayscale global-shutter camera. In addition, Waveshare and OpenMV connectors can be used to attach various third-party infrared and visible-spectrum cameras to address a wider range of computer-vision applications.
Included in FP-AI-VISION1 are 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. Support for flexible memory configurations allows fine-tuning the model for the intended application.
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