This repository is a simple Readme describing all AI for STM32 GitHub projects.
| Repository | Description |
|---|---|
| meta-st-x-linux-ai | OpenEmbedded meta layer to install AI frameworks, tools and application samples for the STM32MPU series |
| stm32ai-modelzoo | AI Model Zoo for STM32 devices |
| STEdgeAI Ultralytics fork | Fork of the Ultralitics repository that implements STEdgeAI models |
| stm32ai-nota | This repository contains Jupyter notebooks that demonstrate how to use Netspresso to prune pre-trained deep learning models from STM32AI Model Zoo and fine-tune them for your specific use case. Learn how to reduce the size of your models without sacrificing accuracy and customize them for your own applications |
| stm32ai-tao | Nvidia TAO (Train, Adapt, Optimize) with STM32Cube.AI Developer Cloud |
| stm32ai-wiki | Application examples and resources that demonstrate Artificial Neural Networks running on STM32 microcontrollers and microprocessors. It illustrates and supports the STM32 AI Wiki articles |
| stm32ai-datalogger | GenericDataLogger for AI is a project composed of tools that format and log data with ease, especially between a STM32 and a computer |
| stm32ai-perf | MLPerf™ Tiny Deep Learning Benchmarks for STM32 devices |
| stm32ai-nanoedge-vibration-monitoring | STM32 Application for vibration monitoring with NanoEdge AI Studio |
| stm32ai-nanoedge-datalogger | STM32 Application for datalogging feature with NanoEdge AI Studio |
| stm32ai-tvm | STM32 Application for Deep Learning Framework with TVM |
| x-cube-webcam | This is an STM32 expansion software to manage USB Video device Class (UVC). It also provides UVC camera application examples |
For communication and support, please refer to:
- ST Support Center for any defect
- ST Community Forum forum