This repository is a simple Readme describing all AI for STM32 projects.
| Project | Description |
|---|---|
| stm32ai-modelzoo-services | AI Model Zoo Services (training, quantization, evaluation scripts...) for STM32 devices |
| stm32ai-modelzoo | Storage for the AI Model Zoo for STM32 devices |
| HuggingFace-STMicroelectronics | Hugging Face space containing the models card and a space for the model zoo app |
| Project | Description |
|---|---|
| STM32N6 AI | STM32N6 AI ecosystem with application examples |
| Project | Description |
|---|---|
| meta-st-x-linux-ai | OpenEmbedded meta layer to install AI frameworks, tools and application samples for the STM32MPU series |
| meta-st-x-linux-isp | OpenEmbedded meta layer to install ISP tools and applications for the STM32MP2x series |
| Project | Description |
|---|---|
| stm32-mw-isp | The ISP (Image Signal Processing) middleware library supports camera applications development for STM32 microcontrollers embedding the ISP camera pipeline called DCMIPP. |
| stm32-mw-camera | The camera middleware library simplifies the development process for applications that require camera functionality by abstracting hardware-specific details. |
| stm32-mw-ipl | The STM32 Image Processing Library (IPL) is a C software library of image processing and computer vision functionalities enabling to accelerate the development of vision applications on STM32 microcontrollers. |
| x-cube-isp | The X-CUBE-ISP is an image signal processing (ISP) tuning software. It targets STM32 microcontrollers embedding an ISP camera pipeline called DCMIPP. It offers advanced image quality tuning services, enabling developers to easily create ISP-based applications. |
| x-cube-webcam | This is an STM32 expansion software to manage USB Video device Class (UVC). It also provides UVC camera application examples. |
| Project | Description |
|---|---|
| x-cube-ai | X-CUBE-AI - AI expansion pack for STM32CubeMX |
| ST Edge AI Developer Cloud | ST Edge AI Developer Cloud - online optimization platform |
| NanoEdge AI Studio | NanoEdge AI Studio - automated machine learning tool |
| STM32 ISP IQtune | STM32 ISP IQTune - comprehensive STM32 ISP tuning softwar |
| Project | Description |
|---|---|
| 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-nanoedge-vibration-monitoring | STM32 Application for vibration monitoring with NanoEdge AI Studio |
| stm32ai-nanoedge-datalogger | STM32 Application for datalogging feature with NanoEdge AI Studio |
| Project | Description |
|---|---|
| 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 |
| STEdgeAI Ultralytics fork | Fork of the Ultralitics repository that implements STEdgeAI models |
| Project | Description |
|---|---|
| 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-perf | MLPerf™ Tiny Deep Learning Benchmarks for STM32 devices |
For communication and support, please refer to:
- ST Support Center for any defect
- ST Community Forum forum