-
Notifications
You must be signed in to change notification settings - Fork 20
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Signed-off-by: Maxence GUILHIN <[email protected]>
- Loading branch information
Showing
3 changed files
with
46 additions
and
36 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -1,9 +1,8 @@ | ||
|
||
<p align="center"> | ||
<img width="720" src="https://raw.githubusercontent.com/STMicroelectronics/meta-st-stm32mpu-ai/master/x-linux-ai-logo.png"> | ||
</p> | ||
|
||
X-LINUX-AI version: v5.0.0 | ||
X-LINUX-AI version: v5.1.0 | ||
|
||
X-LINUX-AI is a free of charge open-source software package dedicated to AI. | ||
It is a complete ecosystem that allow developers working with OpenSTLinux to create AI-based application very easily. | ||
|
@@ -20,8 +19,8 @@ X-LINUX-AI OpenEmbedded meta layer to be integrated into OpenSTLinux distributio | |
It contains recipes for AI frameworks, tools and application examples for STM32MPx series | ||
|
||
## Compatibility | ||
The X-LINUX-AI OpenSTLinux Expansion Package v5.0.0 is compatible with the Yocto Project™ build system Mickledore. | ||
It is validated over the OpenSTLinux Distribution v5.0 on STM32MP157F-DK2 with a USB image sensor, on STM32MP157F-EV1 with its built-in camera module, and on STM32MP135F-DK with its built-in camera module | ||
The X-LINUX-AI OpenSTLinux Expansion Package v5.1.0 is compatible with the Yocto Project™ build system Mickledore. | ||
It is validated over the OpenSTLinux Distribution v5.1.0 on STM32MP25x and STM32MP1x series. | ||
|
||
## Versioning | ||
Since its release v5.0.0, the major versioning of the X-LINUX-AI OpenSTLinux Expansion Package is aligned on the major versioning of the OpenSTLinux Distribution. This prevents painful backward compatibility attempts and makes dependencies straightforward. | ||
|
@@ -31,27 +30,38 @@ The X-LINUX-AI generic versioning v**x**.**y**.**z** is built as follows: | |
* **z**: patch version to introduce bug fixes. A patch version is implemented in a backward compatible manner. | ||
|
||
## Available frameworks and tools within the meta-layer | ||
[X-LINUX-AI v5.0.0 expansion package](https://wiki.st.com/stm32mpu/wiki/Category:X-LINUX-AI_expansion_package): | ||
* XNNPACK support for TensorFlow™ Lite and ONNX Runtime, with about 20% to 30% performance gain for quantized networks on a 32-bit system | ||
* TensorFlow™ Lite 2.11.0 with XNNPACK delegate activated | ||
* ONNX Runtime 1.14.0 with XNNPACK execution engine activated | ||
* OpenCV 4.7.x | ||
* Python™ 3.10.x (enabling Pillow module) | ||
* Coral Edge TPU™ accelerator native support | ||
* libedgetpu 2.0.0 (Gouper) aligned with TensorFlow™ Lite 2.11.0 | ||
* libcoral 2.0.0 (Gouper) aligned with TensorFlow™ Lite 2.11.0 | ||
* PyCoral 2.0.0 (Gouper) aligned with TensorFlow™ Lite 2.11.0 | ||
* Support for the OpenSTLinux AI package repository allowing the installation of a prebuilt package using apt-* utilities | ||
* Application samples | ||
* C++ / Python™ image classification example using TensorFlow™ Lite based on the MobileNet v1 quantized model | ||
* C++ / Python™ object detection example using TensorFlow™ Lite based on the COCO SSD MobileNet v1 quantized model | ||
* C++ / Python™ image classification example using Coral Edge TPU™ based on the MobileNet v1 quantized model and compiled for the Edge TPU™ | ||
* C++ / Python™ object detection example using Coral Edge TPU™ based on the COCO SSD MobileNet v1 quantized model and compiled for the Edge TPU™ | ||
* C++ face recognition application using proprietary model capable of recognizing the face of a known (enrolled) user. Contact the local STMicroelectronics support for more information about this application or send a request to [email protected] | ||
* Python™ image classification example using ONNX Runtime based on the MobileNet v1 quantized model | ||
* C++ / Python™ object detection example using ONNX Runtime based on the COCO SSD MobileNet v1 quantized model | ||
* Application support for the 720p, 480p, and 272p display configurations | ||
* X-LINUX-AI SDK add-on extending the OpenSTLinux SDK with AI functionality to develop and build an AI application easily. The X-LINUX-AI SDK add-on provides support for all the above frameworks. It is available from the [X-LINUX-AI](https://www.st.com/en/embedded-software/x-linux-ai.html) product page | ||
[X-LINUX-AI v5.1.0 expansion package](https://wiki.st.com/stm32mpu/wiki/Category:X-LINUX-AI_expansion_package): | ||
* AI Frameworks: | ||
* STAI_MPU Unified API based on OpenVX™(STM32MP25x only), TensorFlow™ Lite, Coral Edge TPU™ and ONNX Runtime™ compatible with all STM32MPU series | ||
* TIM-VX™ 1.1.57 (STM32MP25x only) | ||
* TensorFlow™ Lite 2.11.0 (CPU only) with XNNPACK delegate activated | ||
* ONNX Runtime™ 1.14.0 (CPU only) with XNNPACK execution engine activated | ||
* Coral Edge TPU™ accelerator native support | ||
* libedgetpu 2.0.0 (Grouper) aligned with TensorFlow™ Lite 2.11.0 | ||
* libcoral 2.0.0 (Grouper) aligned with TensorFlow™ Lite 2.11.0 | ||
* PyCoral 2.0.0 (Grouper) aligned with TensorFlow™ Lite 2.11.0 | ||
|
||
* Out of the box applications: | ||
* Image classification : | ||
* C++ / Python™ example using STAI_MPU Unified API]] based on the MobileNet v1 and v2 quantized models | ||
* Object detection : | ||
* C++ / Python™ example using STAI_MPU Unified API]] based on the SSD MobileNet v1 and v2 quantized models | ||
* Python™ example using STAI_MPU Unified API]] based on YoloV8n pose quantized model | ||
* Semantic segmentation : | ||
* Python™ example using STAI_MPU Unified API]] based on DeepLabV3 quantized model | ||
* Face recognition: | ||
* C++ example using proprietary model capable of recognizing the face of a known (enrolled) user. | ||
* Contact the local STMicroelectronics support for more information about this application or send a request to [email protected] | ||
* Note: applications are based on Gstreamer 1.22.x, GTK 3.x, OpenCV 4.7.x, Pillow, Python 3 | ||
|
||
* Utilities: | ||
* X-LINUX-AI tool suite provides tools for software information, AI packages management and Neural Network models benchmarking. | ||
* Support wide range of image sensors for ST MPU including IMX335 (5MP) for MP2 with use of internal ISP, GC2145 and OV5640 for STM32MP13x | ||
* Support for the OpenSTLinux AI package repository allowing the installation of a prebuilt package using apt-* | ||
|
||
* Host tools: | ||
* ST Edge AI tool for NBG generation | ||
* X-LINUX-AI SDK add-on extending the OpenSTLinux SDK with AI functionality to develop and build an AI application easily. The X-LINUX-AI SDK add-on supports all the above frameworks. It is available from the X-LINUX-AI product page | ||
|
||
## Further information on how to install and how to use X-LINUX-AI Starter package | ||
<https://wiki.st.com/stm32mpu/wiki/X-LINUX-AI_Starter_package> | ||
|
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters