X-LINUX-AI 2.1.0

Compatible with OpenSTLinux Distribution release v2.1.0, v2.0.0 and v1.2.0.

For further information:
https://wiki.st.com/stm32mpu/wiki/X-LINUX-AI_OpenSTLinux_Expansion_Package

Signed-off-by: Vincent ABRIOU <[email protected]>

Author: vinceab

README.md

@@ -3,23 +3,29 @@ OpenEmbedded meta layer to install AI frameworks and tools for the STM32MP1.
 It also provide application samples.
 
 ## Compatibility
-This version has been validated against the OpenSTLinux ecosystem release v2.0.0 and validated on STM32MP157x-DKx and STM32MP157x-EV1 boards.
+This version has been validated against the OpenSTLinux ecosystem release v2.1.0, v2.0.0 and v1.2.0.
+It supports STM32MP157x-DKx, STM32MP157x-EV1 and Avenger96 boards.
 
 ## Available frameworks and tools within the meta-layer
-[X-LINUX-AI v2.0.0 expansion package](https://wiki.st.com/stm32mpu/wiki/X-LINUX-AI_OpenSTLinux_Expansion_Package):
-* TensorFlow Lite 2.2.0
-* Coral Edge TPU accelerator support
-* armNN 20.05
+[X-LINUX-AI v2.1.0 expansion package](https://wiki.st.com/stm32mpu/wiki/X-LINUX-AI_OpenSTLinux_Expansion_Package):
+* TensorFlow™ Lite 2.4.1
+* armNN 20.11
 * OpenCV 4.1.x
-* Python 3.8.x (enabling Pillow module)
+* Python™ 3.8.x (enabling Pillow module)
 * Support STM32MP15xF devices operating at up to 800MHz
-* Python and C++ application samples
-  * Image classification using TensorFlow Lite based on MobileNet v1 quantized model
-  * Object detection using TensorFlow Lite based on COCO SSD MobileNet v1 quantized model
-  * Image classification using Coral Edge TPU based on MobileNet v1 quantized model and compiled for the Coral Edge TPU
-  * Object detection using Coral Edge TPU based on COCO SSD MobileNet v1 quantized model and compiled for the Coral Edge TPU
-  * Image classification using armNN TensorFlow Lite parser based on MobileNet v1 float model
-  * Object detection using armNN TensorFlow Lite parser based on COCO SSD MobileNet v1 quantized model
+* Support of the Avenger96 board from Linaro™ 96Boards based on the STM32MP157A microprocessor, either with a USB camera or the DesignCore® OV5640 camera mezzanine board from D3 Engineering tested with the OpenSTLinux Distribution v2.1.0
+* Coral Edge TPU accelerator support
+  * libedgetpu 2.4.1 (built from source) aligned with TensorFlow™ Lite 2.4.1
+* The X-LINUX-AI OpenSTLinux Expansion Package v2.1.0 is compatible with Yocto Project® build systems Thud and Dunfell. As a consequence, it is compatible with OpenSTLinux Distributions v1.2.0, v2.0.0 and v2.1.0 on STM32MP157C-DK2 with a USB camera, and on STM32MP157A-EV1 and STM32MP157C-EV1 with their built-in camera module
+* Support for the OpenSTLinux AI package repository allowing the installation of prebuilt package using apt-* utilities
+* Application samples
+  * C++ / Python™ image classification application using TensorFlow™ Lite based on MobileNet v1 quantized model
+  * C++ / Python™ object detection application using TensorFlow™ Lite based on COCO SSD MobileNet v1 quantized model
+  * C++ / Python™ image classification application using Coral Edge TPU™ based on MobileNet v1 quantized model and compiled for the Coral Edge TPU
+  * C++ / Python™ object detection applicationusing Coral Edge TPU™ based on COCO SSD MobileNet v1 quantized model and compiled for the Coral Edge TPU
+  * C++ image classification application using armNN TensorFlow™ Lite parser based on MobileNet v1 float model
+  * C++ object detection application using armNN TensorFlow™ Lite parser based on COCO SSD MobileNet v1 quantized model
+  * 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]](mailto:[email protected])
 
 ## Further information on how to install and how to use
 <https://wiki.st.com/stm32mpu/wiki/X-LINUX-AI_OpenSTLinux_Expansion_Package>