Revision as of 15:37, 21 June 2024 by Registered User
This article provide information about the X-LINUX-AI Tool, the way to install it, and how to use it.
1. Description[edit source]
The X-LINUX-AI Tool is a small binary designed to provide users with useful information about the X-LINUX-AI Expansion Package.
It is the entry point to install the packages of X-LINUX-AI on top of the OpenSTLinux Starter Package. It also provides information about the X-LINUX-AI version and supported features.
2. X-LINUX-AI Tool installation[edit source]
apt-get install x-linux-ai-tool
3. How to use X-LINUX-AI Tool[edit source]
Usage: x-linux-ai -[option] -v --version : Show X-LINUX-AI current version if it is installed -f --supported-features : Print all supported frameworks in this X-LINUX-AI version -l --list : Print installed and ready-to-install packages -i --install <pkg> : Install X-LINUX-AI package -r --remove <pkg> : Remove X-LINUX-AI package -h --help : Show this help
3.1. Usage example[edit source]
- To show the current version of X-LINUX-AI:
x-linux-ai -v
X-LINUX-AI version: v5.0.0
- To display X-LINUX-AI features:
x-linux-ai -f Features: * TensorFlow™ Lite 2.11.0 with XNNPACK delegate 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 * ONNX Runtime™ 1.14.0 with XNNPACK execution engine activated * OpenCV 4.7.x * Python™ 3.11.x * Support of Sony™ IMX335 5Mpx sensor with use of DCMIPP and internal ISP * Support for the OpenSTLinux AI package repository allowing the installation of a prebuilt package using apt-* utilities * Application : * Image Classification : * C++ / Python™ example using TensorFlow™ Lite based on the MobileNet v3 quantized model * C++ / Python™ example using Coral Edge TPU™ based on the MobileNet v1 quantized model and compiled for the Edge TPU™ * Python™ example using ONNX Runtime based on the MobileNet v3 quantized model * C++ example using Network Binary Graph based on MobileNet v3 quantized model * Object Detection : * C++ example using TensorFlow™ Lite based on the COCO SSD MobileNet v1 quantized model * Python™ example using TensorFlow™ Lite based on the YoloV4-tiny quantized model * C++ / Python™ example using Coral Edge TPU™ based on the COCO SSD MobileNet v1 quantized model and compiled for the Edge TPU™ * C++ / Python™ example using ONNX Runtime based on the COCO SSD MobileNet v1 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 edge.ai@st.com * Human Pose Estimation * Python™ example using TensorFlow™ Lite based on Movenet SinglePose Lightning quantized model * Semantic Segmentation * Python™ example using TensorFlow™ Lite based on DeepLabV3 quantized model * Application support for the 1080p, 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] STM32MP25-beta repository ## Further information on how to install and how to use X-LINUX-AI Starter package <https://wiki.st.com/stm32mp25-beta-v5/wiki/X-LINUX-AI_Starter_package> ## Further information on how to install and how to use X-LINUX-AI Developer package <https://wiki.st.com/stm32mp25-beta-v5/wiki/X-LINUX-AI_Developer_package> ## Further information on how to install and how to use X-LINUX-AI Distribution package <https://wiki.st.com/stm32mp25-beta-v5/wiki/X-LINUX-AI_Distribution_package> ## Application samples Find more information on the wiki page: https://wiki.st.com/stm32mpu/wiki/X-LINUX-AI_OpenSTLinux_Expansion_Package
- To list of the packages of X-LINUX-AI:
x-linux-ai -l [installed] coral-edgetpu-benchmark [installed] libedgetpu2 [installed] libtensorflow-lite2 [installed] tflite-vx-delegate [installed] tim-vx [installed] x-linux-ai-benchmark [not installed] coral-image-classification-cpp [not installed] coral-image-classification-python [not installed] coral-models-coco-ssd-mobilenetv1 [not installed] coral-models-mobilenetv1 [not installed] coral-object-detection-cpp [not installed] coral-object-detection-python [not installed] libcoral2 [not installed] libtensorflow-lite-tools [not installed] onnx-image-classification-python [not installed] onnx-models-coco-ssd-mobilenetv1 [not installed] onnx-models-mobilenetv1 [not installed] onnx-models-mobilenetv3 [not installed] onnx-object-detection-cpp [not installed] onnx-object-detection-python [not installed] onnxruntime [not installed] onnxruntime-tools [not installed] onnxruntime-unit-tests [not installed] packagegroup-x-linux-ai [not installed] packagegroup-x-linux-ai-coral [not installed] packagegroup-x-linux-ai-npu [not installed] packagegroup-x-linux-ai-onnxruntime [not installed] packagegroup-x-linux-ai-tflite [not installed] python3-libtensorflow-lite [not installed] python3-onnxruntime [not installed] python3-pycoral [not installed] tflite-face-recognition-cpp [not installed] tflite-image-classification-cpp [not installed] tflite-image-classification-python [not installed] tflite-models-coco-ssd-mobilenetv1 [not installed] tflite-models-deeplabv3 [not installed] tflite-models-mobilenetv1 [not installed] tflite-models-mobilenetv3 [not installed] tflite-models-movenet-singlepose-lightning [not installed] tflite-models-yolov4-tiny [not installed] tflite-object-detection-cpp [not installed] tflite-object-detection-python [not installed] tflite-pose-estimation-python [not installed] tflite-semantic-segmentation-python [not installed] tim-vx-tools
- To install packages of X-LINUX-AI:
x-linux-ai -i <package>
x-linux-ai -i onnxruntime Reading package lists... Done Building dependency tree... Done Reading state information... Done The following NEW packages will be installed: onnxruntime 0 upgraded, 1 newly installed, 0 to remove and 16 not upgraded. Need to get 0 B/6089 kB of archives. After this operation, 0 B of additional disk space will be used. The software package is provided AS IS, and by downloading it, you agree to be bound to the terms of the software license agreement (SLA). The detailed content licenses can be found at https://wiki.st.com/stm32mpu/wiki/OpenSTLinux_licenses. Selecting previously unselected package onnxruntime. (Reading database ... 18419 files and directories currently installed.) Preparing to unpack .../onnxruntime_1.14.0+git0+6ccaeddefa-r0_arm64.deb ... Unpacking onnxruntime (1.14.0+git0+6ccaeddefa-r0) ... Setting up onnxruntime (1.14.0+git0+6ccaeddefa-r0) ... N: Ignoring file 'packages.openstlinux.st.com.list.tmp' in directory '/etc/apt/sources.list.d/' as it has an invalid filename extension onnxruntime has been installed successfully.
- To uninstall packages of X-LINUX-AI:
x-linux-ai -r <package>
x-linux-ai -r onnxruntime Reading package lists... Done Building dependency tree... Done Reading state information... Done The following packages will be REMOVED: onnxruntime 0 upgraded, 0 newly installed, 1 to remove and 16 not upgraded. After this operation, 0 B of additional disk space will be used. The software package is provided AS IS, and by downloading it, you agree to be bound to the terms of the software license agreement (SLA). The detailed content licenses can be found at https://wiki.st.com/stm32mpu/wiki/OpenSTLinux_licenses. (Reading database ... 18423 files and directories currently installed.) Removing onnxruntime (1.14.0+git0+6ccaeddefa-r0) ... N: Ignoring file 'packages.openstlinux.st.com.list.tmp' in directory '/etc/apt/sources.list.d/' as it has an invalid filename extension onnxruntime has been removed successfully.