linux openvino

Linux OpenVINO是Intel发布的一种人工智能推理引擎，可以在Linux操作系统上运行。它可以加速深度学习和计算机视觉任务，提高算法的性能和效率。此外，OpenVINO还支持多种硬件平台（如CPU、GPU、FPGA等）和多种语言（如C++、Python等），方便开发者进行算法优化和部署。

相关问题

Linux安装OpenVINO

OpenVINO是英特尔开发的一种开源工具套件，用于优化和部署深度学习模型。在Linux上安装OpenVINO可以按照以下步骤进行：

1. 下载OpenVINO：首先，你需要从英特尔官方网站下载OpenVINO的安装包。选择适合你系统的版本，并下载到本地。

2. 安装依赖项：在安装OpenVINO之前，你需要确保系统已经安装了一些必要的依赖项。这些依赖项包括CMake、GCC、Python等。你可以使用包管理器来安装这些依赖项，例如在Ubuntu上可以使用apt-get命令。

3. 解压安装包：将下载的OpenVINO安装包解压到你选择的目录中。

4. 运行安装脚本：进入解压后的目录，运行安装脚本来开始安装。你可以使用以下命令：

   sudo ./install.sh

5. 配置环境变量：安装完成后，你需要配置一些环境变量，以便系统能够正确地使用OpenVINO。你可以在`.bashrc`或者`.bash_profile`文件中添加以下行：

   source /opt/intel/openvino/bin/setupvars.sh

6. 验证安装：最后，你可以通过运行示例代码来验证OpenVINO的安装是否成功。在安装目录下的`inference_engine/samples`文件夹中有一些示例代码，你可以尝试运行其中的一个来验证。

希望以上步骤对你有所帮助！如果你还有其他问题，请随时提问。

openvino linux

### OpenVINO on Linux Installation and Usage Guide

#### Prerequisites
Before installing the Intel® Distribution of OpenVINO™ toolkit, ensure that the system meets all prerequisites. For Ubuntu-based systems, it is essential to have a supported version such as Ubuntu 20.04 LTS or earlier versions like Ubuntu 18.04.3 LTS[^2]. The hardware should also be compatible with OpenVINO requirements.

#### Docker Image Setup for OpenVINO
For users preferring containerized environments, an updated Docker image from DockerHub can simplify setup significantly. Specifically targeting those using NVIDIA GPUs alongside CPUs within an Ubuntu environment:

docker pull openvino/ubuntu20_dev:latest
docker run -it --rm --net=host --name openvino openvino/ubuntu20_dev:latest

This command sequence pulls down the latest available OpenVINO development image built specifically for Ubuntu 20 and runs this image interactively without needing additional configuration due to automatic detection mechanisms provided by the official images[^1].

#### Installing Directly on Host Machine
Alternatively, direct installation onto the host machine involves downloading the installer package directly from the official website following detailed instructions at [official documentation](https://docs.openvinotoolkit.org/latest/_docs_install_guides_installing_openvino_linux.html):

- Downloading the appropriate offline/online installers.
- Executing the installation script after extracting files.
- Configuring environmental variables post-installation through `source /opt/intel/openvino/bin/setupvars.sh`.

#### Post-Installation Configuration
After successful installation, configuring the environment correctly ensures seamless integration between different components including TensorFlow*, Caffe*, ONNX models conversion utilities among others which are key features offered by Intel's proprietary edition aimed primarily towards inference acceleration across various platforms supporting Movidius Myriad X VPU devices too.

#### Verification Steps
To verify whether everything has been set up properly one could execute sample applications bundled inside `/opt/intel/openvino/deployment_tools/demo` directory where multiple pre-configured demos reside ready-to-use out-of-the-box showcasing capabilities ranging from object recognition over video streams to facial landmark estimation tasks etc.

--related questions--

1. What specific steps need attention when setting up GPU support during OpenVINO installations?
2. How does model optimizer tool work under OpenVINO framework converting third-party frameworks into IR format suitable for deployment?
3. Can you provide examples demonstrating how to deploy trained neural networks utilizing OpenVINO runtime APIs effectively?
4. Are there any differences in functionality between running OpenVINO via Docker compared to native setups?