When it comes to people, more specific models can detect a raised hand, a face, a pedestrian, or a physical pose. How Does Neural Compute Stick Use OpenVINO? The NCS2 uses a Vision Processing Unit (VPU), while the Coral Edge Accelerator uses a Tensor Processing Unit (TPU), both of which are specialized processors for machine learning. At the writing of this article that is the "2019" branch. It looks like a beefy dongle.

After the above steps were followed for this example, the directory structure for the deployment system looks like the list that follows, with comments in parenthesis.

Both devices plug into a host computing device via USB. Only needed if not already installed), libusb-1.0.so.0 (usb-1.0 softlink to libusb-1.0.so.0.1.0), libusb-1.0.so.0.1.0 (actual usb-1.0 library). All the OpenCV libraries are from version 4.1. Code Repository. If building for a platform that can support these plugins the OFF can be changed to ON in the cmake command. The inference-engine directory contains the components that will need to be built to use the Intel® NCS 2 device. The Neural Compute Stick will retail for $100. Intel® Distribution of the OpenVINO™ toolkit, Intel® Threading Building Blocks (Intel®TBB), Get Started with Intel® Neural Compute Stick 2 (Intel® NCS 2), Check out the ncappzoo github repository, it contains numerous sample apps for the  Intel® NCS 2, Explore the Intel® Distribution of OpenVINO™ toolkit, Get Started with the Intel® Distribution of OpenVINO™ Toolkit, Transitioning from Intel® Movidius™ Neural Compute SDK to Intel® Distribution of OpenVINO™ toolkit. Many of us are already familiar with a prevalent machine learning training process. You must use a framework, such as TensorFlow or Caffe, to generate the trained model.

And in applications where you have full access to cloud-connected computers or high-end processing platforms, that trained network might be ready for deployment. An upside to this approach is that OpenVINO means that you can start working with machine learning algorithms without any additional hardware in most cases. If apt is not available or packages are not available, some research may be required to determine how to get the equivalent components installed on your system. That exact situation is where OpenVINO comes in.

Don’t have an Intel account? There are a few ways a trained neural network in IR format can be obtained: Downloading directly from download.01.org is the simplest. Sponsored Links. See the opencv installation instructions for more information. While in a terminal logged in as a user that is a member of the users group run the following commands: The USB driver is configured after the above commands have executed successfully. These optimizations include SSE2, SSE3, and SSSE3 instruction sets and other optimizations. For clarity, OpenVINO is not a machine learning framework itself. Then it is told if the decision it made was correct. Intel These files will be passed to the benchmark_app when executed below. There is a script to install these build dependencies in the inference-engine directory named install_dependencies.sh. For the purpose of verifying the build, the benchmark_app in this directory can be used. Deprecation Notice: This article uses the Movidius APIv1 and APIv2 which is now superseded by Intel’s OpenVINO software for … At first, it might seem like this device is a "machine learning accelerator." Look for the error message "Cannot detect Linux OS via reading /etc/*release" and add the build system's OS Name to the conditional statement. OpenVINO Example, detecting a license plate, Trained neural network identifying car images.

The Neural Compute Stick 2 offers plug-and-play simplicity, support for common frameworks and out-of-the-box sample applications.

This is where the Myriad plugin is located on the file system. Please do not confuse the "Neural Compute Stick" with the "Compute Stick." The MYRIAD plugin shared object library must be available.

These files are downloaded onto the build system during the build process and can be copied from the build system here /dldt/inference-engine/bin//Release/lib to the deployment system ~/benchmark/lib directory. More: Intel Unveils the Intel Neural Compute Stick 2 at Intel AI Devcon Beijing for Building Smarter AI Edge Devices. In addition to the above packages ffmpeg maybe needed if audio or video streams will be processed by OpenCV. At an event in Beijing, Intel debuted the Neural Compute Stick 2, which packs a Myriad X system-on-chip it claims has an 8 times performance advantage. Therefore, the bare minimum which will need to be built to use an Intel® NCS 2 is the inference engine API and the MYRIAD plug-in. The other plug-ins in the repository will not be needed and depending on your platform may not apply. Forgot your Intel If the script doesn't work straightaway on your system there may be some trial work required to get the necessary components Below are the packages (Ubuntu package names) that are installed by the install_dependencies.sh script as of this writing. All the build samples can be found in the /dldt/inference-engine/bin//Release directory. The Myriad plugin is the libmyriadPlugin.so shared object library. Just like a biological brain, training the neurons cause them to make weighted connections.

The other case for NCS2 is development, training, and (performance) testing targeting an end-product based on the Movidius VPU. If there is a separate system on which the software will be deployed then the Deploying section below should be followed to get the required components on the system prior to verifying. To build the code cmake and gcc must be installed on your system. To make sure that all dependencies that these two shared libraries have are also available, run ldd on these libraries as well. Note that the frames per second (FPS) for the network with the sample input image is displayed as the last line of output. If your system has apt (advanced packaging tool) support you can install it with this command: After git is installed, you can clone the git repository using the following command: The image to the right shows the contents of the dldt directory after cloning. If one or more of the packages above can't be found or fails to install its worthwhile to attempt to build before going through the trouble of tracking down a replacement.

Platforms it supports are desktop-class CPUs, GPUs, FPGAs, and VPUs.

The chip has a dozen camera inputs, but these weren’t exposed on the original stick. To avoid typing the apt-get command for each package it's possible to cut and paste relevant lines from the install_dependencies.sh script.

It looks like a beefy dongle. By

Profiling, tuning, and compiling a DNN on a development computer with the tools are provided in the Intel Movidius Neural Compute SDK.

November 14, 2018 Comments. Remember, the training process requires many iterations of getting new data, making a guess, and then adjusting its network based on a simple "yes" or "no" response. Make sure the binary is executable, use chmod +x .~/benchmark/benchmark_app to accomplish this. The Movidius NCS’ compute capability comes from its Myriad 2 VPU (Vision Processing Unit).

Inside is the Movidius Myriad X vision processing unit (VPU). See the file dldt/inference-engine/CMakeLists.txt file and the variable referenced as ${ARCH_FOLDER} to see how will be set. username

Intel's compilers may or may not optimize to the same degree for non-Intel microprocessors for optimizations that are not unique to Intel microprocessors.

Intel's Neural Compute Stick 2 (NCS2) is a stick with a USB port on it. For example, reCAPTCHA sometimes shows you pictures that it knows you should click, and sometimes it shows you images to see if you pick the same answer it did. Not all packages will be required for all build scenarios. Once OpenVINO is installed, and you can load the included examples to the VPU, there is one more GitHub repository to visit. Both of these files can be copied from build machine directory /dldt/inference-engine/bin//Release/lib to the deployment machine ~/benchmark/lib directory. Sign up here The most popular target for OpenVINO is the Movidius in the Neural Compute Stick 2. Examples of inference models include object, person, and vehicle detection.

Each of these are explained in this section. The open model zoo also contains models in FP32 and Int8 depending on the specific model. To prepare the system for building, the build tools, the git submodules, and the dependencies need to be on the build system. Google's reCAPTCHA may have asked you to identify elements like bicycles, crosswalks, or traffic lights in a series of low-quality pictures. For the libformat_reader.so, ldd indicates that three OpenCV libraries are also not found on the deployment system.

All shared object libraries the application depends on must be available: To determine the libraries the application depends on execute the following command from the ~/benchmark directory. Intel calls it the Open Model Zoo. Inspired by Moore’s Law, we continuously work to advance the design and manufacturing of semiconductors to help address our customers’ greatest challenges. Note: will be different depending on the build platform's architecture. Specifies the target device on which to run the inference. Instead, when paired with a PC, it becomes a development platform. The MYRIAD plugin shared object library must be available: The myriad plugin filename is libmyriadPlugin.so and it can be copied from the build machine in this directory: /dldt/inference-engine/bin//Release/lib to the deployment machine in ~/benchmark/lib. Version requirements for these tools may change, but as of this writing, cmake 3.5 and gcc 4.8 are required.

A VPU is a Visual Processing Unit or a processor that contains a neural compute engine. How to get it installed may vary from platform to platform and could require building from source. Machine learning is the study of computer algorithms that improve automatically through experience. Then you needed to determine what combination of toolkits, platforms, connectivity models, and processor options benefits your end-application. Intel, the Intel logo and other Intel marks are trademarks of Intel Corporation or its subsidiaries.

For the age/gender network that was downloaded, the input should be an image that is 62 pixels wide and 62 pixels high with three channels of color. Please refer to the applicable product User and Reference Guides for more information regarding the specific instruction sets covered by this notice. These files can be copied to the deployment system in the ~/benchmark directory. After the build completes this is in the .../Release/lib directory. To verify that the Intel® NCS 2 device and the OpenVINO™ toolkit is working correctly, the following items need to be considered. After building and installing cmake, any open terminals may need to be closed and re-opened to use the newly installed cmake. These data sets are also sometimes called "training data." Intel (Nasdaq: INTC) is an industry leader, creating world-changing technology that enables global progress and enriches lives. Since OpenVINO's license is Apache 2.0, third parties can add support for other hardware through a plug-in. Note: After the above commands are successfully executed the following files will be on the system: ~/models/age-gender-recognition-retail-0013.xml, and ~/models/age-gender-recognition-retail-0013.bin. If cmake is not installed you can install it via the package manager for your system. Inside is the Movidius Myriad X vision processing unit (VPU). After successfully completing the inference engine build, the result should be verified to make sure everything is working. The Intel® Distribution of the OpenVINO™ toolkit provides a binary installation that supports a fair number of development and target platforms, providing tools and an API for the Intel® NCS 2.

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