The OpenVINO™ toolkit is a comprehensive toolkit that you can use to develop and deploy vision-oriented solutions on Intel® platforms. Vision-oriented means the solutions use images or videos to perform specific tasks. A few of the solutions use cases include autonomous navigation, digital surveillance cameras, robotics, and mixed-reality headsets.
The OpenVINO™ toolkit:
Enables CNN-based deep learning inference on the edge
Supports heterogeneous execution across an Intel® CPU, Intel® Integrated Graphics, Intel® Neural Compute Stick 2
Speeds time-to-market via an easy-to-use library of computer vision functions and pre-optimized kernels
Includes optimized calls for computer vision standards including OpenCV*, OpenCL™, and OpenVX*
The OpenVINO™ toolkit includes the following components:
Intel® Deep Learning Deployment Toolkit (Intel® DLDT)
Deep Learning Model Optimizer — A cross-platform command-line tool for importing models and preparing them for optimal execution with the Deep Learning Inference Engine. The Model Optimizer supports converting Caffe*, TensorFlow*, MXNet*, Kaldi*, ONNX* models.
Deep Learning Inference Engine — A unified API to allow high performance inference on many hardware types including Intel® CPU, Intel® Processor Graphics, Intel® FPGA, Intel® Neural Compute Stick 2.
nGraph — graph representation and manipulation engine which is used to represent a model inside Inference Engine and allows the run-time model construction without using Model Optimizer.
OpenCV — OpenCV* community version compiled for Intel® hardware. Includes PVL libraries for computer vision.
This Guide provides overview of the Inference Engine describing the typical workflow for performing inference of a pre-trained and optimized deep learning model and a set of sample applications.
Before you perform inference with the Inference Engine, your models should be converted to the Inference Engine format using the Model Optimizer or built directly in run-time using nGraph API. To learn about how to use Model Optimizer, refer to the Model Optimizer Developer Guide. To learn about the pre-trained and optimized models delivered with the OpenVINO™ toolkit, refer to Pre-Trained Models.
Intel® System Studio is an all-in-one, cross-platform tool suite, purpose-built to simplify system bring-up and improve system and IoT device application performance on Intel® platforms. If you are using the Intel® Distribution of OpenVINO™ with Intel® System Studio, go to Get Started with Intel® System Studio.