Develop Multiplatform Computer Vision Solutions

Explore the Intel® Distribution of OpenVINO™ toolkit

Make your vision a reality on Intel® platforms—from smart cameras and video surveillance to robotics, transportation, and more.

Your Computer Vision Apps...Now Faster

Develop applications and solutions that emulate human vision with the Intel® Distribution of OpenVINO™ toolkit. Based on convolutional neural networks (CNN), the toolkit extends workloads across Intel® hardware (including accelerators) and maximizes performance.

  • Enables CNN-based deep learning inference at the edge
  • Supports heterogeneous execution across computer vision accelerators—CPU, GPU, Intel® Movidius™ Neural Compute Stick, and FPGA—using a common API
  • Speeds up time to market via a library of functions and preoptimized kernels
  • Includes optimized calls for OpenCV and OpenVX*

Get Started

Discover the Capabilities

Deep Learning for Computer Vision

Accelerate and deploy CNNs on Intel® platforms with the Deep Learning Deployment Toolkit (DLDT) that's available in the Intel Distribution of OpenVINO toolkit.

Hardware Acceleration

Harness the performance of Intel®-based accelerators: CPUs, GPUs, FPGAs, VPUs, and IPUs.

Who Needs This Product

Software developers and data scientists who:

  • Work on computer vision, neural network inference, and deep learning deployment capabilities
  • Want to accelerate their solutions across multiple platforms, including CPU, GPU, VPU, and FPGA


Medical Imaging Powered by AI

Intel teamed up with Philips to deliver high performance, efficient deep-learning inference on X-rays and computed tomography (CT) scans without the need for accelerators. The solution runs on servers powered by Intel® Xeon® Scalable processors and was optimized by Intel® Distribution of OpenVINO™ toolkit.

What's New in the 2018 R5 Release

  • Extends neural network support to include long short-term memory (LSTM) from ONNX*, TensorFlow*, MxNet frameworks, and 3D convolutional-based networks in a preview mode (CPU only) to support additional, new use cases beyond computer vision.
  • Introduces the Neural Network Builder API in a preview mode, which provides the flexibility to create a graph from simple API calls. Directly deploy it using the Inference Engine without loading intermediate representation (IR) files.
  • Delivers a significant boost in CPU performance, especially on multicore systems, through new parallelization techniques.
  • Provides INT8-based primitives for Intel® Advanced Vector Extensions-512, Intel® Advanced Vector Extensions 2, and Single Instruction Multiple Data (SIMD) extensions (SSE4.2) platforms that deliver optimized performance on Intel® Xeon®, Intel® Core™, and Intel® Atom processors.
  • Supports Raspberry Pi* hardware as a host for the Intel Movidius Neural Compute Stick 2 (preview). Offload your deep learning workloads seamlessly to this low-cost, low-power USB stick that's based on the Intel® Movidius™ Myriad™ X technology. It also supports the previous generation.
  • Adds three optimized pretrained models (a total of 30 in the toolkit):
    • Text detection of indoor and outdoor scenes
    • Two single-image, super-resolution networks to enhance the resolution of an input image by a factor of three or four

Release Notes

Product Brief

System Requirements

Case Studies

Intel and GE* bring the power of AI to clinical diagnostic scanning and other healthcare workflows.

GeoVision sped up its facial recognition solution using Intel® System Studio and the Intel Distribution of OpenVINO toolkit.

This toolkit is the centerpiece of Agent Vi*, which provides next-generation vision technology.

NexCOBOT offers a flexible, modular robotics solution that integrates AI with machine vision using tools from Intel.

Open-Source Software

The OpenVINO™ toolkit is an open-source product. It contains the Deep Learning Deployment Toolkit (DLDT) for Intel® processors (for CPUs), Intel® Processor Graphics (for GPUs), and heterogeneous support. It includes an open model zoo with pretrained models, samples, and demos.

OpenVINO™ Toolkit

GitHub* for DLDT

GitHub for Open Model Zoo