Just Released! Intel® Computer Vision SDK Beta R2
For computer vision, deep learning, video solutions (such as security cameras), or office automation, top systems may incorporate multi-channel streaming, real-time software-based analytics, and more. On the heels of its newest release, you can get your geek on to integrate intelligence into your apps with the updated Intel® Computer Vision SDK (Intel® CV SDK) Beta R2. It delivers improved runtime performance, code algorithm efficiencies, and enhancements to the Deep Learning Deployment Toolkit. And we can’t forget – new support for more OSs: Windows 10*, Ubuntu 16.04*, and Yocto MR3*. Additionally, installation was improved for the OpenCL driver.
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Dive into the Fun Technical Stuff
See below the details of what's new in this release.
Improved Deep Learning Tools
- New support for TensorFlow*, a deep learning framework (partial features apply to GoogleNet V1, V3).
- Horizontal fusion support for Caffe*.
- Custom Layers support on GEN.
- Provides an application to verify the actual inference on the target hardware to validate accuracy (top1/top5) on image classification problems and to measure performance (in FPS) for selected batch sizes.
New topologies are now supported
- SqueezeNet, GoogleNet (Caffe V2,V3), Resnet (50, 101, 152), SSD, YOLO1
- Improved performance of our Inference Engine on CPU and our GPU/GEN Graphics processor.
- Intel® CV SDK OpenVX Runtime internal optimizations make computer vision building blocks more efficient - reducing development time-to-market.
- Improved scheduling with Intel® Threading Building Blocks closed the gap for heterogenous use cases and give you the ability to control where your code is running easily (CPU, GPU and so on) without writing targeted code for each hardware platform.
- Intel® Math Kernel Library for Deep Neural Networks (Intel® MKL-DNN) integration and CNN extension fusion improves the deep learning workloads performance.
New Features in the Vision Algorithm Designer (VAD)
- The new version supports OpenVX legacy code and provides the ability to upload legacy OpenVX code and generate Graphml for backwards compatibility.
- Application tracing and performance analysis capabilities help you as a developer improve code performance.
- Deep learning application support helps you to better understand optimized deep learning OpenVX Graphs.
- Model Optimizer generated code in VAD provides the ability to debug the application.
- OpenCL™ Custom kernel code generation is now supported.
Additional OS Support, OpenCL Driver Installation Improved
The new release includes support for Windows* 10, Ubuntu* 16.04, and Yocto* MR3; and supports OpenCV* 3.3. Additionally, a new easy-to-install and use OpenCL driver is included.
The Computer Vision SDK supports these Intel® platforms:
- 6th generation Intel® Core™ processors
- Next-Generation Intel® Atom processors
Download the Intel Computer Vision SDK now.
About the Intel Computer Vision SDK
The Intel Computer Vision SDK is a comprehensive toolkit for developing and deploying computer vision solutions on Intel® platforms, including digital surveillance cameras, robotics, autonomous vehicles, office automation, mixed-reality headsets, and more. Based on OpenVX*, this SDK offers many useful extensions and supports heterogeneous execution across CPU and SoC accelerators using an advanced graph compiler, optimized and developer-created kernels, and design and analysis tools. It also includes deep learning tools that unleash inference performance on deep learning deployment.
More Resources & Support
Get a quick overview and development shortcuts in this free webinar recording: Develop Smart Computer Vision Solutions Faster (via registering with the Embedded Vision Alliance), or download the PDF here.
Learn more about Intel Computer Vision SDK
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