Welcome back to the oneAPI channel.
Take almost any deep-learning based model,
If you don’t have one, we have tons of them ready, all yours
Want to re-train the model with your data-set? Sure
Want to optimize, squeeze, prune? No problem
Run on CPUs, GPUs, VPUs or all together? possible
On Windows, Linux, macOS?
Sure, it’s all open source
Want to build a demo in minutes? We have so many of them..
Benchmark inference? Video compression? All together, the full workload? Of course,
Want to build a deployment server yourself?
On Azure? On the edge? On the cloud? Yes again..
Sounds like a dream? Well, this is OpenVINO
Let me tell you all about it
In previous videos we have talked about the oneAPI components.
We mentioned the multi-device multi-vendor open spec libraries..
That can now work on multiple devices, CPU, GPU and others, what we call XPUs..
And are arranged into toolkits, One of them is OpenVINO.
Powered by oneAPI and implementing the vision of oneAPI of unified cross-architecture programming perfectly
Let me give you the highlights in few minutes
There are many reasons why OpenVINO is so popular and adopted by so many products in the market
but in a very high level I would say that the main reasons are
1. Simple. You can execute inference with
really just few lines of code of python C or C++ Yet, the API is flexible enough to allow for all
the fancy stuff like batching, asynchronous execution and many runtime operations
2. Performance. OpenVINO usually give you
much better performance than any other engine or framework
It can be sometimes up to 2x faster with 5x less memory consumption
Depending of course on the model, the platform and more..
3. Portability OpenVINO inference engine allow you
to run almost the same code on totally different platforms with totally different architecture
So the same code can run on a 1 Watt Movidius based VPU and on 100W Intel CPU or GPU, with best
performance on all these platforms And 4 Comprehensive
OpenVINO is really a full echo system with all the tools and resources
you need in order to build a real product
Just a quick walk through the developer's journey with OpenVINO..
You have multiple ways to use OpenVINO
Run it in a docker, get it and install with Apt, yum, anaconda Download the package or build from source
Use it in the Intel remote DevCloud Try it out in the juyter notebooks
On Linux, Windows, MacOs, Raspbian,
Bring your model. It could be vision, audio, text, we support many types of model
In many formats
If you’d like to compress, quantize, prune or apply many others optimization we have the NNCF framework
If you’d like to re-train models with your data-set, we have the training extensions
And we can easily re-shape, scale, change the format of your model,
add or remove layers and more
And if you do not have a model, we have tons of them in the Open Model zoo
You can find here models for detection, classification, segmentation, re-identification,
2D, 3D, audio, NLP and many others They are highly optimized for inference,
and you can use them for demos or in your production application.
The inference-engine API is easy to use, in Python, C or C++
And we have lots of sample code you can use as reference
It will be almost the same code if you’d like to run on an Atom based CPU or a Xeon machine,
an integrated or discrete intel GPU, VPU and more.
And we have ready benchmarking utilities that you can run locally or on the DevCloud to measure the
performance like the DL-workbench for example
DL-streamer can help you build a full pipeline, a full application using a few lines of code
A really simple yet powerful way to build a Gstreamer based workloads, that includes inference,
tracking, messaging and more, Use it to prototype the full workload or
as an inference serving utility.
And if you care about decode encode and video acceleration Media-SDK which will be replaced by oneVPL,
the video processing library is also included
As well as OpenCV, OpenVX and more
If you are ready to deploy, we have several options for example the OpenVINO Model-server,
few minutes and you have an inference server on an edge device or the cloud
There is much more to it, of course And there are also many resources available to learn from
I can talk forever on OpenVINO, and I actually do,
We have a very long playlist on OpenVINO in this QR code.
We explain the concepts, how to get started, how to build demos, special features and more.
Check it out
OpenVINO, a full echo system for AI deployment, and much more.. Enjoy and don't forget to Subscribe
more content like this video Thank you