In the previous video we have seen CVAT​
The computer vision annotation tool​
Which is free, open source, online ,multi platform and operating systems
Raw data is process by CVAT on a web UI
Underneath there are multiple micro-services that we launch with docker-compose​
Basically CVAT is running in multiple containers, each running a different task ​
You have here a service for the UI, for the communication and more.​
I ran (in previous video) all these containers on my local machine​
But you can run them anywhere, check out the installation for AWS and others.
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In this video we’ll add one service that will allow CVAT to communicate
with serverless functions that we will manage using nuclio​
A serverless doesn’t mean that there is no server..​
It only means that you, as a developer, don’t have to care about the server behind the scenes.. ​
About setting it up, maintaining it and so on.​
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Nuclio is an open source serverless platform and we will use it to manage inference functions.​
So basically we can have inference services anywhere,
thanks to the flexibility provided by nuclio​
And get annotation services from them directly to CVAT…​
Let me show you how.​
You can always refer to this serverless tutorial, in this QR
In documentation go to advance, and semi and full automatic annotation,​
We are running a new container we call “serverless”​
And you can see the configuration in the yaml file​
When done, you can see a new container running, nuclio-storage-reader​
And let’s install nuclio command line tool​
And create a project in nuclio​
And now we can run the models that are already in our repository​
Under cvat directory​
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And few options here, let’s goto OpenVINO​
Open Model Zoo​
Public​
And Yolo-V3​
Under function.yaml you can find the list of labels and other instructions for nuclio​
This is the main function and the model handler is the actual inference function we are running​
And if you run your own model you have here a reference for generating this file..​
We can now run the dext model, and let’s go to local 8070​
And in the nuclio panel you can see cvat and the openvino dextr model is coming up​
And our list of containers has now not only the nuclio reader,
but also the OpenVINO dextr function ​
And I’ll launch also the yolo model.. ​
Building and running​
And I have now 2 serverless functions, 2 models I could use..​
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Going back to our task,​
I can now use the AI-Tools, ​
Detectors, yolo-v3​
annotate​
And this frame is fully annotated, I have to review and make fixes if needed​
But this is only one frame,​
What I really want is to automatically annotate the full video​
So automatic annotation, use YOLO V3​
I’ve added few labels to make it more interesting​
And this process of annotating the full video can take some time,​
But, yea, I’m getting a coffee​
And it’s done​
And the full video was automatically annotated, ​
Exactly what we wanted​
Free, Open, Very flexible, very powerful and pretty intuitive to use​
CVAT is my annotation tool,​
Thank you​