Welcome back to the OpenVINO channel
On previous video, we saw how to set up the CVAT,
which is a free open source annotation tool
How to load the data in, how to annotate it and how to generate the labels file.
On this video, I'd like to show you how to use OpenVINO for automatic annotation,
All you'll have to do is to review the results and correct them where needed.
I go again to the CVAT git hub page, Installation guide,
Under advanced topics, you can see the additional components..
We'll need the "auto annotation using DL models in OpenVINO toolkit format"
We basically need now the installation file of OpenVINO..
It says here OpenVINO R5, but any version should work.
I'll just google for OpenVINO
Linux
And I will just save the zipped installation file..
The OpenVINO installation file should be located at CVAT/Components/OpenVINO
There is a different kind of Docker container we need to build
Let's go back to the CVAT directory
And run the docker..
And we are almost ready to go..
In order to perform auto annotation we need 4 files
The first 2 are the IR files, .bin and .xml for the OpenVINO DL model we'd like to use
The 3rd one is a labels file and the 4th file is an interpretation script in python..
This file is required to convert the outputs of the neural network to a result,
to a label, that CVAT can understand...
My data video is a crossroad so I can use the first example..
You already know how to get models from our model zoo..
check out Video 20..
And I will place the 4 files under CVAT/Utils/auto_annotation
The two IR files In this case, person-vehicle-bike detection
The labels_map json file with the labels that I just copied from the example..
And you can edit for your model
And the interpretation file which I just copied from the example
The 4 files are in place, CVAT is running in the docker container,
And I open the Chrome browser (please note that it's working only on Chrome)
And we can get to work..
Let's open the job..
You can see that nothing is annotated yet
Now let's go to the model-manager Give a name to our model
And select all the 4 files..
And hit submit..
Now we run "auto annotation" We choose the model to use
And we need to map the models labels to our labels..
A person is a person and a car will be what the model detect as vehicle
And we hit start
The annotation runs on CPU on all the frames in the data-set
And when we open the video file, we see lot's of annotation already there
Some of them will be wrong and we'll need to delete them
Some of them will need a minor correction But as you can see 90% of the work was done automatically
Now I'm going to open the menu, save my work And dump the annotation to any format you'd like
So we saw how to install the OpenVINO as a component to CVAT,
how to setup the auto annotation files and how to run auto annotation
As you saw from the example, it can basically save you most of the work, of course if your DL model is good enough..
CVAT is a great add to OpenVINO offering,
it is free and easy to use, and can save you a lot of effort.
subscribe to our channel to get more videos like this
Thank you