If you decided to start experimenting with Ikomia Computer Vision STUDIO, you are at the right place. For those of you who want to experiment by themselves, it’s a no code tool so just follow the in-app help and enjoy the experience!
In the team, we use the STUDIO on a daily basis to test, chain and train Computer Vision algorithms with the drag and drop system.
If you are searching for a short guide to kickstart you, this content is for you. If on the other hand you would rather follow a detailed guide, please read the Step by step user guide to start with STUDIO.
First steps with Ikomia STUDIO
What is it An intuitive no code interface to build a Computer Vision i.e. visual AI application from A to Z with a drag & drop system.
It integrates 140 ready-to-use algorithms (ocv_*). They are all categorized according to openCV’s categories for a seamless use. If you are eager to test Canny, Sobel or Clahe, they’re all there!
We are trying to cover the whole spectrum of Computer Vision, whether it is classification, object detection, object segmentation, pose estimation or generative algorithms.
And, icing on the cake, take full advantage of the Cuda acceleration to boost your calculations.
What does it do? It applies an algorithm on your data in 1 click, it enables you to build workflows with algorithms from any source and configure your models, it shows you the result on your images or videos instantly.
Where do I get more algorithms? This is where the magic begins: join the Ikomia Community to choose the algorithms that match your needs from our Open Source Ikomia HUB. More that 70 algorithms and 800 models have been selected and tested for you, and the team adds more each week. You will find the top-notch algorithms from your preferred sources: OpenCV, OpenMMlab…
But you can also create and integrate your own algorithms and mix them with other tested algorithms.
How do I start? First you need to download the STUDIO:
Then we suggest that you start testing no code Computer Vision with this quick tuto on how to run a facial detection algorithm from the HUB in Ikomia STUDIO.
It’s a good start !
We aim at covering the whole spectrum of Computer Vision, whether it is classification, object detection, object segmentation, pose estimation or generative algorithms. Just browse the HUB to see what fits your goal.
Now that you have started experimenting with the STUDIO, you might want to work with videos. Here is the perfect use case for you Mask R-CNN using CUDA backend from OpenCV 4.2.0.
A step further : training of custom and Deep Learning models
Now that you know how to prototype a Computer Vision workflow with the STUDIO, it’s time to start training. We will use the object detection YOLO algorithms to train an object detection model in less than 5 minutes. Yes, it’s quick ! Once your model is trained, you can easily test it within Ikomia STUDIO.
We’re always happy to take a sneak peek at your productions. You can share them by mail at community@ikomia.com and tell us whether you would like a feedback or if you wish to share with the community (or both!).
If you want to learn how to train well-known Deep Learning models on your data with Ikomia, you should definitely read this STUDIO use case. There is everything you need to know about classification, object detection and semantic segmentation. You will also discover the integration with mlflow.
And remember : your questions get answered on the Ikomia community Q&A page.
Be innovative with Ikomia !
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