The open source framework to easily build & deploy your computer vision solutions
Computer vision, quick and simple
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Computer vision, quick and simple
We select the best state-of-the-art algorithms available in Open Source in all major fields of Computer Vision (classification, detection, segmentation, pose…), and we test them for you.
Use all our algorithms without writing a single line of code.
Test OpenCV in 1 click or start using deep learning algorithms effortlessly.
Integrate your own algorithms into Ikomia STUDIO to test, compare and improve them.
Then run them anywhere, on any machine.
Our API allows you to deploy your Computer Vision applications on any remote computing server (Google Colab, AWS, GCP…) or on your own servers.
Inférence TransUNet for semantic segmentation.
Paper : TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation. J. Chen, Y. Lu, Q. Yu, X. Luo, E. Adeli, Y. Wang, L. Lu, A-L. Yuille, Y Zhou. Preprint 2021
Original code : github.com/Beckschen/TransUNet
Inference DeepLabv3+ from Detectron2 for semantic segmentation.
Paper : Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation. Liang-Chieh Chen, Yukun Zhu, George Papandreou, Florian Schroff, Hartwig Adam. ECCV 2018
Original code : github.com/facebookresearch/detectron2
Ikomia API is a Python library that allows you to easily prototype your Computer Vision application. Whether it’s a workflow from Ikomia STUDIO or a workflow from scratch, easily run state-of-the-art algorithms on any type of machine (desktop computer, calculation servers, cloud computing) in a few lines of code.
Apply an algorithm on your data in 1 click.
Keep an eye on your workflow.
Evaluate the results.
Easily configure your models
Papier : TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation. J. Chen, Y. Lu, Q. Yu, X. Luo, E. Adeli, Y. Wang, L. Lu, A-L. Yuille, Y Zhou. Preprint 2021
Modèle d’inférence DeepLabv3+ de Detectron2 pour la segmentation sémantique.
Papier : Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation. Liang-Chieh Chen, Yukun Zhu, George Papandreou, Florian Schroff, Hartwig Adam. ECCV 2018
Ikomia API is a Python library that allows you to easily prototype your Computer Vision application. Whether it’s a workflow from Ikomia Studio or a workflow from scratch, easily run state-of-the-art algorithms on any type of machine (desktop computer, calculation servers, cloud computing) in a few lines of code
Ikomia API to apply models to your images or videos in a few lines of code.
and easily open your images, videos, video streams and annotated datasets.
your idea quickly with state-of-the-art models and create your first PoC.
your CV solution on cloud or embedded system.
Ikomia API to apply models to your images or videos in a few lines of code.
and easily open your images, videos, video streams and annotated datasets.
your idea quickly with state-of-the-art models and create your first PoC.
your CV solution on cloud or embedded system.
You can install Ikomia API through the PIP package management system.
Our API is compatible with Python 3.7 / 3.8 / 3.9 .
pip install ikomia
Want to know what AI can do for you?
Want to know what AI can do for you?
