Open source tools to build and deploy Computer Vision at scale

The open-source toolset to accelerate your project by 5x and put it to production smoothly

The streamlined path to Computer Vision solutions

It takes a lot of trials, trainings and combinations to develop a Computer Vision solution, with diverse input and output structures, dependencies, sources and libraries incompatibilities.

We have simplified the entire process.

Tailor-made tools to ease the creation of Computer Vision applications

280+ easy to use SOTA algorithms
#HUB

300+ ready-to-use SOTA algorithms

We've carefully curated the best open-source SOTA algorithms, and packaged them so that they respond to the same Python commands.

A growing library focused on vision to provide 300 algorithms in image classification, object detection and segmentation, pose estimation, text detection and recognition…

#API

Prototype seamlessly
with the API

Develop Computer Vision solutions without worrying about installation, dependencies and compatibilities.
You can train, test and build workflows by reusing the same code patterns.

Feel free to mix all algorithms from the HUB, inputs and outputs become universally compatible.

Adopt the STUDIO, the vision prototyping User Interface
#STUDIO

Or adopt STUDIO, the vision desktop application

You would rather use a friendly UI than Python code? We developed the application version of the API for you.

Build inference and training pipelines and watch the results at once in the same window.

#SCALE

Put to production with SCALE [Beta version]

We had a dream that Computer Vision solutions could be deployed for users without setting and maintaining a complex infrastructure.

So we built an automated deployment SaaS platform for engineers to transform projects into businesses without the need for DevOPs knowledge.

#HUB

Easy access to your preferred libraries and sources

Without installation, dependency or compatibility issues

Style transfer
Style transfer
Tracking
Tracking
Panoptic segmentation
Panoptic segmentation
Semantic segmentation
Semantic segmentation
Classification
Classification
Inpainting
Inpainting
Action Recognition
Action Recognition
Instance segmentation
Instance segmentation
Object Detection
Object Detection
Optical Flow
Optical Flow
Emotion Recognition
Emotion Recognition
Colorization
Colorization
Scikit
Scikit
Text Recognition
Text Recognition
Dataset Loader
Dataset Loader
Background matting
Background matting
Text detection
Text detection
Pose estimation
Pose estimation

Build solutions from A to Z...

Test algorithms, chain them in workflows whatever the source or library, create your own algo and train models.

Selection and tests

Find algorithms
STEP 01

Find algorithms

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Experiment
STEP 02

Experiment

Adjust settings
STEP 03

Adjust settings

Prototyping

Train
STEP 04

Train

Ikomia test
STEP 05

Test model

Chain algorythm
STEP 06

Chain algorithms

Test
step 07

Validate

Product image ikomia
STEP 08

Export your workflow

...then put them to production

with SCALE, the automated Computer Vision deployment SaaS platform. Transform your workflows and models into ready-to-use endpoint APIs in a few clicks.

Your solution is deployed at scale on a robust and secure cloud infrastructure.

#API

Build with Python API

#STUDIO

Create with STUDIO app

#SCALE

Deploy with SCALE