GAIA

Generate Synthetic Images with Procedural Engine in hours!

Effortless Image Data Generation with a Procedural Engine

Gaia Procedural Engine offers full control over scene parameters:

1.

Get Started

Create a project and add your first batch. You can add as many batches as you want to each project.

launch your AI Verse data generation

2.

Set the scene

Select the type of environment you need. Add specific objects of interest from a catalog with 3D assets. Your objects of interest are automatically added to each scene.

3.

Call the Action

Select the activities you are interested in. Set various parameters related to the characters you are adding such as age, gender, physical characteristics, ethnicity, etc.

4.

Lights

For each batch, select several lighting scenarios from a catalog including various artificial and natural lighting conditions. You can even simulate pictures taken with a flash if desired.

5.

Camera

Set your camera’s intrinsic and extrinsic parameters to match your use case. For example, simulate images from a fixed surveillance camera, a drone, satellite image.

6.

Generate

Select the labels you need among instance and semantic segmentation, depth image, 3D normal image, albedo image, Lambertian reflectance model, or skeleton key points. Next, choose the number of scenes and images per scene. Then, generate your fully labeled dataset.

Generate Images in days, not months with Procedural Engine GAIA!

Examples of Synthetic Images Generated with Gaia:

Use Cases

Our Synthetic Images Have Been Successfully Used to Train Various AI Models:

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Training a tank detection model using conventional data presents several challenges. One of the biggest obstacles is the scarcity of labeled data. Tanks are not everyday objects, and acquiring enough annotated images for training is extremely difficult due to confidentiality of images.

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Generate Fully Labelled Synthetic Images
in Hours, Not Months!