With our procedural engine, simply set your desired parameters and watch as Helios generates the scene for you.
Generate your own custom datasets on-demand. Save time and resources while gaining full control over scene configurations for AI training.
Each image in your dataset comes fully labeled. Enjoy pixel-perfect labels without bias, enabling your models to learn from high-quality data that reflects real life.
With more than 50 adjustable parameters, configure scenes according to your specifications—from sensor settings and lighting conditions to activities and labels.
Helios allows you to instantly preview images during your session, so you can refine scenes on the fly and get the quality you expect.
1.
Get Started
Create a project and add your first batch. You can add as many batches as you want to each project.
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.
Configure the images you need in minutes
Click to generate
Download your automatically labeled dataset
Configure with more than 50 parameters and optimize your dataset.
Add various human activities to your scenes. Select the gender, age, ethnicity and physical characteristics of the human participants.
Flexible pay-per-use system. Datasets are stored securely and delivered via the cloud—no minimum or a maximum number of images. Expand your datasets incrementally as needed.
Labels are pixel-perfect and bias-free.
Our data has been successfully used to train models in various areas, including:
Fall Detection
Abandoned Luggage Detection
Weapon Detection
Human Detection
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Choosing between synthetic data and real-life data for AI model training is both a strategic and technical decision. Each option has its advantages and challenges, and the right choice depends on multiple factors such as data availability, quality, ethical considerations, complexity, and cost. Let’s explore how to make this decision effectively, navigating five critical questions. […]
In computer vision, developing robust and accurate models depends on the quality and volume of training data. Synthetic images, generated by procedural engine, have emerged as a transformative solution to the data bottleneck. They empower developers to overcome data scarcity, reduce biases, and enhance model performance in real-world scenarios. Here’s a detailed guide to training […]
