Make the conditions repeatable.
Scene and asset preparation for repeatable image generation and computer vision workflows.
Control the scene. Define the dataset.
- Computer vision scene preparation
- Object and environment variation
- Dataset prototyping
Useful synthetic data begins with a clear definition of the task. Specify the objects, camera views, variations and labels you need, then validate a small sample before expanding the generation scope.
Scene & object scope
Object classes, scene composition and camera requirements agreed before production.
Variation plan
A defined range of viewpoints, lighting, materials and object arrangements.
Annotation specification
Requested label types and export structure, confirmed against your training pipeline.
Sample review
A representative sample and acceptance criteria before a larger generation run.
A useful starting brief
Include your vision task, object classes, camera setup, annotation format and expected dataset size.
Prepare your project briefWhat do you need
to simulate?
An individual asset, a complete scene or a starting point for something more specific.
Discuss a project