Adverse Weather Simulator

Adverse Weather Simulator

At DeepLux, we know that the power of AI lies in the quality of its training data. That’s why we’re developing cutting-edge simulation tools to enhance visual clarity and optimize performance for downstream tasks like object detection. For example, our innovative Rain Simulator uses physics-based modeling to transform ideal datasets—like images captured on a sunny day—into realistic rainy-night scenarios. This approach ensures our models are prepared for the challenges of real-world environments, delivering unmatched accuracy and adaptability.

Revolutionizing Training Data: The Power of Physics-Based Image Simulation

Our physics-based lighting level simulator is a critical key towards developing robust training datasets that go beyond simple brightness/contrast adjustments.

  • Reduce data collection costs

  • Improve edge case performance

  • Physics-based

Real-World to Simulated:
Side-by-Side Comparisons

Real vs Sim-1

Real vs Sim-2

Before After

Real vs Sim-3

We leverage the physics behind real environments to build our image simulation tools. From the behavior of water on glass to the density of fog at a distance, understanding our imaging scenarios is key to pushing the boundaries of quality and performance.

Ready to see the difference?

From extreme low-light conditions to adverse weather simulations, DeepLux is redefining what’s possible in computer vision.