the right data For
your vision model
Deep learning models need large amounts of training data, and it is difficult to ensure the right data is collected and annotated to improve performance.
SBX generates synthetic data to build and improve computer vision models. Synthetic data avoids the costly and slow collection + annotation requirements of using real data alone. Iterate faster and build vision models with stronger performance.
Training with synthetic data is the best way to build and improve computer vision models. SBX matches real-world sensors and scenes to generate endless simulated variations.
By combining a small amount of real training data with a large synthetic set, models reach peak performance. Rapidly iterate on datasets to solve real-world vision tasks.
Save the compute time needed for training with SBX vision models. Data is a critical step to building a vision model, but when time is of the essence, it’s useful to skip development.
better vision Models
with SBX Robotics
Synthetic data is an exciting new way to accelerate computer vision. Training with synthetic data produces robust deep learning models, using only a small fraction of real data. Using synthetic data is the right way to build and improve computer vision models
Companies who choose us
Streamlined Data Processing
Training on synthetic data helps you develop powerful deep learning models without having to collect, label, and clean real data. This is currently the fastest way of bootstrapping and improving computer vision models.
Get Time & Cost-Effective Training
Using simulation software enables us to create training data that’s up to 10x faster and more cost-effective than other annotation services or in-house teams.
Optimized for Top Performance
Every SBX dataset goes through rigorous testing and optimization to ensure the best possible performance on real-world data.
The Power of SBX Robotics
SBX Robotics uses technology from film and gaming to create realistic, perfectly labeled training datasets that support object detection, segmentation and 6D post estimation models.
- Clients send 25 images from their robot’s camera and in turn, receive 25,000 perfectly labeled synthetic training images. SBX’s data is ready for use by deep learning computer vision models.
- Synthetic data gives data scientists and developers full control. Long gone are the days of unreliable, incomplete data. You don’t have to struggle to find data for machine learning at any scale.
- Real data tends to be supplemented with synthetic data as a means of creating enhanced observations and trends.