Semantic segmentation of any object in 3D point clouds.
We support segmentation of any object in 3D that might be difficult to describe with a cuboid. Examples include:
Simply send sensor data to our elegant API and receive impeccable ground truth data. We'll handle the rest.
client.createLidarsegmentationTask(
{
instruction: 'Please label all cars, pedestrians, and
cyclists in each frame.',
labels: ['car', 'pedestrian', 'cyclist'],
callback_url: 'http://www.example.com/callback',
},
(err, task) => {
// do something with task
}
);
Our APIs accept sequences of temporally linked frames, allowing us to produce 3D tracks for detected objects. Use this data to train your perception models.
We support a large and growing number of labels for 3D labeling, from cars and cyclists to construction cones and animals. Leverage our expertise.
We provide simple interfaces to send over LIDAR, camera, and radar to provide a comprehensive 3D scene. We aim to be the one interface for 3D perception.
We apply machine learning in a multitude of ways to make our workforce more efficient and ensure impeccable quality and accuracy.
Each customer is paired with a dedicated customer success engineer who ensures smooth integration and service.
We process millions of tasks each month and are built to rapidly scale up and down to meet your requirements.
Get started today with on-demand, or chat with us about an enterprise plan.
Enterprise-grade SLAs include task completion times and tasks can be rapidly scaled up or down to meet your needs.
Each enterprise customer is paired with a dedicated customer success manager who will ensure smooth integration and continued service.
Enterprise engagements include upfront and volume-based discounts, and is the most cost-effective solution for high-quality labels. Plus with Scale, there are no platform fees.
Industry leading quality datasets safe-guarded against ever-changing, messy data.
Our tasks are annotated by trained and qualified workers with additional layers of both human, data and machine learning driven quality control checks.
The resulting accuracy is consistently much higher than what a human or synthetic labeling approach can achieve independently, as measured against rigorous quality areas for each annotation.
We already support machine learning for some of the biggest autonomous vehicle and computer vision companies in the world.
“Scale has a team of very talented engineers who really understand the problems in training machine learning models, of data annotation, and of data quality.”
“Scale is a critical part of our stack, providing both software & trained resources to label our LIDAR and camera data with extremely high quality. When the team comes to me with new projects, I’m always confident that Scale will meet our needs & timelines.”