Self-driving vehicles depend on their ability to perceive their environment for safe navigation. Experts play a key role by annotating bounding boxes, helping the vehicle's computer vision system accurately assess the distance and size of objects on the road and along the sides.
Semantic segmentation enhances object detection in autonomous vehicles by grouping multiple objects of the same category as a single unit. This process involves classifying every pixel in an image based on its semantic meaning, such as identifying all cars or all people within the scene.
Autonomous vehicles rely on environmental perception to navigate safely. Specialists contribute by marking bounding boxes, enabling the vehicle's computer vision system to accurately determine the size and distance of objects on and around the road.
Access expert assistance to accurately trace polygons around irregularly shaped objects. This enables computer vision systems in autonomous vehicles to detect all visible objects on the road, such as motorcycles, bicycles, cars, and animals, ensuring safe driving by preventing collisions.
Yes, it is! No credit card is required to use Unitlab. You can use the Unitlab tool for free forever as long as you stay within the set limits. However, for more extensive use, Unitlab offers a subscription model. This model's pricing is customized to your organization's specific usage, data requirements, and any extra services you might need, like our advanced labeling solutions. To get a tailored quote and further information, please connect with our sales team.
Yes, you can start working with a Free Plan and then change plans in the future as you evaluate which is best for you.
Data Labeling Services start at just $0.02 per image. The base price depends on the types of data annotation, the number of classes, and the average number of objects to annotate per image.
Unitlab offers a range of scalable On-Premises solutions! Contact Us to discuss your requirements. You can purchase Unitlab's On-Premises solution after consulting with us. We help you install our entire annotation system in your workspace.
We care about your data and use cookies solely to enhance your experience. By using this website, you agree to our cookie policy. Learn more about our Privacy Policy and Cookies Policy.