High quality training and test data are essential for the development of algorithms and functions for various automotive and industrial applications.
C.LABEL is an easy-to-use, flexible and extendable labeling software designed for the efficient annotation of data required for the development of autonomous driving algorithms and functions, as well as the testing and validation thereof.
Efficient labeling comprises the labeling of the data itself and continual quality control as well as effective correction mechanisms.
Thanks to our intelligent processing strategies (e.g. deep learning, interpolation and extrapolation, or automatic object recognition) the manual labeling effort is reduced while the quality of the data in the labeling process is improved.
CAL is our classification scheme for levels of automation in labeling tools. Our development approach strives for fully automated labeling by continuously developing algorithms and functions which can perform on certain automation levels according to project requirements.
The user interface of C.LABEL is designed to minimize the effort of the user by providing special features and enabling a flexible configuration depending on individual needs.
Multi-view and tabbing
The multi-view and tabbing functionality allows the user to visualize several data streams simultaneously as well as to drag them freely into the tool frame or view on a second monitor.
Bounding Box Labeling
Point Cloud Labeling
We can help you with the clarification of label specifications and project requirements, so that your ground truth data suits your needs.
We provide you with additional cost-effective solutions for large labeling projects encompassing project management, data management, workforce and much more.
Check out our page Turn-key Labeling Solutions for Automotive Data and learn more about how we can support you.
C.LABEL is part of C.IDS—CMORE Integrated Data Solutions.