SANTA MONICA, CA, November 5, 2019—HyperLabel Developer – a full-featured desktop application for creating labeled datasets for Machine Learning (ML) quickly, easily and with complete privacy – is now available free, with no label quantity restrictions.
HyperLabel Developer offers the fastest path to implementing ML and allows individual data scientists, developers and engineers, as well as large, in-house or distributed labeling teams to create high-quality training datasets in any quantity free of charge.
Sixgill, LLC, which first introduced HyperLabel in July, is revising HyperLabel Developer for unlimited use, free, making it more easily obtainable and inherently valuable for users. HyperLabel is continuing to build its fast-growing user community with a robust set of free, easy-to-use features so developers and other data experts can spend more time training models and less time labeling.
Stand-alone, self-hosted, and anchored to the desktop for image and video labeling, HyperLabel Developer is fast, accurate and private. The application guides users through a quick, easy, step-by-step process. In just a few clicks, users can set up projects, import imagery, define schemas and begin labeling. With HyperLabel, labeling speed and ease of use do not compromise the quality of data sets generated. Application features include:
- Complete Privacy and Control: Import files from local drives or cloud storage. There’s no need to upload anything to a HyperLabel cloud.
- Simple User Experience: Get from project setup to label export in five simple steps. HyperLabel is easy and intuitive to use, even for non-engineers.
- Custom Schemas: Rectangles, polygons, point, feature points, free text, select, and multi-select.
- Flexible Scalability: Manage small-to-large, simple-to-complex labeling projects.
- Easy Export: Formats include JSON, COCO, Pascal VOC, and YOLO.
For users seeking even more speed and flexibility for ML projects, HyperLabel is also unveiling HyperLabel Studio services that allow customers to focus on the bigger picture. Services include:
- Managed Labeling: HyperLabel’s skilled data labeling team will manage labeling projects for customers to produce fast, accurate image and video annotations.
- Custom Model Building: HyperLabel’s expert ML engineers will build, train and deliver custom ML models to meet specific project needs and deadlines.
In addition, HyperLabel meets the needs of enterprises and large data science teams with custom installations of HyperLabel. Contact HyperLabel for details.
“We’re stoked to realize the great potential of deep learning ourselves, and strive to remove pain from data labeling and ML model building for data experts and developers around the world,” says Logan Spears, Innovation Chief at Sixgill. “We can’t wait to experience and share the innovation yet to come as HyperLabel helps others take the fastest path to Machine Learning.”
For more insights on how HyperLabel was developed and launched, see Logan’s article “Pain & Label: Why and How We Built Our Own ML Data Labeling Tool and Released it Free for Everyone” in the online publication Machine Learning.
Future HyperLabel versions will offer even more advanced capabilities such as ML-assisted object tracking and pre-trained architectures, cloud collaboration, advanced QA, import/export support, and labeling of 3D data types including DICOM and LiDAR.
Sixgill provides a full suite of universal data automation and authenticity products and services that enable organizations to govern IoE assets. With the Sixgill® product suite, organizations easily acquire, analyze and act on IoE data, at any velocity or scale. Meeting the increasing necessity for end-to-end sensor data management, process automation and analytics for sensor-informed operations, Sixgill offers Sense™ for IoE data enrichment and automation, Sense Vision™ for ML-based camera data intelligence, and Integrity™ for blockchain-based authenticity. HyperLabel™, by Sixgill, is a desktop application for creating, automating, updating, and managing annotated datasets for Machine Learning. To learn more, visit Sixgill.com.