Unitlab is a computer vision data labeling tool focused on automation and quality control. It uses AI to speed up dataset preparation and reduce manual work for annotators.
AI-assisted labeling for images and video
Upload images or video frames, choose the annotation type, and get pre-labeled data to review. AI algorithms help with common CV tasks so humans can focus on verification and corrections rather than labeling from scratch.
Object detection and region segmentation
Scene or image classification
Pre-labeling to accelerate annotation workflows
Dataset management and curation
Unitlab helps organize large datasets and prepare training and test splits. You can filter by metadata and label quality, remove duplicates, identify problematic samples, and balance classes.
Metadata-based filtering and dataset structuring
Duplicate removal and hard-example review
Building training and test subsets
Model validation and quality control
Validate computer vision models on labeled data, track metrics, analyze errors, and loop back to re-label difficult cases. This supports faster ML iteration and reduces the risk of hidden issues in production.
Metrics tracking and error analysis
Iterative re-labeling for edge cases
