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Lightly AI is for machine-learning and computer-vision teams that need to build useful training datasets from large collections of images and videos. It helps teams find the samples worth reviewing and labeling, rather than relying on manual inspection or training on every available item. Explore datasets using metadata filters, visualizations, and embedding-based search, including searches by text or image. Sampling tools can help identify diverse examples, remove near-duplicates, find outliers, locate similar data, and balance selections across classes or other metadata. These workflows can help teams spot gaps and reduce redundant or low-value samples before training. Lightly AI also supports image and video annotation, annotation review and quality checks, and evaluation of model predictions against ground truth. Teams can curate and export subsets for labeling or model training, and use the Python SDK and browser interface to work with their data. It may suit teams building computer-vision models who want data exploration, curation, annotation, and evaluation in a shared workflow.
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