# Lightly Computer vision data curation, labeling and model training for ML engineers. - Findings24: - Site: - Preços: Freemium - Categorias: Ferramentas Dev IA, Limpeza de dados com IA ## O que é Lightly? Lightly is a computer vision platform for ML engineers and organizations managing visual datasets and developing models. It connects data selection, annotation, quality review and model evaluation in a shared workflow. Its two core products serve different stages of development: **LightlyStudio** provides dataset curation, labeling, visualization and management, while **LightlyTrain** supports self-supervised pretraining. Teams can explore their data, select samples for annotation and inspect model errors before preparing datasets for downstream training. ## O que Lightly pode fazer? ### Embedding search and sampling Indexed data receives automatic embeddings. Combine metadata filters with text or image search, then sample for diversity, deduplication, outlier detection, similarity or class balance. ### Annotation and quality review Create, edit and review annotations in the same workspace. Labeled objects receive individual embeddings for object-level search and clustering; annotations are versioned. ### Model error analysis Evaluate detection, classification and segmentation against ground truth. Inspect per-sample metrics and a confusion matrix, then sort by false positives, false negatives or mean intersection over union. ### Python plugins Install plugins for SAM3 segmentation, LightlyTrain auto-labeling and video bounding box propagation. Register custom Python functions with forms so colleagues can run them from the interface. ### Team access controls Assign Viewer, Labeler, Editor or Admin roles to control browsing, annotation, workspace configuration and administration. Cloud credentials can be managed centrally. ### Dataset export Export annotations or filenames through the interface or Python. Choose a full dataset or a subset filtered by tags or queries, with formats including COCO, YOLO and Pascal VOC. ## Casos de uso ### Prioritize a labeling backlog For a large collection of raw images, select a varied subset and remove duplicates before assigning annotation work, focusing labeling effort on samples that expand dataset coverage. ### Investigate model failure patterns After evaluating a model, inspect its worst predictions to identify recurring errors and decide which examples need annotation review or additional training coverage. ### Explore egocentric video datasets Organize action clips with captions and metadata for robotics research. Lightly demonstrates this workflow with more than 37,000 EPIC-KITCHENS-100 clips, using embedding plots, text search and diversity sampling. ## Perguntas frequentes ### How do LightlyStudio and LightlyTrain differ? LightlyStudio handles dataset exploration, curation, annotation and evaluation. LightlyTrain focuses on self-supervised pretraining for computer vision models. ### Can teams automate labeling? LightlyStudio supports SAM3 and LightlyTrain auto-labeling plugins, alongside manual annotation and review. A separate plugin supports propagating video bounding boxes. ### Can Lightly fit an existing ML workflow? Lightly provides Python interfaces for custom plugins and dataset exports. Its supported export formats let teams prepare annotations for downstream training tools. ### Is there a free starting option? The website invites users to try LightlyStudio for free and offers demo bookings. ## Informações rápidas - **Category**: Computer vision platform - **Primary users**: ML engineers and organizations scaling computer vision - **Core products**: LightlyStudio and LightlyTrain - **Related service**: LightlyServices: training data services for LLMs, AI agents and computer vision - **Website**: https://lightly.ai