Best Video Annotation Tools for Lightly

Find and compare the best Video Annotation tools for Lightly in 2024

Use the comparison tool below to compare the top Video Annotation tools for Lightly on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

  • 1
    V7 Reviews
    A class-agnostic, pixel-perfect automated annotation platform. Built for teams that have a lot of data and strict quality requirements but little time. Ground truth creation can be scaled up 10x. Collaborate with unlimited team members, annotators and seamlessly integrate into your deep learning pipeline. Create ground truth 10x faster with pixel-perfect annotations. Use V7's intuitive tools for labeling data and automating your ML pipelines. The ultimate image and Video Annotation Solution
  • 2
    CVAT Reviews

    CVAT

    CVAT

    $33 per month
    CVAT, the leading data engine for machine-learning, allows you to annotate better. Teams at all scales use and trust CVAT for data of all sizes. CVAT's intuitive, lightning-fast user interface was developed in collaboration with real-world teams that are solving real-world issues. CVAT is used by the most ambitious AI teams in the world every day, from medical to retail to autonomous cars. CVAT can handle any input data and expected results. It works well with images, videos and even 3D. Bounding boxes and polygons. Points, skeletons. Cuboids. Trajectories. Automated interactive algorithms such as intelligent scissors, histogram equality, and others will help you annotate more efficiently. Get actionable insights from metrics such as the annotator's working hours, the number of objects per hour and more.
  • 3
    Label Studio Reviews
    The most flexible data annotation software. Quickly installable. Create custom UIs, or use pre-built labeling template. Layouts and templates that can be customized to fit your dataset and workflow. Detect objects in images. Supported are boxes, polygons and key points. Partition an image into multiple segments. Use ML models to optimize and pre-label the process. Webhooks, Python SDK and API allow you authenticate, create tasks, import projects, manage model predictions and more. ML backend integration allows you to save time by using predictions as a tool for your labeling process. Connect to cloud object storage directly and label data there with S3 and GCP. Data Manager allows you to manage and prepare your datasets using advanced filters. Support multiple projects, use-cases, and data types on one platform. You can preview the labeling interface as you type in the configuration. You can see live serialization updates at the bottom of the page.
  • 4
    Labelbox Reviews
    The training data platform for AI teams. A machine learning model can only be as good as the training data it uses. Labelbox is an integrated platform that allows you to create and manage high quality training data in one place. It also supports your production pipeline with powerful APIs. A powerful image labeling tool for segmentation, object detection, and image classification. You need precise and intuitive image segmentation tools when every pixel is important. You can customize the tools to suit your particular use case, including custom attributes and more. The performant video labeling editor is for cutting-edge computer visual. Label directly on the video at 30 FPS, with frame level. Labelbox also provides per-frame analytics that allow you to create faster models. It's never been easier to create training data for natural language intelligence. You can quickly and easily label text strings, conversations, paragraphs, or documents with fast and customizable classification.
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