Best Image Annotation Tools for Microsoft Azure

Find and compare the best Image Annotation tools for Microsoft Azure in 2025

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

  • 1
    Diffgram Data Labeling Reviews
    Your AI Data Platform High Quality Training Data for Enterprise Data Labeling Software for Machine Learning Your Kubernetes Cluster up to 3 users is free TRUSTED BY 5,000 HAPPY UBERS WORLDWIDE Images, Video, and Text Spatial Tools Quadratic Curves and Cuboids, Segmentation Box, Polygons and Lines, Keypoints, Classification tags, and More You can use the exact spatial tool that you need. All tools are easy-to-use, editable, and offer powerful ways to present your data. All tools are available as Video. Attribute Tools More Meaning. More freedom through: Radio buttons Multiple selection. Date pickers. Sliders. Conditional logic. Directional vectors. Plus, many more! Complex knowledge can be captured and encoded into your AI. Streaming Data Automation Manual labeling can be up to 10x faster than automated labeling
  • 2
    Appen Reviews
    Appen combines the intelligence of over one million people around the world with cutting-edge algorithms to create the best training data for your ML projects. Upload your data to our platform, and we will provide all the annotations and labels necessary to create ground truth for your models. An accurate annotation of data is essential for any AI/ML model to be trained. This is how your model will make the right judgments. Our platform combines human intelligence with cutting-edge models to annotation all types of raw data. This includes text, video, images, audio and video. It creates the exact ground truth for your models. Our user interface is easy to use, and you can also programmatically via our API.
  • 3
    Segments.ai Reviews
    Segments.ai provides a robust solution for labeling multi-sensor data, combining 2D and 3D point cloud labeling into a unified interface. It offers powerful features like automated object tracking, smart cuboid propagation, and real-time interpolation, allowing users to label complex data more quickly and accurately. The platform is optimized for robotics, autonomous vehicle, and other sensor-heavy industries, enabling users to annotate data in a more streamlined way. By fusing 3D data with 2D images, Segments.ai enhances labeling efficiency and ensures high-quality data for model training.
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