The Best Data Annotation Service For Machine Learning

Bounding Boxes

Bounding boxes are one of the simplest and most common image/video annotation techniques used to train computer vision models. By drawing boxes around objects of interest within the image, object classification and localization models can be trained with the right amount of data and accurate annotations.

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Cuboid Annotation

Similar to bounding (2D) boxes, cuboid (3D) Annotation require annotators to draw a cuboid around objects in an image, calculating the length, width, and approximate depth of the targeted objects as vehicles, buildings or even humans to get their overall volume.

Cuboids are commonly used in the field of construction, autonomous vehicle systems, augmented reality models, and other computer vision solutions.

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Polygonal Annotation

Polygonal Segmentation annotation is the perfect solution when dealing with objects with irregular shapes. Unlike boxes, which can capture a lot of unnecessary objects and noises around the target, polygons are more precise when it comes to localization and reduces confusion when training your computer vision models.

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Categorization

Image categorization is the process of classifying your products into categories, commonly used as an initial step in building computer vision models. For any computer vision models, assigning descriptive tags to each image can provide invaluable context and searchability.

Let our expert annotators categorize your images into your requested categories ensuring accuracy while eliminating annotator bias and human error.

Semantic Segmentation

The Semantic Segmentation or pixel-level labeling is used to label every pixel in the image into the segments you need your computer vision algorithm to recognize. Unlike polygonal segmentation, which is used specifically to detect a defined object of interest, full semantic segmentation provides a complete understanding of every pixel of the scene in the image and can be ideal when amounts of source data is scarce.

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Keypoint Annotation

Keypoint Annotation is used for identifying facial recognition or skeletal features of the human body to allow for movement-based algorithms for tracking human movements. We provide services to identify keypoints of objects such as faces, cars and other templates that match the task.

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Line Annotation

Lines and polylines help to detect all types of lanes on varied roads including city streets or highways for self-driving vehicles. Line annotation delineates boundaries between different parts of an image to distinguish different objects. Poly Lines are used for lane markings on roads to identify lane lines, lane markings on the road and drivable areas for autonomous vehicles.

Let our expert annotators help you create training datasets with our line annotation services.

Video Annotation

With Video Annotation, you can label and track objects through frames in the sequence of images with anything from a bounding box to full segmentation. Video annotation is used to train algorithms for a variety of tasks, from simple classification to the tracking of objects across multiple frames.

Let our expert annotators help you create training datasets with our video annotation services.