Bounding Boxes Data Annotation Services
Worked with the following data annotation tools.: Hasty, Label studio, Labelbox, Labelme, SuperAnnotate, Supervisely, v7
Worked with the following data output formats.: COCO, COCO Keypoints, JSON, YOLO
Worked with the following data annotation types.: 3D cuboids, Annotation image categorization, Bounding boxes, Landmark / Keypoint, Object labeling / tagging, Polygon (segmentation), Semantic segmentation, Video object tracking
The most commonly used annotation type is 2D bounding boxes. They are easy to apply to machine learning models and faster to annotate in comparison to other annotation types. Due to the inherent instance-awareness of bounding boxes, your algorithms will get a better understanding of the concept of specific objects and -if you want- track certain objects throughout the sequence. Bounding Boxes are most often used for testing and validation of new sensors or for tracking of objects in sequential data.