Plainsight provides several label accelerator tools to make annotating your data faster and more efficient, many of which use AI to assist in speeding up the annotation process.
Plainsight makes it extremely easy to label image frames from video data. The user provides annotations for the first frame using rectangles and polygons, and Track Forward predicts the annotations for those objects in the next frame. This allows for fast labeling of video datasets since many object annotations can be generated automatically.
Labeling images with identical object placement from image to image (such as frames from a video) can be a tedious process, especially when objects appear in multiple images at the same position. When objects are stationary from one image to another, it can save time to copy a label forward. While this feature is not assisted by AI, it accelerates labeling by saving the user time having to label stationary objects.
SmartPoly is a mode that lets you draw a rectangular bounding box around the object that is automatically transformed into a polygon.
Auto Label is a labeling assistance feature that uses predictions from an ML model to automatically annotate an image. The model is pre-trained on the COCO dataset, a large dataset of common objects. Auto Label can be used with the Rectangle and Polygon label types.