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For computer-vision teams, researchers, and businesses preparing image datasets or building image recognition models, SentiSight.ai brings image annotation and model development into one web platform. Label images with classifications, bounding boxes, polygons, points, polylines, or bitmaps, and use smart selection to help mark objects. Similarity-based labeling can suggest labels for new images based on labeled examples, without first training a model. Teams can share labeling projects, manage user permissions, review work by contributor, and track labeling time. Once images are labeled, users can train classification, object detection, and segmentation models, then use models through the platform or REST API, or download supported models for offline use. Pre-trained models are also available for selected image-recognition tasks. The platform also includes image similarity search to find images like a query image or identify similar pairs within a dataset. SentiSight.ai may suit users who need to prepare image data collaboratively, experiment with custom computer-vision models, or search and organize large image collections.
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