Roboflow is a computer vision platform that provides tools for building, training, deploying, and managing computer vision models, making it easier for developers and organizations to create applications that understand visual data. Founded in 2020 by Joseph Nelson and Brad Dwyer, the company is headquartered in Des Moines, Iowa. Roboflow provides an end-to-end workflow for computer vision projects, starting from data collection and annotation through model training and production deployment. The platform offers a web-based annotation tool for labeling images and videos with bounding boxes, polygons, keypoints, and segmentation masks. It supports assisted labeling features that use AI to speed up the annotation process through model-assisted labeling and automatic label suggestions. Roboflow Universe is a public repository hosting over 250,000 computer vision datasets and pre-trained models contributed by the community, which users can use as starting points for their own projects. The platform supports training models for object detection, image classification, instance segmentation, and semantic segmentation using popular architectures including YOLOv8, YOLO-NAS, and other state-of-the-art models. Roboflow also integrates with foundation models like SAM (Segment Anything Model) and CLIP for zero-shot and few-shot computer vision tasks. For deployment, Roboflow provides hosted inference APIs, edge deployment options for running models on devices like NVIDIA Jetson and Raspberry Pi, and SDKs for iOS, Android, and web applications. The Roboflow Inference server can be self-hosted for on-premises deployment requirements. The platform includes dataset management features such as version control, augmentation, preprocessing, and health checks that identify potential data quality issues. Roboflow offers a free tier for public projects, a Starter plan for individual developers, a Growth plan for teams, and an Enterprise plan with dedicated support, custom deployment options, and advanced security features.
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