Accelerate your end-to-end ML lifecycles with semi-automated image annotation using Azure ML

Many data and machine learning scientists have had the experience of working on a computer vision problem, e.g. While labeling data can be relaxing, our existence is impermanent. This is achieved by integrating the open-source web-based image annotation tool COCO-Annotator with a custom-built image segmentation or keypoint detection model that is trained and deployed on Azure. COCO-Annotator allows developers to easily review and correct inaccurate segmentation proposals for unlabeled data generated by the custom-built model. Corrected data can then be added to the training set for retraining the model.