Azure Computer Vision

Image recognition technology that provides true understanding of your digital media. With our on-device computer vision model, users can expect an average response time of less than 250ms. This is more than 4x faster than using our API and does not require an internet connection. Users can recognize objects in a space by simply scanning their phone around a room, eliminating the need to take individual pictures. This feature is unique to our on-device model. By removing the need for data to leave the end-user device, privacy concerns are virtually eliminated. While our API takes every precaution possible to protect your privacy and data, our on-device model raises the bar on security substantially. Send CloudSight your visual content, and our API will generate a natural language description in response. Filter and categorize images, monitor for inappropriate content, and automatically assign labels for all of your digital media.

Amazon Rekognition makes it easy to add image and video analysis to your applications using proven, highly scalable, deep learning technology that requires no machine learning expertise to use. With Amazon Rekognition, you can identify objects, people, text, scenes, and activities in images and videos, as well as detect any inappropriate content. Amazon Rekognition also provides highly accurate facial analysis and facial search capabilities that you can use to detect, analyze, and compare faces for a wide variety of user verification, people counting, and public safety use cases. With Amazon Rekognition Custom Labels, you can identify the objects and scenes in images that are specific to your business needs. For example, you can build a model to classify specific machine parts on your assembly line or to detect unhealthy plants. Amazon Rekognition Custom Labels takes care of the heavy lifting of model development for you, so no machine learning experience is required.