Luxand
3.4 out of 5 stars
(5 Ratings)
Luxand FaceSDK is a cutting-edge, cross-platform software development kit designed to deliver high-performance face recognition, identification, and facial feature detection. Perfect for software developers worldwide, Luxand FaceSDK integrates seamlessly with web, desktop, and mobile applications, enabling face-based user authentication, as well as automatic face detection and recognition, elevating the user experience to new heights.
Learn more about Luxand
SightRadar
SightRadar is a hosted face-recognition API for developers adding face-based search, comparison, and detection to applications. It indexes faces from photos into customer-managed collections, searches a collection using a selfie, compares two faces for 1:1 verification, and detects faces with confidence and quality results. Its API uses AWS Rekognition-compatible request and response shapes for supported operations, allowing existing AWS SDK clients to be pointed at the SightRadar endpoint. Developers can use the Python and Node/TypeScript SDKs or REST API. Use cases include event and wedding photo galleries, identity-check onboarding, media libraries, and other consent-based workflows. Images used for detection and comparison are processed in memory; indexed face embeddings are held in collections customers can delete. Processing is billed per photo, with separate charges for stored face vectors.
Learn more about SightRadar
Betaface
We offer ready components, such as face recognition SDKs, as well as custom software development services and hosted web services with a focus on image and video analysis, faces and objects recognition. Our technology is used by video and images archives, web advertising and entertainment projects, media content producers, video surveillance and security software solutions, end user and b2b software developers and others. Betaface facial recognition suite embraces whole range of complex operations from fundamental face detection through face recognition (identification, verification or 1:1, 1:N matching) to biometric measurements, face analysis, face and facial features tracking on video, age, gender, ethnicity and emotion recognition, skin, hair and clothes color detection, hairstyle shape analysis and facial features shape description. Our technology is used by video and images archives, web advertising and entertainment projects.
Learn more about Betaface
Amazon Rekognition
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.
Learn more about Amazon Rekognition