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HAQM Rekognition

What is HAQM Rekognition Image?

Rekognition Image is a deep learning powered image recognition service that detects objects, scenes, and faces; extracts text; recognizes celebrities; and identifies inappropriate content in images. It also allows you to search and compare faces. Rekognition Image is based on the same proven, highly scalable, deep learning technology developed by HAQM’s computer vision scientists to analyze billions of images daily for Prime Photos. The service returns a confidence score for everything it identifies so that you can make informed decisions about how you want to use the results. In addition, all detected faces are returned with bounding box coordinates, which is a rectangular frame that fully encompasses the face that can be used to locate the position of the face in the image.

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Rekognition Image detects objects, scenes, activities, and landmarks. Rekognition Image also detects dominant colors and measures image brightness, sharpness, and contrast. These capabilities enable you to generate metadata for your image libraries for search and filtering as well as identify the quality of your images.

Rekognition Image enables you to use an input face to search for similar matches in a collection of stored faces. You can create a collection of faces detected from your images. Rekognition Image’s fast and accurate search returns faces that best match your input face.

With Rekognition Image, you can locate faces within images and analyze face attributes, such as whether or not the face is smiling or the eyes are open. When analyzing an image, Rekognition Image will return the position and a rectangular frame for each detected face.

Rekognition Image lets you measure the likelihood that faces in two images are of the same person. With Rekognition, you can use the similarity score to verify a user against a reference photo in near real time.

Rekognition Image enables you to detect explicit and suggestive content so that you can filter images based on your application requirements. Rekognition provides a hierarchical list of labels with confidence scores to enable fine-grained control over what images you want to allow.

Rekognition Image detects and recognizes thousands of individuals who are famous, noteworthy, or prominent in their field. This allows you to index and search digital image libraries for celebrities based on your marketing and media needs.

HAQM Rekognition Image can detect if persons in images are wearing PPE such as face covers, hand covers, and head covers and whether the protective equipment covers the corresponding body part (nose for face covers, head for head covers, and hands for hand covers). Learn more

HAQM Rekognition can be accessed using the HAQM Rekognition API, AWS Management Console, and the AWS command-line interface (CLI). The console, API, and CLI provide the ability to use the Rekognition APIs to detect labels, analyze faces, compare faces, and find a face. AWS Lambda has blueprints for Rekognition that make it easy to initiate image analysis based on events in your AWS data stores such as HAQM S3 and HAQM DynamoDB.

For a summary of the Rekognition API, please see the API Reference in the Rekognition documentation.

HAQM Rekognition is directly integrated with HAQM Augmented AI (HAQM A2I) so you can easily implement human review for unsafe image detection. HAQM A2I provides built-in human review workflow for image moderation, which allows predictions from HAQM Rekognition to be reviewed and validated easily. With HAQM A2I, you can use a pool of reviewers within your own organization, or you can access the workforce of over 500,000 independent contractors who are already performing machine learning tasks through HAQM Mechanical Turk. You can also make use of workforce vendors that are pre-screened by AWS for quality and adherence to security procedures. To learn more about implementing human review workflows, see the HAQM A2I website and HAQM A2I Integration with HAQM Rekognition in the HAQM A2I developer guide.