Components

Image API consists of services available via REST API.

Service name	Functions
gateway	The service is responsible for getting access to Image API and interacting with the processing services listed below.
body-detector	The service is designed to detect bodies in an image. The detection result is the coordinates of the bounding box (bbox) around the detected body.
face-detector-face-fitter	The service is used to determine face landmarks and the head rotation angles. The returned result is a set of 21 anthropometric points and the values of head rotation angles (yaw, pitch, roll).
emotion-estimator	The service estimates emotions from a face image. The result is the degree of manifestation of each estimated emotion.
age-estimator	The service estimates a person’s age from a face image. The estimation result is the numerical value of the person's age.
gender-estimator	The service is used to determine a person’s gender from a face image.
face-detector-liveness-estimator	The service is used to detect if a person in an image is real or fake. The result is a Real/Fake verdict with a numerical value of confidence.
mask-estimator	The service detects if a person in an image is wearing a medical mask. The result is a True/False verdict with a numerical value of confidence.
quality-assessment-estimator	The service is designed to estimate the quality of a face image. The result is a list of detected faces with a detailed image quality analysis.
verify-matcher	The service compares two face images to determine if they belong to the same person.
face-detector-template-extractor	The service is designed to extract a biometric template from a face image.
template-extractor	The service is designed for building biometric templates. The result is a biometric template for all detected persons.
liveness-estimator	The service is designed to calculate Liveness. The result is a Liveness verdict for one detected face.
deepfake-estimator	The service is designed to estimate whether a face image is generated using deepfake technology. The result is the model's confidence that the face is AI-generated.
glasses-estimator	The service is designed to estimate the presence of glasses on a facial image. The result is a verdict and a confidence score for the presence of glasses on the facial image.
quality-core	The service is designed to evaluate the most critical quality parameters (face size, frontal alignment, image noise, etc.) for both recognition and Liveness estimation. The output is a pass/fail verdict along with a list of checks that were not passed.
quality-estimation	The service is designed to estimate a numerical score indicating how suitable a facial image is for recognition. While this score effectively filters out low-quality images, it is hard to interpret because it does not return direct feedback on what exactly is wrong with the image and how to improve it. This service is suitable for scenarios where providing end users with guidance on improving their photos is not necessary.