FaceServer software service can use Docker for localized private deployment, which can fully protect data security while providing strong identification capabilities.

Function introduction

Face Detection Detect whether there is a face in the image and return the maximum face position

Face Compare Compare the face information in two images, analyze facial features, and judge whether they are the same person

Face Search Search the face database and return the top N face images most similar to the input face

Liveness detection Determine whether the person in the picture or video is a real person

Solution advantage

FaceServer provides an easy-to-use API interface, manages multiple faces databases through HTTP requests, and has a high-precision face recognition model to ensure accurate recognition of faces even if they are covered by masks. FaceServer does not depend on the GPU and can only use the CPU for calculations, which greatly reduces the cost of deployment and operation.

Accurate recognition Accurately detect faces and provide strong support for multiple scenarios. The accuracy rate of face comparison on the LFW public test set is 99.9%+

Data security and privacy The software is deployed on the local server, and the data is stored and processed on the enterprise intranet without uploading to a third party. Guarantee the privacy and security of the enterprise’s core production data.

Response in milliseconds Support million-level face database management, can achieve millisecond-level response and recognition

simple and efficient The API provided by the service is simple and easy to use, which is convenient for customers to quickly integrate into their services.

Easy to deploy Based on Docker deployment, the deployment may be completed within 5 minutes

Application Scenario

identity verification

Member identification, login authentication, etc. The privatized deployment method can ensure the security of user information during verification and prevent the leakage of private data.