2D Face SDK

1. Strong system adaptability

Deeply adapted to Windows system features, supports x86/x64 architecture, compatible with Windows graphical interfaces, can directly call local cameras and read local image/video files;

2. Outstanding core algorithm capabilities

High precision: In regular scenarios (with normal lighting and proper posture), the face detection rate is ≥ 99%, the 1: N recognition accuracy is ≥ 98% (in a million level face database), and the misidentification rate can be controlled within 0.001%;

Real time performance: When deployed locally on Windows, single frame face detection takes ≤ 10ms, 1:1 comparison takes ≤ 5ms, meeting real-time interaction requirements;

Robustness: Suitable for common scenarios on the Windows platform, such as backlit computer cameras, wearing masks/glasses, and slight facial features, with a certain tolerance for posture/lighting/occlusion;

Lightweight: No need to rely on complex GPU clusters, regular Windows PCs (Core i5 and above) can run smoothly.

  3. Usability and Scalability

Provide standardized API interfaces, support synchronous/asynchronous calls, and adapt to Windows multi-threaded development mode;

Support local offline operation without relying on the cloud, ensuring data privacy (in line with the requirements of localized deployment on Windows);

Customizable parameters (such as detection threshold, recognition threshold) to adapt to the accuracy/speed requirements of different business scenarios.

4. Compliance

Compliant with Windows system security standards, supports digital signatures, and avoids interception by system firewalls/antivirus software;

Partial SDKs are adapted to the Personal Information Protection Law and provide interfaces for facial data encryption and anonymization.

1. Authentication related issues

Replacing traditional passwords/card swiping: Windows software (such as office OA, financial systems, industrial control software) integrates facial login to solve problems such as password leakage, proxy clocking, and card loss;

Remote identity verification: The Windows client collects facial information and compares it with the backend database to solve identity authentication problems in remote work, online account opening, and other scenarios.

2. Issues related to human-computer interaction

Intelligent attendance: Windows industrial computer/desktop computer with camera, realizing enterprise/campus facial attendance, solving the problems of low efficiency and cheating in manual attendance;

Intelligent access control: Windows embedded devices (such as access control hosts) integrate facial recognition to solve the problems of cumbersome traditional access control permission management and stranger intrusion;

Personalized interaction: Windows based entertainment/educational software (such as children's learning machines and live streaming software) uses face detection to achieve beauty, facial expression interaction, and attention monitoring.

3. Efficiency and safety related issues

Batch face processing: Windows based tool software (such as security monitoring playback, portrait management system) uses SDK to achieve batch face detection, annotation, and retrieval, solving the problem of low manual processing efficiency;

Data Security: Windows local deployment SDK, facial data does not go through the cloud, solving the risk of data leakage during cloud transmission;

Low cost development: No need to independently develop 2D facial algorithms (algorithm development cost exceeds one million), quickly integrated through SDK, reducing the threshold and cycle of facial function development for Windows applications (from months to days).