2D Face SDK

1. Strong system adaptability

Deeply adapts to Windows system features, supports x86/x64 architecture, is compatible with Windows graphical interfaces, and 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 facial detection takes ≤ 10ms, and 1:1 comparison takes ≤ 5ms, meeting the requirements for real-time interaction;

Robustness: Suitable for common scenarios on the Windows platform, (such as backlit computer cameras, wearing masks/glasses, and slight head rotation, with tolerance for variations in posture/lighting/occlusion;

Lightweight: It does not require complex GPU clusters, and can run smoothly on regular Windows PCs (Intel Core i5 and above).

3. Usability and Scalability

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

Supports local offline operation without relying on the cloud, ensuring data privacy (meeting localized deployment requirements);

Customizable parameters (such as detection thresholds and recognition thresholds) to meet 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 compliant with the Personal Information Protection Law and provide interfaces for facial data encryption and anonymization.

1. Authentication-related issues

Replacing traditional passwords/card swiping: Facial login can be integrated into Windows software (such as office OA, financial systems, industrial control software) to solve problems including password leakage, proxy clocking-in, and card loss;

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

2. Issues related to human-computer interaction

Intelligent attendance: Windows industrial computers/desktop computers with camera, realizing enterprise/campus facial attendance, resolving low efficiency and cheating issues in manual attendance;

Intelligent access control: Windows embedded devices (such as access control hosts) integrate facial recognition to resolve the issues 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 facial detection to achieve beauty enhancement, 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 systems) uses the SDK to achieve batch facial detection, annotation, and retrieval, resolving the problem of low manual processing efficiency;

Data Security: Windows local deployment of SDK, facial data does not pass through the cloud, resolving 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 via the SDK, reducing the threshold and cycle of facial function development for Windows applications (from months to days).