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Face Recognition
Demo Faceapi

Demo Faceapi

Block out underage faces in real-time video

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What is Demo Faceapi ?

Demo Faceapi is a cutting-edge face recognition tool designed to block underage faces in real-time video streams. It leverages advanced AI technology to detect and obscure faces of individuals who appear to be underage, helping to protect their privacy and ensure compliance with age-related regulations. This tool is particularly useful for platforms that need to manage age-appropriate content effectively.

Features

• Real-time face detection and processing for immediate blocking of underage faces
• Highly accurate age estimation using state-of-the-art AI models
• Automatic blurring or obscuring of detected underage faces
• Customizable thresholds for age detection to suit different use cases
• Seamless integration with video platforms and applications
• Efficient performance with minimal impact on video streaming quality

How to use Demo Faceapi ?

  1. Install the Demo Faceapi library using the provided installation instructions.
  2. Set up your video capture device (e.g., webcam or video file input).
  3. Integrate Demo Faceapi into your application using the API or SDK.
  4. Capture video frames and pass them to the Demo Faceapi for processing.
  5. Detect and block underage faces in real-time using the tool's built-in functionality.
  6. Output the processed video with obscured underage faces.

Frequently Asked Questions

1. What platforms is Demo Faceapi compatible with?
Demo Faceapi is designed to work with most major video platforms and frameworks, including web-based applications and mobile devices. Contact support for specific compatibility details.

2. How accurate is the age estimation feature?
The age estimation feature is highly accurate, with precision optimized for real-time video processing. However, accuracy may vary depending on lighting conditions and video quality.

3. Can I customize the way underage faces are blocked?
Yes, Demo Faceapi allows users to customize the blocking method (e.g., blurring, pixelation, or masking) and set custom thresholds for age detection to meet specific requirements.

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