face-detection6

face-detection6 MCP Server

Overview

The face-detection6 MCP server offers robust capabilities for detecting human faces in images. It is designed to integrate seamlessly with your applications, providing advanced computer vision functionalities that can identify and analyze faces with high accuracy.

Features

Face Detection

The core functionality of the face-detection6 server is to locate human faces within an image. This tool provides the position of faces using bounding boxes, which are defined by the top-left and bottom-right pixel coordinates of each face detected. Additionally, each detected face is accompanied by a probability score, indicating the confidence level of the detection.

Face Detection with Age & Gender

In addition to basic face detection, the server can also predict the age range and binary gender of each detected face. This tool uses advanced machine learning models to provide insights into the demographic characteristics of the individuals in the image.

Functionality

The face-detection6 server includes the following tools:

• Face Detection: Detects the locations of human faces within an image. It outputs the bounding box coordinates and the probability score for each detected face.

• Face Detection with Age & Gender: Extends the basic face detection capabilities by providing additional demographic information, including age range and gender predictions for each detected face.

Usage

To utilize the face-detection6 MCP server, provide an image URL, and the server will process the image to return the desired information. The server is designed to offer a balance between speed and accuracy, with an optional parameter to adjust the accuracy level of the detection model. This allows users to tailor the performance according to their specific needs.

Accuracy Configuration

• Accuracy Boost: This parameter allows you to adjust the trade-off between speed and accuracy. The valid values range from 1 to 4, where:
  • 1 is the fastest and least accurate model.
  • 4 is the slowest and most accurate model.
  • A recommended setting for most use cases is 2, balancing efficiency and precision.

Conclusion

The face-detection6 MCP server is an affordable and efficient solution for integrating face detection and demographic analysis into your applications. With its state-of-the-art models and scalable infrastructure, it provides reliable and accurate results, making it an ideal choice for developers looking to add machine learning capabilities to their projects.