CLASSIFIED OUTPUT:

INITIALIZING...

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The Architecture: The visual input is converted into a tensor (a multidimensional array of numerical values). A MobileNetV1 neural network scans this array to detect facial boundaries, while a secondary Depthwise Separable Convolutional Neural Network identifies 68 specific geometric landmarks (eyes, nose, jawline).

The Calculation: The system measures the topological distance between these landmarks. It compares these geometric arrangements against a pre-trained dataset of labeled images to generate a statistical probability score. This is a mathematical correlation of surface data, not a psychological reading.

Confidence Score: 0.0% | Library: face-api.js (TensorFlow.js)