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CORTEX ANOMALITY DETECTOR empowers organizations to proactively identify threats and anomalies in real time, ensuring trust and safety at the highest standard. The project focused on identifying irregularities within datasets or systems. Built primarily with HTML.

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The index.html file is a comprehensive HTML document for the "CORTEX Anomaly Detection" application. Here's an explanation of its structure and functionality:

General Overview:

  • Purpose: This file is the main interface for a cyberpunk-inspired anomaly detection application. It utilizes AI and facial recognition technologies.
  • Key Features:
    • Real-time video feed with face and anomaly detection.
    • User interaction through buttons and settings.
    • Integration with AI models and Google API for advanced functionality.

File Details:

1. Metadata and Styling:

  • HTML Metadata:
    • Language: Norwegian (lang="no").
    • Title: "CORTEX Anomaly Detector | Cyberpunk Ansiktsgjenkjenning".
    • Description and Keywords: Highlight features like facial recognition, real-time AI, and biometrics.
  • Styling:
    • Uses Tailwind CSS and a custom font (Share Tech Mono).
    • Custom CSS defines a "cyberpunk" theme with neon colors, shadows, and animations.
    • Includes classes like .cyber-button and .cyber-border for futuristic UI elements.

2. Layout:

  • Main Container:
    • A responsive, flexbox-based layout with a "cyber-border" effect.
  • Video Section:
    • Displays real-time video feed (<video> tag).
    • An overlay (<canvas>) is used for drawing detections.
  • Control Panel:
    • Buttons for face registration, database export/import, behavior analysis, and anomaly reporting.
    • File input for importing a database in .json format.
  • Sidebar:
    • Sections for:
      • API key input.
      • Settings (e.g., recognition tolerance slider).
      • Known individuals list.
      • System log.
      • Chat assistant for user interaction.

3. Modals:

  • Multiple modals provide additional functionality:
    • Register New Individual: Input a name for a new face.
    • Analysis Report: Displays anomaly analysis.
    • Behavior Analysis: Submits behavior data for advanced AI analysis.
    • Generate Phantom Image: AI generates an image based on a textual description.

4. Scripts and Functionality:

  • Libraries Used:
    • face-api.js: AI-based face detection and recognition.
    • Built-in Gemini API for advanced generative AI tasks.
  • Functional Highlights:
    • initialize(): Loads AI models and starts the webcam.
    • detectFacesLoop(): Continuously detects faces in the video feed and highlights anomalies.
    • Event Handlers:
      • API key saving and toggling advanced features.
      • Behavior analysis and anomaly explanation using AI.
      • Exporting and importing face data.
      • Running "Gabriel" and "Rafael" protocols for database integrity and movement analysis.
  • State Management:
    • Keeps track of known and unknown faces.
    • Logs system activities and errors for the user.

5. Loading Screen:

  • Initial "AI-core initialization" screen with a spinner and status messages.

6. Accessibility:

  • Buttons and inputs are disabled/enabled based on conditions (e.g., API key availability).

Notable Visual and Functional Enhancements:

  • Cyberpunk aesthetics with a neon palette.
  • Smooth animations and hover effects on buttons.
  • Detailed error handling and user feedback through logs.

Summary:

This file serves as the front-end for a complex anomaly detection and facial recognition system, combining AI APIs with a visually engaging user interface. It’s designed for real-time interaction, with modular features like behavior analysis, data handling, and API integration.

About

CORTEX ANOMALITY DETECTOR empowers organizations to proactively identify threats and anomalies in real time, ensuring trust and safety at the highest standard. The project focused on identifying irregularities within datasets or systems. Built primarily with HTML.

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