CorTex Anomality Detector

minor changes...

What's Changed

• Resolve merge conflicts by synchronizing branch with main by @Copilot in #9
• Merge pull request #9 from GizzZmo/copilot/fix-6008b767-de9e-413e-8d5… by @GizzZmo in #10
• Merge pull request #10 from GizzZmo/main by @GizzZmo in #11
• Implement Phase 1 GitHub Integration for CORTEX 6.0 - OAuth Authentication and Repository Management by @Copilot in #13
• Document existing night vision on/off button functionality by @Copilot in #14
• Optimize and modernize CoreTex with comprehensive performance improvements and documentation by @Copilot in #16
• Implement Multi-YAML Configuration System with Cross-Platform Support by @Copilot in #18
• Add CI/CD Pipeline with Build Artifacts for React Application by @Copilot in #12
• Fix security vulnerabilities, improve accessibility, and enhance input validation by @Copilot in #20
• CI/CD Pipeline with Build Artifacts Already Implemented by @Copilot in #21

Full Changelog: 7.1.3...7.1.4

CoreTex® with NightVision®

...this will work on any webcam connected to any computer with a working web-browser.

CORTEX Anomaly Detector v5.9 – Usability & Documentation Upgrade

CORTEX Anomaly Detector v5.9 – Usability & Documentation
Release Notes:

Major improvement to user experience: Camera selector and night vision filter are now easier to find and use, with clearer feedback and dynamic UI.
Expanded README.md in English with detailed usability instructions for surveillance scenarios.
Help texts and Wiki updated (in Norwegian) to give step-by-step guides for all core functions, including face registration, camera switching, and AI features.
Improved accessibility: Buttons and fields enable/disable based on system status, and errors/feedback are shown in real time.
Enhanced error handling and logging for camera/system events.
Visual polish: cyberpunk UI, smooth animations, and improved feedback.
Application interface remains fully in Norwegian for optimal usability.
How to Use the New Features:

Select cameras from the drop-down in settings when multiple are connected.
Toggle night vision for better visibility in dark environments.
Use updated help and wiki tabs for quick guidance (på norsk).
See logs for system feedback and troubleshooting.

Made by Jon-Arve Constantine, Copilot and Geminiº

7.0.1

Link til Coretex Anomality Detector v7.0.1
[https://g.co/gemini/share/1a02d22277d9]

(https://g.co/gemini/share/1a02d22277d9?fbclid=IwZXh0bgNhZW0CMTAAYnJpZBEwc29ESEtYRENLOGVDaHZ3UAEeNBSZEvezAbtsKz-Ntya9NWW5Ih6NWaZHNPqNskkKGwxcgyHaDnVzV2uTLFo_aem_0MUnDTQ2ebBBo4cnXDKWZw)
EXECUTIVE ORDER // DIREKTIV 7A

PREAMBEL
Dette #direktivet etablerer de operative og etiske rammene for CORTEX-systemet. Systemets formål er å fungere som et avansert beslutningsstøtteverktøy for sikkerhetspersonell, med mål om å øke effektivitet, innsikt og proaktiv respons.
MANDAT 1: #PROAKTIV_SIKKERHET
CORTEX skal prioritere identifisering og analyse av potensielle trusler før de eskalerer. Ved hjelp av prediktive analyser (METATRON) og sanntidsvurderinger (RAFAEL, URIEL, SANDALPHON), skal systemet gi operatøren tidlig varsling om avvikende adferd, mønstre og miljøfarer.
MANDAT 2: #INFORMASJONSINTEGRITET
All data samlet og behandlet av CORTEX er en kritisk ressurs. Systemet skal sikre dataintegritet gjennom verifiserbare mekanismer (GABRIEL). All datahåndtering skal være sporbar og sikker.
MANDAT 3: #OPERATØR_MYNDIGGJØRING
AI-en er et verktøy for å forsterke menneskelig intuisjon og ekspertise, ikke erstatte den. Systemet skal levere klar, konsis og handlingsrettet informasjon som gir operatøren full kontroll og et solid grunnlag for å ta avgjørende beslutninger. Mennesket har alltid den endelige autoriteten.
#Gjenkjenningstoleranse
Dette er en verdi som bestemmer hvor strengt systemet er når det sammenligner ansikter. En lav verdi (f.eks. 0.4) krever et nesten perfekt treff. En høyere verdi (f.eks. 0.6) er mer tolerant for variasjoner som smil eller ulik belysning.
#Protokoll_GABRIEL
En AI-drevet beskytter av informasjonsintegritet. Protokollen verifiserer den lagrede ansiktsdatabasen for å sikre at den er ukorrupt og sikker. Den genererer en sjekksum som fungerer som et digitalt segl.
#Protokoll_RAFAEL
En AI-drevet beskytter av transport og bevegelse. Protokollen analyserer en sekvens av bilder for å vurdere flyt, tetthet og unormale bevegelsesmønstre i sanntid.
#Protokoll_URIEL
En AI-drevet beskytter av omgivelsene. Protokollen analyserer videostrømmen for avvik i miljøet, slik som gjenglemte gjenstander, åpne dører eller uvanlige objekter, og gir en risikovurdering.
#Protokoll_SANDALPHON
En AI-drevet protokoll for analyse av sosial dynamikk. Sandalphon observerer grupper av individer for å vurdere deres interaksjoner – om de er positive, negative, eller nøytrale – og identifiserer potensielt urovekkende gruppedynamikk.
#Protokoll_METATRON
Den mest avanserte protokollen. METATRON analyserer en bildesekvens for å forutsi et subjekts sannsynlige neste handling eller intensjon. Den gir en konkret prediksjon og en konfidensscore.

Cortex Anomality Detector

6.4.2

Update index.html

CORTEX Anomaly Detection 5.9.2

Here are the changes from version 5.8.0 to 5.9.2 in the CoreTex Anomaly Detection project:

---

Major Feature Change

• Rafael Protocol Upgrade:
  The "Rafael" protocol now analyzes a sequence of images (multi-frame) instead of just a single frame. This means movement and flow analysis is now based on a short video segment, enabling true movement analysis rather than just analyzing a static image.

---

Technical and UI Changes

• New Helper Function:
  Added captureFrameSequence to grab multiple frames from the video feed over 1.5 seconds.
• Protocol Interaction:
  When you click the "RAFAEL" button, the app now captures 3 frames, gives the user feedback during this process, and sends all frames to the Gemini API for a more powerful analysis.
• Prompt Updates:
  The AI prompt for the Rafael protocol now describes and requests analysis of a sequence, not a single image.
• Keywords Update:
  The meta keywords now include "sequence" to reflect the new functionality.
• UI Version String:
  Version display updated from 5.8 to 5.9.

---

Internal Code Improvements

• callGeminiAPI:
  Now accepts an array of images and sends multiple images for analysis, not just one.
• Behavior Analysis and Other AI Calls:
  Functions updated to use the new multi-image structure.
• New Functions:
  • callImagenAPI: To generate images using the Imagen model.
  • displayChatMessage and handleChatQuery: For improved chat assistant features.

---

Summary

The main change is the enhancement of the "Rafael" protocol to analyze sequences for better movement/flow analysis, making the feature more accurate and useful for real-world anomaly detection. There are also supporting changes to prompts, code structure, and the UI to reflect and enable this new capability.

If you want to see the code-level diff, let me know!

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.

Cortex Anomality Detection 5.8.0

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.