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codebloodedcb/mayavihin

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2 stars 품질 32 트렌드 4

DEEPFAKE DETECTION TOOL

개요

MAYAVIHIN is a web-based deepfake detection and verification system that analyzes uploaded media files (images, videos, audio) to determine their authenticity using multiple AI analysis agents. - Users can upload image, video, or audio files for analysis - Support for common formats (JPG, PNG, MP4, MP3, WAV) - File size limits and format validation - Progress tracking during upload and analysis The system employs five specialized analysis agents that work in parallel: 1. - Analyzes images and videos for visual manipulation artifacts 2. - Detects audio deepfakes and voice cloning artifacts 3. - Examines file metadata and compression signatures 4. - Cross-validates results from other agents 5.

README

원문 README의 일부입니다. 원문 보기.

MAYAVIHIN Deepfake Detection System Version 19

Overview

MAYAVIHIN is a web-based deepfake detection and verification system that analyzes uploaded media files (images, videos, audio) to determine their authenticity using multiple AI analysis agents.

Core Features

Media Upload and Analysis

  • Users can upload image, video, or audio files for analysis
  • Support for common formats (JPG, PNG, MP4, MP3, WAV)
  • File size limits and format validation
  • Progress tracking during upload and analysis

Multi-Agent Detection System

The system employs five specialized analysis agents that work in parallel:

  1. Visual Forensics Agent - Analyzes images and videos for visual manipulation artifacts
  2. Audio Analysis Agent - Detects audio deepfakes and voice cloning artifacts
  3. Metadata Agent - Examines file metadata and compression signatures
  4. Consistency Agent - Cross-validates results from other agents
  5. Explainability Agent - Generates human-readable explanations for detection results

Analysis Results Dashboard

  • Overall authenticity verdict (Authentic/Fake/Uncertain)
  • Confidence score (0-100%)
  • Detailed per-agent results display: Each of the five agents shows individual verdicts (“Real”, “Fake”, “Uncertain”) with corresponding confidence percentages
  • Rich explainable AI layout: Visual Forensics, Audio Analysis, Metadata, Consistency, and Explainability agents each display detailed sub-results with human-readable reasoning text and percentage confidence bars
  • Multi-agent verdict visualization: Clear display of each agent’s analysis outcome with explanatory text and visual confidence indicators
  • Visual indicators highlighting suspicious areas (for images/videos)
  • Timeline view for video analysis results

Analysis History

  • Users can view their previous analysis requests
  • Search and filter past analyses by date, file type, or result
  • Export analysis reports

System Logs

  • Comprehensive activity logging displaying application events
  • Log entries for media uploads, analysis actions, deletions, and system errors
  • Scrollable card-based or table layout with columns for timestamp, action type, file name/ID, status, and message details
  • Filter and search functionality for quickly locating specific log entries
  • Real-time log updates and chronological ordering

Backend Data Storage

  • Analysis Records: Store analysis results, confidence scores, agent outputs, and explanations with detailed per-agent verdict data including individual agent confidence scores, reasoning text, and sub-analysis results
  • File Metadata: Store original filename, file type, size, upload timestamp
  • User Sessions: Track user uploads and analysis history (no authentication required)
  • System Logs: Store comprehensive activity logs including timestamps, action types, file references, status codes, and detailed messages

Backend Operations

GitHub에서 전체 README 보기

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