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codebloodedcb/mayavihin

开发工具

本页由 AI 翻译,技术细节请以原文为准。 查看原文

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深度伪造检测工具

概览

MAYAVIHIN 是一个基于网络的深度伪造检测和验证系统,利用多个 AI 分析代理分析上传的媒体文件(图片、视频、音频)以确定其真实性。 - 用户可以上传图片、视频或音频文件进行分析- 支持常见格式(JPG、PNG、MP4、MP3、WAV)- 文件大小限制和格式验证 - 上传和分析时的进度跟踪 该系统采用五个并行工作的专用分析代理: 1. - 分析图像和视频中的视觉处理伪影 2.- 检测音频深度伪造和声音克隆伪造 3.- 检查文件元数据和压缩签名 4.- 交叉验证其他代理的结果 5.

概述(AI 翻译)

概述

MAYAVIHIN 是一个基于网络的深度伪造检测和验证系统,利用多个 AI 分析代理分析上传的媒体文件(图片、视频、音频)以确定其真实性。

核心功能

媒体上传与分析

  • 用户可以上传图片、视频或音频文件进行分析
  • 支持常见格式(JPG、PNG、MP4、MP3、WAV)
  • 文件大小限制与格式验证
  • 上传和分析期间的进度跟踪

多代理检测系统

该系统采用五个并行工作的专用分析代理:

  1. 视觉取证人员 - 分析图像和视频中的视觉伪真
  2. 音频分析代理 - 检测音频深度伪造和声音克隆伪影
  3. 元数据代理 - 检查文件元数据和压缩签名
  4. 一致性代理 - 交叉验证其他代理的结果
  5. 可解释性代理 - 生成人类易读的检测结果解释

分析结果仪表盘

  • 整体真实性判决(真伪/不确定)
  • 信心评分(0-100%)

本页由 AI 翻译,技术细节请以原文为准。

README

以下为原文 README 节选,完整内容请查看原文。

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

在 GitHub 查看完整 README

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