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DETECTING ARTIFICIAL LIFE
Deepfake analysis โข Synthetic media detection โข Manipulation forensics โข Reality verification
Baudrillard wrote about the "vital illusion"โthe way life itself becomes a simulation. In our age of AI-generated faces, voices, and videos, this illusion is literal. vital-illusion detects synthetic media and AI-generated content.
"The illusion of the world is not its unreality, but its resemblance to reality."
Detect AI-generated or manipulated faces:
from vital_illusion import FaceAnalyzer analyzer = FaceAnalyzer() # Analyze image result = analyzer.analyze("photo.jpg") print(f"Authenticity: {result.authenticity}%") print(f"Generation method: {result.method}") print(f"Confidence: {result.confidence}%") for artifact in result.artifacts: print(f"โธ {artifact.type} at {artifact.location}") print(f" Evidence: {artifact.description}")
Detect deepfake videos and face swaps:
from vital_illusion import VideoAnalyzer analyzer = VideoAnalyzer() # Real-time analysis async for frame_result in analyzer.stream("video.mp4"): if frame_result.manipulation_detected: print(f"Frame {frame_result.frame}: {frame_result.manipulation_type}") print(f"Confidence: {frame_result.confidence}%")
Detect AI-generated or cloned voices:
from vital_illusion import VoiceAnalyzer analyzer = VoiceAnalyzer() result = analyzer.analyze("audio.wav") print(f"Voice authenticity: {result.authenticity}%") print(f"Cloning detected: {result.cloned}") print(f"TTS markers: {result.tts_detected}")
Detect AI-generated text:
from vital_illusion import TextAnalyzer analyzer = TextAnalyzer() result = analyzer.analyze(text) print(f"AI probability: {result.ai_probability}%") print(f"Likely model: {result.likely_model}") print(f"Perplexity: {result.perplexity}")
โ VITAL-ILLUSION v2.0 โบ MEDIA ANALYSIS
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FILE: suspect_video.mp4
TYPE: Video (1920x1080, 30fps, 2:47)
ANALYSIS COMPLETE
โธ FACE DETECTION
Faces found: 2
Face A: SYNTHETIC
Method: StyleGAN2
Confidence: 94%
Artifacts: Eye reflection mismatch, hair boundary
Face B: AUTHENTIC
Confidence: 98%
No artifacts detected
โธ TEMPORAL ANALYSIS
Frame-to-frame consistency: 87%
Temporal artifacts detected at:
0:34 - 0:38 (blending artifacts)
1:12 - 1:14 (expression discontinuity)
2:01 (blink rate anomaly)
โธ AUDIO ANALYSIS
Voice detected: 1 speaker
TTS markers: DETECTED
Clone probability: 78%
Lip sync correlation: 0.67 (LOW)
โธ METADATA
Original creation: STRIPPED
Encoding: Multiple passes detected
Compression artifacts: Inconsistent
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VERDICT: SYNTHETIC MEDIA DETECTED
CONFIDENCE: 91%
AI-generated images contain subtle artifacts:
- Eye reflections that don't match
- Asymmetric facial features
- Background inconsistencies
- Unnatural hair/skin textures
Videos reveal manipulation through:
- Frame-to-frame inconsistencies
- Unnatural blinking patterns
- Expression timing anomalies
- Lip sync correlation
Audio deepfakes show:
- Frequency artifacts from synthesis
- Prosody anomalies
- Breathing pattern irregularities
- Room tone inconsistencies
AI-generated content has:
- Different compression artifacts
- Metadata anomalies
- Statistical signatures of generation
Full analysis suite with:
- Batch processing
- Detailed reports
- Timeline visualization
- Export capabilities
Quick verification on the go:
- Camera capture and analyze
- Import from gallery
- AR overlay showing artifacts
- Share verification results
Cloud-based analysis:
- REST API
- High-throughput processing
- Webhook notifications
- Usage analytics
Log verification results immutably:
from vital_illusion import Analyzer from cool_memories import ImmutableLog log = ImmutableLog() analyzer = Analyzer() result = analyzer.analyze(media) await log.record( event_type="media_verification", data=result.to_dict(), attachment=media, severity="high" if result.synthetic else "low" )
pip install baudrillard-vital-illusion # With GPU support pip install baudrillard-vital-illusion[gpu] # Mobile apps cd apps/vital-illusion-mobile npm install && npx expo build
"In a world of perfect simulation, authenticity becomes the greatest mystery."
BAUDRILLARD SUITE