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I Built a Real-Time Deepfake Detector in Python — 9 Signal Layers, Full Architecture, Free to Use"

DEV Community·Abhishek Kumar·about 1 month ago
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description: "A complete technical breakdown of how Vigil AI detects AI-generated voices and deepfake video calls using MFCC analysis, pitch jitter, MediaPipe landmarks, Fourier transforms, and optical flow — with all the code decisions explained." tags: python, machinelearning, ai, security canonical_url: https://vigilai.online I Built a Real-Time Deepfake Detector in Python — 9 Signal Layers, Full Architecture, Free to Use Deepfake fraud crossed $860 million in losses in 2024. Every major solution on the market costs thousands of dollars per month. So I built one that's free — and open about exactly how it works. This is a complete technical breakdown of Vigil AI — the architecture, the signal selection decisions, the code, the tradeoffs, and everything I learned building a real-time audio and video deepfake detector as a solo developer. Live demo: www.vigilai.online Why These 9 Signals? The Decision-Making Process Most deepfake detectors are black boxes.…

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