Dev Tools · 2h ago
Building a Perceptual Hash Pipeline for Video Deduplication
A European viral-video discovery product uses perceptual hashing to collapse near-duplicate clips before ranking. The pipeline samples frames, computes DCT-based 64-bit hashes, and queries millions via SQLite and a Go helper. This approach avoids GPU or vector databases while surviving re-encoding, cropping, and watermarking.
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The post offers a practical, production-tested method for video deduplication without proprietary services, though its reliance on SQLite may limit scale for larger platforms.
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Building a Perceptual Hash Pipeline for Video Deduplication in Python →
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