Simple, Fast, and Scalable Reverse Image Search Using Perceptual Hashes and DynamoDB. Christopher Bong provides a clear explanation of how perceptual hashes can be used to create a string representing the visual content of an image, such that similar images can be identified by calculating a hamming distance between those hashes. He then explains how they built a large-scale system for this at Canva on top of DynamoDB, by splitting those strings into smaller hash windows and using those for efficient bulk lookups of similar candidates.
- Weeknotes: datasette-enrichments, datasette-comments, sqlite-chronicle - 8th December 2023
- Datasette Enrichments: a new plugin framework for augmenting your data - 1st December 2023
- llamafile is the new best way to run a LLM on your own computer - 29th November 2023
- Prompt injection explained, November 2023 edition - 27th November 2023
- I'm on the Newsroom Robots podcast, with thoughts on the OpenAI board - 25th November 2023
- Weeknotes: DevDay, GitHub Universe, OpenAI chaos - 22nd November 2023