github.com/rivo/duplo
Package duplo provides tools to efficiently query large sets of images for visual duplicates. The technique is based on the paper "Fast Multiresolution Image Querying" by Charles E. Jacobs, Adam Finkelstein, and David H. Salesin, with a few modifications and additions, such as the addition of a width to height ratio, the dHash metric by Dr. Neal Krawetz as well as some histogram-based metrics. Quering the data structure will return a list of potential matches, sorted by the score described in the main paper. The user can make searching for duplicates stricter, however, by filtering based on the additional metrics. Package example.
Readme
This Go library allows you to perform a visual query on a set of images, returning the results in the order of similarity. This allows you to effectively detect duplicates with minor modifications (e.g. some colour correction or watermarks).
It is an implementation of Fast Multiresolution Image Querying by Jacobs et al. which uses truncated Haar wavelet transforms to create visual hashes of the images. The same method has previously been used in the imgSeek software and the retrievr website.
go get github.com/rivo/duplo
import "github.com/rivo/duplo"
// Create an empty store.
store := duplo.New()
// Add image "img" to the store.
hash, _ := duplo.CreateHash(img)
store.Add("myimage", hash)
// Query the store based on image "query".
hash, _ = duplo.CreateHash(query)
matches := store.Query(hash)
sort.Sort(matches)
// matches[0] is the best match.
http://godoc.org/github.com/rivo/duplo
For more information, please go to http://rentafounder.com/find-similar-images-with-duplo/ or get in touch.
FAQs
Package duplo provides tools to efficiently query large sets of images for visual duplicates. The technique is based on the paper "Fast Multiresolution Image Querying" by Charles E. Jacobs, Adam Finkelstein, and David H. Salesin, with a few modifications and additions, such as the addition of a width to height ratio, the dHash metric by Dr. Neal Krawetz as well as some histogram-based metrics. Quering the data structure will return a list of potential matches, sorted by the score described in the main paper. The user can make searching for duplicates stricter, however, by filtering based on the additional metrics. Package example.
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