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I'm trying to build a utility like this http://labs.ideeinc.com/multicolr, but I don't know which algorithm they are using, Does anyone know?
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How could we compute how similar one image is to another? For similarity among data in a vectorized form, we can find the sum of the squared differences between two examples, or use similar methods like cosine similarity.
Learning Fine-grained Image Similarity with Deep Ranking is a novel application of neural networks, where the authors use a new multi scale architecture combined with a triplet loss to create a neural network that is able to perform image search.
What are image embeddings? An image embedding is a lower-dimensional representation of the image. In other words, it is a dense vector representation of the image which can be used for many tasks such as classification. A convolutional neural network (CNN) can be used to create the image embedding.
I'd suggest you do some kind of clustering of the colors present in the images in your database. I mean, for each image in your database:
When the user provides a set of one or more query colors you do some kind of greedy matching choosing the best match between the given colors and the color descriptor (the 5 reprsentative colors) of each image in your database.
What is the size of your image collection, because depending on the size some search indexing can be a bigger problem than the alogorith itself?
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