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Home > AI for Retail > Visual Search (Online)

Visual Search

Visual search for retail enables online shoppers to search for products using images, parts of an image, or even pictures taken with their own cameras. Using images or pictures can be a more intuitive and accurate way for consumers to find what they want than text-based queries, especially when they don’t know the name of the product of brand

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1. Get Inspired

Understand the Use-case under 5 minutes

2. Know More

Get to know more Business and Technical details about the use-case (15-30 minutes)

Deeper Intro

More detailed introduction covering business and technical aspects

Business Focused

Case studies, Organizational Aspects, Return on Investment examples

Tech focused

More details on the technical aspects of the use-case

3. Do

Technical resources that will help you implement the use-case (notebooks, tutorials..)

Data Sets

Data Sets you can use to build Demos, POCs, or test Algorithms

Street2Shop Dataset

This dataset contains exact street2shop pairs and the retrieval sets for 11 clothing categories: bags, belts, dresses, eyewear, footwear, hats, leggings, outerwear, pants, skirts, tops

Fashion MNIST

a dataset of Zalando's article images—consisting of a training set of 60,000 examples and a test set of 10,000 examples. Each example is a 28x28 grayscale image, associated with a label from 10 classes


a comprehensive fashion dataset. It contains 491K diverse images of 13 popular clothing categories from both commercial shopping stores and consumers.


Off-the-Shelf Products using AI for Visual Search

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