Image Similarity with SQL Server

> **Note:** You can read more about this solution and deployment guides in the [Image Similarity solution](https://microsoft.github.io/ml-server-image-similarity/) published on GitHub. > **Required preliminary agreement:** You need to accept the Terms of Use for the Data Science Virtual Machine on your Azure Subscription before you deploy this VM the first time. Click [here](https://portal.azure.com/#blade/Microsoft_Azure_Marketplace/LegalTermsSkuProgrammaticAccessBlade/legalTermsSkuProgrammaticAccessData/%7B%22product%22%3A%7B%22publisherId%22%3A%22microsoft-ads%22%2C%22offerId%22%3A%22standard-data-science-vm%22%2C%22planId%22%3A%22standard-data-science-vm%22%7D%7D) to agree to these terms. ## Overview This template describes how to build and deploy an image similarity solution with [SQL Server Machine Learning Services with Python](https://docs.microsoft.com/en-us/sql/advanced-analytics/python/sql-server-python-services). In this solution, we demonstrate how to apply transfer learning, e.g., using pretrained deep neural network (DNN) model (trained on ImageNet) in solving the image similarity problem for an image based similar product recommendation scenario. The solution uses a small sample of upper body clothing images (around 300 images) as an example: there are 3 different types of textures in the clothing images: dotted, striped, and leopard. Those with similar texture are considered more similar than those with different textures. These data are scraped from the internet using Bing Image Search API and manually annotated. The URLs of these images are provided as a reference. The users of this solution are welcome to use their own dataset. The end to end machine learning workflow for building such as solution is provided: data preprocessing, featurization, training, testing, evaluation, and ranking. All these major steps are provided in SQL Server Stored procedures with python script embedded inside, which makes it convenient to deploy such as solution with SQL Server ML Services. Read more about this solution, including step-by-step instructions on how to deploy it, at the [Image Similarity Website](https://microsoft.github.io/ml-server-image-similarity/). ## Pricing Your Azure subscription used for the deployment will incur consumption charges on the services used in this solution, approximately $2.06(USD)/hour for the default VM in the East US. ### Disclaimer * All prices shown are in US Dollar ($). This is a summary estimate, not a quote. For up to date pricing information please visit [https://azure.microsoft.com/pricing/calculator/](https://azure.microsoft.com/pricing/calculator/). >Please ensure that you stop your VM instance when not actively using the solution. Running the VM will incur higher costs. > >**Please delete the solution if you are not using it.** ## Disclaimer ©2017 Microsoft Corporation. All rights reserved. This information is provided "as-is" and may change without notice. Microsoft makes no warranties, express or implied, with respect to the information provided here. Third party data was used to generate the Solution. You are responsible for respecting the rights of others, including procuring and complying with relevant licenses in order to create similar datasets.