Reverse Image Search using Deep Learning (CNN)

In this post, you will learn about a solution approach for searching similar images out of numerous images matching an input image (query) using machine learning / deep learning technology. This is also called a reverse image search. The image search is generally searching for images based on keywords.

Here are the key components of the solution for reverse image search:
  • A database of storing images with associated numerical vector also called embeddings.
  • A deep learning model based on convolutional neural network (CNN) for creating numerical feature vectors (aka embeddings) for images

How it works

Hosted API

The CSS API is a fully hosted API. There is no software to install and no updates to worry about. By using our hosted API, you save time and money needed to build and maintain your own image recognition solutions.

Easy to integrate

The CSS API is easily integrated with your existing technology, regardless of the languages and tools you use.

Fully documented

The CSS API is a REST-based API, delivered over HTTP or HTTPS in JSON format. REST/JSON bindings are available in all major programming languages. We also support a growing number of language-specific libraries to make integration very straight forward. Our documentation and libraries are extensive.

Scalable and high performance

Multiple image query support including JPEG, PNG, or GIF. Query images can be specified by a publicly accessible image URL, or uploaded.

Large and growing image index

The CSS API searches the CSS index which is an index of a large cross section of the web. The CSS index is at 41,274,531,291 images today.