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Image similarity search, also called content-based image retrieval and Reverse Image Search is a computer vision technique that involves finding and retrieving images from a database that are visually similar to a given query image.
It depends on extracting and matching characteristics, like hue, consistency, form, or deep neural network embeddings, to gauge the similarity between images.
This AI-powered technology finds widespread applications, such as content-based image retrieval, e-commerce, recommendation systems, and image organization. It allows users to swiftly and efficiently discover visually akin images, without relying solely on textual metadata or tags.
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You can use Image Similarity Search in numerous fields, here are some examples of common use cases:
While comparing Image Similarity Search APIs, it is crucial to consider different aspects, among others, cost security and privacy. Image Similarity Search experts at Eden AI tested, compared, and used many Image Similarity Search APIs of the market. Here are some actors that perform well (in alphabetical order):
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Clarifai's unique Smart Image Search API uses deep learning techniques to sort, rank and retrieve images based on their content and visual similarity. This surpasses conventional image search methods that rely exclusively on image metadata or textual descriptions.
Nyckel's efficient and secure API allows you t search your image library using images or free-form text queries. No training is necessary; you can simply upload your images and start searching.
Sentisight has developed the REST API to find visually similar images to an uploaded image. The images retrieved are categorized by their similarity score, enabling users to efficiently organize vast datasets and identify duplicates or similar images.
Utilizing this API provides a high degree of adaptability and scalability, all without the requirement for costly hardware like GPUs, and without any additional training necessary.
Ximilar's Visual Search API has the capability to process a range of images, including general photos and product/fashion photos. Once uploaded, it can promptly identify images that bear similarity to a specific query image.
Image Similarity Search API performance can vary depending on several variables, including the technology used by the provider, the underlying algorithms, the amount of the dataset, the server architecture, and network latency. Listed below are a few typical performance discrepancies between several Image Similarity Search APIs:
Companies and developers from a wide range of industries (Social Media, Retail, Health, Finances, Law, etc.) use Eden AI’s unique API to easily integrate Image Similarity Search tasks in their cloud-based applications, without having to build their solutions.
Eden AI offers multiple AI APIs on its platform among several technologies: Text-to-Speech, Language Detection, Sentiment Analysis, Face Recognition, Question Answering, Data Anonymization, Speech Recognition, and so forth.
We want our users to have access to multiple Image Similarity Search engines and manage them in one place so they can reach high performance, optimize cost, and cover all their needs. There are many reasons for using multiple APIs :
Eden AI is the future of AI usage in companies: our app allows you to call multiple AI APIs.
The Eden AI team can help you with your Image Similarity Search integration project. This can be done by:
You can directly start building now. If you have any questions, feel free to chat with us!
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