Image Match Detection API API ID: 7417

Image Match Detection API analyzes and compares two images using advanced algorithms to identify visual matches, duplicates, or similarities with high accuracy.
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About the API:

The Image Match Detection API is a robust and user-friendly solution for assessing how similar two images are. Using advanced machine learning and computer vision techniques, it thoroughly analyzes visual elements to deliver a precise similarity score.

This score reflects the degree of likeness between images, where higher scores signify stronger similarity and lower scores indicate less. Built for seamless integration, the API offers fast and dependable results, ideal for applications like duplicate detection, content verification, image search, and quality assurance.

API Documentation

Endpoints


To use this endpoint you must indicate the URL of 2 images in the parameters.



                                                                            
GET https://pr197-testing.zylalabs.com/api/7417/image+match+detection+api/11827/get+similarity
                                                                            
                                                                        

Get Similarity - Endpoint Features

Object Description
url1 [Required] Indicates 1º Image
url2 [Required] Indicates 2º Image

Free test requests remaining: 3 of 3.


INPUT PARAMETERS

hide_analysis
access_key
url1
url2

API EXAMPLE RESPONSE

{"output":{"success":true,"is_same":true,"confidence_score":0.8505765699827665,"url1":"https://5.imimg.com/data5/SELLER/Default/2021/2/ZZ/BN/ME/123104813/football-1000x1000.jpg","url2":"https://img.freepik.com/premium-photo/ball-corner-line-soccer-field_647082-167.jpg?w=740"}}

Get Similarity - CODE SNIPPETS


curl --location --request GET 'https://zylalabs.com/api/7417/image+match+detection+api/11827/get+similarity?url1=https://5.imimg.com/data5/SELLER/Default/2021/2/ZZ/BN/ME/123104813/football-1000x1000.jpg&url2=https://img.freepik.com/premium-photo/ball-corner-line-soccer-field_647082-167.jpg?w=740' --header 'Authorization: Bearer YOUR_API_KEY' 


    

API Access Key & Authentication

After signing up, every developer is assigned a personal API access key, a unique combination of letters and digits provided to access to our API endpoint. To authenticate with the Image Match Detection API simply include your bearer token in the Authorization header.
Headers
Header Description
Authorization [Required] Should be Bearer access_key. See "Your API Access Key" above when you are subscribed.

Simple Transparent Pricing

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Image Match Detection API FAQs

The POST Similarity Calculator endpoint returns a similarity score between two images, while the GET Get Similarity endpoint provides a success status, a boolean indicating if the images are the same, a confidence score, and the URLs of the compared images.

Key fields include "similarity" in the POST response, and "success," "is_same," "confidence_score," "url1," and "url2" in the GET response, which provide insights into the comparison results.

The POST endpoint requires two parameters: "type" (set to "URL") and "content" (the image URL to compare). The GET endpoint requires two image URLs as parameters for comparison.

The POST response is a simple JSON object with a "similarity" key. The GET response is a nested JSON object containing an "output" key, which holds the success status and comparison details.

Common use cases include image recognition, detecting duplicate images, integrating similarity scores into applications, and enhancing image search and recommendation systems.

Users can leverage the similarity score to assess how closely images match, use the confidence score to gauge reliability, and implement alerts or recommendations based on the comparison results.

The API employs machine learning algorithms to analyze images, ensuring that the similarity scores are based on robust visual content analysis, although specific quality checks are not detailed.

Users can expect similarity scores ranging from 0.0 (no similarity) to 1.0 (identical images) and confidence scores typically between 0.0 and 1.0, indicating the reliability of the similarity assessment.

General FAQs

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