Today, APIs have become an essential part of our daily lives. We use them to access information and perform operations on our devices. These tools are frequently used by developers to create new applications, making them even more popular. Image analysis is the process of gathering data from images using artificial intelligence (AI). This data can be used to gather data about images in a variety of ways. Some APIs focus on object recognition, while others may focus on image tagging or other tasks. Some APIs can be used for face-matching.
If you’re looking for an API that can help you with image analysis, we recommend using a Face Match Validator API. This kind of API is easy to use and will allow you to quickly and accurately identify faces in an image and compare them to images stored in a database. Given that these tools were created using cutting-edge artificial intelligence (AI), they will give you trustworthy results. There are a few available choices, however, we suggest looking into the Face Match Validator API developed by Zyla Labs. Keep reading to find out more about it!
Face Match Validator API
The face match validator API is easy to use and will allow you to quickly and accurately compare the faces of two images. You can also use it to see how two faces compare to each other! This is a great tool for businesses that need to compare faces for verification or authentication purposes. This tool is also ideal for law enforcement agencies that need to compare images for identification purposes. The response will include an API confidence score that helps you determine if the images belong to the same person or not.
How To Use The Face Match Validator API
Begin by creating an account on the Zyla API Hub and purchasing a subscription to the face match validator API. You can begin using this API as soon as you’re finished. This API uses a set of two endpoints to create the task and the response. Just replace the URLs of the two images you want to analyse in the request body form and run the API call. You will generate a request ID. Last but not least, choose the “retrieve task result” endpoint and input the request ID from the previous response. Run the API call and obtain your results in a few seconds!
By way of illustration, we contrast the following picture URLs: “https://images.hola.com/us/images/027c-16c591c79212-b332633b42dd-1000/horizontal-800/jennifer-lopez-in-her-monochromatic-holiday-look.jpg” and “https://cloudfront-us-east-1.images.arcpublishing.com/infobae/OHQ2I6WVVOHJCJ67UCZ446A2T4.jpg”. After the API request, we got:
{
"request_id": "589201d3-a43a-4cee-9770-9b9baf7639f1"
}
Finally, we insert the previous response in the “retrieve task result” endpoint and run an API call. The following data was obtained:
[
{
"action": "compare",
"completed_at": "2023-06-20T23:31:37+05:30",
"created_at": "2023-06-20T23:31:31+05:30",
"group_id": "123",
"request_id": "589201d3-a43a-4cee-9770-9b9baf7639f1",
"result": {
"image_1": {
"face_detected": true,
"face_quality": "Good"
},
"image_2": {
"face_detected": true,
"face_quality": "Good"
},
"is_a_match": true,
"match_score": 99.91,
"review_recommended": false
},
"status": "completed",
"task_id": "123",
"type": "face"
}
]
This response leads us to the conclusion that the two images correspond to the same person with a match score of 99.91%.
If you want an accurate face analysis for face matching, try the face match validator API. This is an excellent tool that ensures identification consistency with a confidence score in a matter of seconds! That’s how simple it is! So what are you waiting for? Get started with this amazing face match images API!
