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Face Blur API

kiadó: SC DE VIS SOFTWARE SRL

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Detects and localizes human faces on a still photo and blurs the faces.

Face blur API - FaceBlurest (also known as Face Anonymizer API or Face Estomper API) is a cross browsers REST API which get a JSON input with a still photo (as base64 encoded string), containing people with clear faces and returns a JSON string which contains a base64 encoded string photo with blured face(s), confidence score, timestamp, vertices for bounding boxes of Faces. Of course, there are some limitations in order to get a higher accuracy. We recommend properly exposed, unobstructed JPEG photos at 1920x1080 (full HD resolution) where ratio between height of the Face and height of entire picture should be at least 1:15. For ratios like 1:16, 1:17, 1:18 and so on the accuracy is lower and the AI algorithm may not see the Face. The faces must be focalized, unobstructed, with details very clear. We do not store pictures. Also, the quality and the angles of the camera are very important and it contribute to a higher reading accuracy. It should have varifocal lenses, high shutter speed, good infrared lighting beam, full HD resolution.

Allthough this Automatic Face blur API (currently we do not offer a Face blur sdk) is intended for software development and therefore developers, we have also here an Face blur online application that may be used to check the input and output JSONs of the API. The necessary steps are written below, basically for this real time Face blur API you send an authorized POST request in JSON format to the API endpoint and you get as JSON response the output as described below through parameters and examples.

This Face Blur API is useful for a large number of domains like: people anonymizers apps, virtual tours, Google Street View panos etc. You own the commercial copyright of the resulted JSON with no additional fee meaning you may use it in your own apps for sale.

Áttekintés

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https://store-images.s-microsoft.com/image/apps.11354.e472bcbd-5834-47e7-be33-6fd537bb8641.8c3fd02f-05a3-4169-8970-3dc0be1c69ff.0dca0cb1-3cd5-4283-af81-0c15b7112539