https://store-images.s-microsoft.com/image/apps.64265.bc8119f5-db81-4fbd-9b66-209a1a09b3a0.c53e7d6b-3d52-455c-861b-a89971ace746.39025515-fff2-4b2d-9065-82c9faa9a58d

Furniture Category Recognition API

SC DE VIS SOFTWARE SRL

Furniture Category Recognition API

SC DE VIS SOFTWARE SRL

Recognizes furniture category or categories among most common categories for household furniture.

Furniture Category Recognition API - FurnishRec (also known as Furniture Category Detection API or Furniture Category Detector API) is a cross browsers REST API which get a JSON input with a still photo (as base64 encoded string), containing household furniture and returns a JSON string which contains a dominant Furniture Category of the input photo among the most used Furniture Categories and SubCategories: Baby Beds, Baby Chairs, Baldachin Beds, Bar Chairs, Bathroom Cabinets, Bed Frames, Bed Tables, Bedroom Cabinets, Benches, Camping Chairs, Camping Tables, Chair Beds, Clothes Hangers, Commode Furnitures, Decorative Mirrors, Hammocks, Kitchen Cabinets, Kitchen Corner Sofas, Kitchen Islands, Living Cabinets, Living Corner Sofas, Living Tables, Massage Armchairs, Matrimonial Beds, Meeting Tables, Nightstands, Office Chairs, Office Desks, Rocking Chairs, Round Tables, Shelves, Shoes Racks, Simple Armchairs, Simple Chairs, Simple Sofas, Single Beds, Sofa Beds, Sun Chairs, Twin Over Beds, Wobble Chairs. The recognized Furniture Categorys have confidence score, timestamp, tagId, tagName. 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 the furniture is clear and focused. If the furniture details are too small or blured, the accuracy is lower and the AI algorithm may not classify in a proper way. 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 has varifocal lenses, high shutter speed, good infrared lighting beam, full HD resolution.

Allthough this Automatic Furniture Category Recognition API (currently we do not offer a Furniture Category Recognition sdk) is intended for software development and therefore developers, we have also here an Furniture Category Recognition 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 Furniture Category Recognition 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 Furniture Category Recognition API is useful for a large number of domains like apps for: furniture e-commerce, furniture manufacturers, furniture distributors, furniture retailers 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.

https://store-images.s-microsoft.com/image/apps.11021.bc8119f5-db81-4fbd-9b66-209a1a09b3a0.c53e7d6b-3d52-455c-861b-a89971ace746.6738a46c-c33a-4b70-a144-a9f0ca8c6a8c
/staticstorage/8165fe0/assets/videoOverlay_7299e00c2e43a32cf9fa.png
https://store-images.s-microsoft.com/image/apps.11021.bc8119f5-db81-4fbd-9b66-209a1a09b3a0.c53e7d6b-3d52-455c-861b-a89971ace746.6738a46c-c33a-4b70-a144-a9f0ca8c6a8c
/staticstorage/8165fe0/assets/videoOverlay_7299e00c2e43a32cf9fa.png
https://store-images.s-microsoft.com/image/apps.11021.bc8119f5-db81-4fbd-9b66-209a1a09b3a0.c53e7d6b-3d52-455c-861b-a89971ace746.6738a46c-c33a-4b70-a144-a9f0ca8c6a8c