Vufind Recognize is an algorithmic computer vision/object recognition API, i.e no human crowd-sourcing layer is involved. There are pros and cons to that. Major pros are: It's real-time, and scales very cost-effectively including for video. However, at the same time, it can't be expected to be 100% accurate. Please note that it's well documented that humans can't deliver 100% accuracy either if they have to inspect 20 images or more per second, or if you expect them to tag all the objects in the frame, and in case of video they tire very quickly. Most importantly, crowd-sourcing costs orders of magnitude more than machine vision.

Vufind's platform is quite configurable and shortly we will expose parameters to enable you to choose to optimize for maximum "recall" (show as many tags as possible even if not very confident), or minimize false-positive rate (i.e only show a tag when the engine is very confident). Our recommendation is to choose minimize FP rate for consumer apps, such photo-albums and augmented reality apps. On the other hand, for advertising/commerce applications, maximizing recall might be a better choice.

We tend to refer to them as "object classifiers", although researchers distinguish between category recognition for a class of objects with variety of shapes (for ex. car, high-rise building, long-dress, sashimi, cat) vs. instance recognition (golden-gate bridge, EmpireState Building, salmon sashimi)

Feb 15, 2014 Update:

Version V1.7.5 of public developers version API Recognize endpoint has been updated, and now has the following classifiers below. We've always adding new classifiers to the set based on customer demand, so feel free to email us any time with the needs of your application. We'd love to hear from you. biz@vufind.com

Genre =fashion: -Long-dress -Short-dress -Purse -High-heels -Women-boots -Women-Long-coat -Sunglasses

Genre=decor - modern-decor - living-room - dining-room - bedroom

Genre= brands: - Pepsi - TacoBell - coming soon (LouisVuitton)

Genre= scenes - outdoors - beach - creek - garden - highrise-bldg - mountain - playground - sea/ocean - shoppingMall

Genre=food - pizza - fried-rice - fried-dumplings - salad - sushi - sashimi - shrimp-cocktail

Genre=landmarks -eiffel-tower -empirestate-bldg -goldengate-br -bay-br -disneycastle -oslo-cityhall -sonoma-cityhall -sydney-opera -white-house

Genre=man-made - sedan - cruiseship - sportscar

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HTTP 200 : string GET/vugraph/v175/recognize.php
recognize Object/Product/Scene recognition in images/video

Recognize objects in an image and return the tags


Test console
Description
Parameter
string

specifies the types of objects you are interested in getting tags for. For example, for location context, you'd specify genre=landmarks, for shopping apps, use genre=apparel, etc. Supported genres: fashion, decor,food,landmarks,man-made,moms,nature,scenes.
Example: fashion

genre

Required

string

The URL of the photo, preferably terminating in .jpg or .png. We do not accept .GIF images
Example: https://s3.amazonaws.com/vufind.demos/img/fashion/halle.jpg

url

Required

string

your app's id of user associated with this image (for interest graph purposes)
Example: 777999

user_id

Required

string

Vufind's API key
Example: dee1eb769deb1c7ed850fc2ab18c31e5

app_key

Required

string

Vufind's persistent token
Example: 3hbv1ionxeoyl9pzsy49e7bl5yh45i830nxuono4vzq309ii80whj9mu022rwgd3

token

Required

  • string – Server overloaded Please try again a bit later. Thanks!

    HTTP 502
  • string – Server Overloaded

    HTTP 503
  • string – Bad API parameter values, and possiblky the image/video URL

    HTTP 400

You must have an API key to test this API!


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