JSON Models
Model |
Description |
Category |
Category of the object. The set of potential categories depends on the model. For instance, with object recognition, a category may be a "chair" or "dog". For visual intent, it may be "food_or_drink". |
CategoryList |
A list of categories that an image matches. |
ImageInfo |
Information about the image. May be omitted if image binary is provided in POST request. Otherwise, either url or imageLookupToken is mandatory. |
ImageRequestInfo |
Base-64 encoded image and optional coordinates of crop area (if specified by user). |
Entity |
Describes an entity. |
IUFeature |
Defines a feature that was detected on the image. For instance, detected OCR or objects. |
IUModelResults |
Output of a model run on the image. The name of the object gives context into the model run, and a list of results is generated for the model. |
NormalizedBox |
Similar to NormalizedRectangle, a box that defines a portion of a larger rectangle. In most cases, NormalizedBox will define a portion of the input image. It contains a set of NormalizedPoints that define a box. |
NormalizedPoint |
An (x,y) coordinate normalized to the size of the image. It has values between 0 and 1. The values are relative to the width and height of the image (or other containing rectangle) respectively.
For instance a normalized point defined as (0.3, 0.5) would describe a point that is 30% across the image (from the left) and 50% down the image (from the top). |
NormalizedRectangle |
A rectangle specified as a portion of a larger rectangle - generally the input image. For instance, { left: 0, top: 0, right: 1, bottom: 1 } would be a rectangle that fills the containing rectangle. This is commonly used to describe a cropped area of an image. |
OcrRegion |
A grouping of text elements detected within an image. |
OcrText |
A block of text detected in an image. |
Category
Category of the object. The set of potential categories depends on the model. For instance, with object recognition, a category may be a "chair" or "dog". For visual intent, it may be "food_or_drink".
Name |
Type |
Description |
name |
string |
|
confidence |
number |
|
CategoryList
(extends IUFeature)
A list of categories that an image matches.
Name |
Type |
Description |
categories |
array[Category] |
|
featureType |
string |
Always 'Categories'. |
ImageInfo
Information about the image. May be omitted if image binary is provided in POST request. Otherwise, either url or imageLookupToken is mandatory.
Name |
Type |
Description |
recognitionModels |
array[IUModelResults] |
Objects (faces, etc.) and other features found by client-side recognition engines. One item per model. |
url |
string |
|
ImageRequestInfo |
ImageRequestInfo |
|
ImageRequestInfo
Base-64 encoded image and optional coordinates of crop area (if specified by user).
Describes an entity.
Name |
Type |
Description |
name |
string |
The name of the entity. For example, this could be a dog breed or plant name. |
description |
string |
A description of the entity. |
featureType |
string |
Always 'Entity'. |
IUFeature
Defines a feature that was detected on the image. For instance, detected OCR or objects.
Name |
Type |
Description |
featureType |
string |
|
score |
number |
Model's condifence score for this feature |
area |
NormalizedBox
|
|
text |
string |
for MSOCR featuretype |
categories |
array[Category] |
for Categories featureType |
IUModelResults
Output of a model run on the image. The name of the object gives context into the model run, and a list of results is generated for the model.
Name |
Type |
Description |
modelName |
string |
Name of the recognition engine |
results |
array[IUFeature] |
The list of results of the recognition model. If the array is empty, it means that the model was run, but there were no results. |
NormalizedBox
Similar to NormalizedRectangle, a box that defines a portion of a larger rectangle. In most cases, NormalizedBox will define a portion of the input image. It contains a set of NormalizedPoints that define a box.
NormalizedPoint
An (x,y) coordinate normalized to the size of the image. It has values between 0 and 1. The values are relative to the width and height of the image (or other containing rectangle) respectively.
For instance a normalized point defined as (0.3, 0.5) would describe a point that is 30% across the image (from the left) and 50% down the image (from the top).
Name |
Type |
Description |
x |
number |
|
y |
number |
|
NormalizedRectangle
A rectangle specified as a portion of a larger rectangle - generally the input image. For instance, { left: 0, top: 0, right: 1, bottom: 1 } would be a rectangle that fills the containing rectangle. This is commonly used to describe a cropped area of an image.
Name |
Type |
Description |
top |
number |
|
left |
number |
|
right |
number |
|
bottom |
number |
|
A grouping of text elements detected within an image.
Name |
Type |
Description |
ocrLines |
array[OcrText] |
Lines of text within the region. |
featureType |
string |
Always 'OcrRegion'. |
A block of text detected in an image.
Name |
Type |
Description |
text |
string |
The entire text detected in the image. |
embeddedTexts |
array[OcrText] |
(Optional) Sub-regions of text within the given block. For instance, this could be an array of lines in a paragraph. |
featureType |
string |
Always 'OcrText'. |