add_tags {AzureVision} | R Documentation |
Add, retrieve and remove tags for a project
Description
Add, retrieve and remove tags for a project
Usage
add_tags(project, tags)
add_negative_tag(project, negative_name = "_negative_")
list_tags(project, as = c("names", "ids", "dataframe", "list"),
iteration = NULL)
get_tag(project, name = NULL, id = NULL, iteration = NULL)
remove_tags(project, tags, confirm = TRUE)
Arguments
project |
A Custom Vision project. |
tags |
For |
negative_name |
For |
as |
For |
iteration |
For |
name , id |
For |
confirm |
For |
Details
Tags are the labels attached to images for use in classification projects. An image can have one or multiple tags associated with it; however, the latter only makes sense if the project is setup for multi-label classification.
Tags form part of the metadata for a Custom Vision project, and have to be explicitly defined prior to use. Each tag has a corresponding ID which is used to manage it. In general, you can let AzureVision handle the details of managing tags and tag IDs.
Value
add_tags
and add_negative_tag
return a data frame containing the names and IDs of the tags added.
Negative tags
A negative tag is a special tag that represents the absence of any other tag. For example, if a project is classifying images into cats and dogs, an image that doesn't contain either a cat or dog should be given a negative tag. This can be distinguished from an untagged image, where there is no information at all on what it contains.
You can add a negative tag to a project with the add_negative_tag
method. Once defined, a negative tag is treated like any other tag. A project can only have one negative tag defined.
See Also
add_image_tags
, remove_image_tags
Examples
## Not run:
add_tags(myproj, "newtag")
add_negative_tag(myproj)
remove_tags(myproj, "_negative_")
add_negative_tag(myproj, "nothing")
## End(Not run)