Using the Computer Vision service

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Hong Ooi

The Computer Vision service provides developers with access to advanced algorithms that process images and return information, depending on the visual features you’re interested in. For example, Computer Vision can determine if an image contains adult content, or it can find all of the human faces in an image.

Creating the resources

You can create a Computer Vision resource using the AzureRMR framework for interacting with Resource Manager. The available service tiers are F0 (free, limited to 20 API calls per minute and 5k calls per month) and S1 (up to 10 calls per second).

library(AzureVision)
rg <- AzureRMR::get_azure_login("yourtenant")$
    get_subscription("sub_id")$
    get_resource_group("rgname")

res <- rg$create_cognitive_service("myvis",
    service_type="ComputerVision", service_tier="S1")

Client interface

To communicate with the Computer Vision service, call the computervision_endpoint function with the service URL and key. Rather than a key, you can also supply an OAuth token obtained with the AzureAuth package.

url <- res$properties$endpoint
key <- res$list_keys()[1]

vis <- computervision_endpoint(url=url, key=key)

AzureVision supports all the Computer Vision API calls:

analyze extracts visual features from the image. To obtain more detailed features, specify the domain and/or feature_types arguments as appropriate.
describe attempts to provide a text description of the image.
detect_objects detects objects in the image.
area_of_interest attempts to find the “interesting” part of an image, meaning the most likely location of its subject.
tag returns a set of words that are relevant to the content of the image. Not to be confused with the add_tags or add_image_tags functions that are part of the Custom Vision API.
categorize attempts to place the image into a list of predefined categories.
read_text performs optical character recognition (OCR) on the image.
list_computervision_domains returns the predefined domain-specific models that can be queried by analyze for deeper analysis. Currently there are two domains: celebrities and landmarks.
make_thumbnail generates a thumbnail of the image.

Sample images

These are the images we’ll use to illustrate how the package works.

Filename	Description	Picture
`bill.jpg`	A portrait of Bill Gates
`park.jpg`	A picture of a city park
`gettysburg.jpg`	The text of the Gettysburg Address

An image to send to the endpoint can be specified as a filename, a publicly accessible Internet URL, or a raw vector. For example, these calls are equivalent, assuming the underlying image is the same:

# from the Internet
analyze(vis, "https://example.com/foo.jpg")

# local file
analyze(vis, "~/pics/foo.jpg")

# read the picture into a raw vector
foo <- readBin("~/pics/foo.jpg", "raw", file.size("~/pics/foo.jpg"))
analyze(vis, foo)

Calls

`analyze`

# analyze Bill's portrait
analyze(vis, "bill.jpg")

$categories
     name    score
1 people_ 0.953125

analyze has optional arguments domain, for choosing a domain-specific model with which to analyze the image; and feature_types, to specify additional details to return.

analyze(vis, "bill.jpg", domain="celebrities")

$categories
     name    score                                       celebrities
1 people_ 0.953125 Bill Gates, 0.999981284141541, 276, 139, 211, 211

analyze(vis, "bill.jpg", feature_types=c("faces", "objects"))

$faces
  age gender faceRectangle.left faceRectangle.top faceRectangle.width faceRectangle.height
1  50   Male                274               138                 210                  210

$objects
  rectangle.x rectangle.y rectangle.w rectangle.h object confidence
1         308         444         102         243    tie      0.652

`describe`

describe(vis, "bill.jpg")

$tags
 [1] "person"   "man"      "suit"     "clothing" "wearing"  "glasses"  "holding"  "standing" "looking"
[10] "front"    "posing"   "business" "older"    "dressed"  "sign"     "smiling"  "old"      "black"
[19] "phone"    "woman"    "people"

$captions
                               text confidence
1 Bill Gates wearing a suit and tie  0.9933712

`detect_objects`

detect_objects(vis, "park.jpg")

  rectangle.x rectangle.y rectangle.w rectangle.h   object confidence parent.object parent.confidence
1         624         278         132         351 building      0.637          <NA>                NA
2           3          22         314         843     tree      0.655         plant             0.658
3         749         353         284         380 building      0.544          <NA>                NA
4        1011           0         989         918     tree      0.719         plant             0.757

`area_of_interest`

area_of_interest(vis, "bill.jpg")

  x   y   w   h 
  0  45 750 749

`tag`

head(tag(vis, "park.jpg"))

      name confidence hint
1    grass  0.9999686 <NA>
2     tree  0.9996704 <NA>
3  outdoor  0.9990110 <NA>
4   flower  0.9853659 <NA>
5     park  0.8954747 <NA>
6 building  0.8255661 <NA>

`categorize`

categorize(vis, "bill.jpg")

     name    score
1 people_ 0.953125

`read_text`

read_text(vis, "gettysburg.png")

[[1]]
 [1] "Four score and seven years ago our fathers brought forth on this continent, a new nation,"
 [2] "conceived in Liberty, and dedicated to the proposition that all men are created equal."
 [3] "Now we are engaged in a great civil war, testing whether that nation, or any nation so"
 [4] "conceived and so dedicated, can long endure. We are met on a great battle-field of that war."
 [5] "We have come to dedicate a portion of that field, as a final resting place for those who here"
 [6] "gave their lives that that nation might live. It is altogether fitting and proper that we should"
 [7] "do this."
 [8] "But, in a larger sense, we can not dedicate—we can not consecrate —we can not hallow — this"
 [9] "ground. The brave men, living and dead, who struggled here, have consecrated it, far above"
[10] "our poor power to add or detract. The world will little note, nor long remember what we say"
[11] "here, but it can never forget what they did here. It is for us the living, rather, to be dedicated"
[12] "here to the unfinished work which they who fought here have thus far so nobly advanced. It"
[13] "is rather for us to be here dedicated to the great task remaining before us — that from these"
[14] "honored dead we take increased devotion to that cause for which they gave the last full"
[15] "measure of devotion— that we here highly resolve that these dead shall not have died in"
[16] "vain— that this nation, under God, shall have a new birth of freedom— and that government"
[17] "of the people, by the people, for the people, shall not perish from the earth."
[18] "— Abraham Lincoln"

`make_thumbnail`

make_thumbnail(vis, "bill.jpg", "bill_thumb.jpg")

Using the Computer Vision service

Hong Ooi

Creating the resources

Client interface

Sample images

Calls

analyze

describe

detect_objects

area_of_interest

tag

categorize

read_text

make_thumbnail

See also

`analyze`

`describe`

`detect_objects`

`area_of_interest`

`tag`

`categorize`

`read_text`

`make_thumbnail`