The document contains examples of JSON responses from various cognitive services APIs, including: - A text detection API that detects text in an image and returns bounding box coordinates. - A face detection API that detects faces in an image and returns attributes like age, gender, and head pose. - A face verification API that takes two face images and returns whether they are identical. - An intent recognition API that takes text and returns the most likely intent and confidence scores. - Examples of using the APIs in code and accessing documentation on the Project Oxford site.

13. JSON:
{
"language": "en",
"orientation": "Up",
"regions": [
{
"boundingBox": "41,77,918,440",
"lines": [
{
"boundingBox": "41,77,723,89",
"words": [
{
"boundingBox": "41,102,225,64",
"text": "LIFE"
},
{
"boundingBox": "356,89,94,62",
"text": "IS"
},
{
"boundingBox": "539,77,225,64",
"text": "LIKE"
}
. . .
TEXT:
LIFE IS LIKE
RIDING A BICYCLE
TO KEEP YOUR BALANCE
YOU MUST KEEP MOVING

17. Detection Result:
JSON:
[
{
"faceRectangle": {
"width": 109,
"height": 109,
"left": 62,
"top": 62
},
"attributes": {
"age": 31,
"gender": "male",
"headPose": {
"roll": "2.9",
"yaw": "-1.3",
"pitch": "0.0"
}
"faceLandmarks": {
"pupilLeft": {
"x": "93.6",
"y": "88.2"
},
"pupilRight": {
"x": "138.4",
"y": "91.7"
},
...

18. Verification Result:
JSON:
[
{
"isIdentical":false,
"confidence":0.01
}
]

26. <speak version="1.0"
xmlns="http://www.w3.org/2001/10/synthesis"
xmlns:mstts="http://www.w3.org/2001/mstts"
xml:lang="en-US">
<voice name="Microsoft Server Speech Text to Speech
Voice (en-US, ZiraRUS)">
Synthesize audio from text, to speak to your users.
</voice></speak>

28. {
“entities”: [
{
“entity”: “flight_delays”,
“type”: “Topic”
}
],
“intents”: [
{
“intent”: “FindNews”,
“score”: 0.99853384
},
{
“intent”: “None”,
“score”: 0.07289317
},
{
“intent”: “ReadNews”,
“score”: 0.0167122427
},
{
“intent”: “ShareNews”,
“score”: 1.0919299E-06
}
]
}

30. https://www.projectoxford.ai

32. Forum
 Find Us
 visit www.msdn.com filter “Project Oxford” under “Microsoft Azure”
 “Community” link in http://www.projectoxford.ai/
 Sample Code
 SDK
 http://www.projectoxford.ai/sdk
 RESTful API
 C#, Java, Node's, PHP, Python, Ruby, Android…
 Complete Solution

33. Magic of How-Old.net
1. Apply Subscription of “Face API” and get your subscription Key
2. Design your app
3. Use detection of “Face API”
static async void MakeRequest()
{
var client = new HttpClient();
var queryString = HttpUtility.ParseQueryString(string.Empty);
// Specify values for optional parameters, as needed
// queryString["analyzesFaceLandmarks"] = "false";
// queryString["analyzesAge"] = "false";
// queryString["analyzesGender"] = "false";
// queryString["analyzesHeadPose"] = "false";
// Specify your subscription key
queryString["subscription-key"] = "";
// Specify values for path parameters (shown as {...})
var uri = "https://api.projectoxford.ai/face/v0/detections?" + queryString;
HttpResponseMessage response;
// Specify request body
byte[] byteData = Encoding.UTF8.GetBytes("");
using (var content = new ByteArrayContent(byteData))
{
response = await client.PostAsync(uri, content);
}
if (response.Content != null)
{
var responseString = await response.Content.ReadAsStringAsync();
Console.WriteLine(responseString);
}
}

34. Magic of TwinsOrNot.net
Verification Result:
JSON: [{"isIdentical":false,"confidence":0.01 }]