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Exam AI-102 topic 2 question 12 discussion

Actual exam question from Microsoft's AI-102
Question #: 12
Topic #: 2
[All AI-102 Questions]

DRAG DROP -
You are developing a call to the Face API. The call must find similar faces from an existing list named employeefaces. The employeefaces list contains 60,000 images.
How should you complete the body of the HTTP request? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Select and Place:

Show Suggested Answer Hide Answer
Suggested Answer:
Box 1: LargeFaceListID -
LargeFaceList: Add a face to a specified large face list, up to 1,000,000 faces.
Note: Given query face's faceId, to search the similar-looking faces from a faceId array, a face list or a large face list. A "faceListId" is created by FaceList - Create containing persistedFaceIds that will not expire. And a "largeFaceListId" is created by LargeFaceList - Create containing persistedFaceIds that will also not expire.
Incorrect Answers:
Not "faceListId": Add a face to a specified face list, up to 1,000 faces.

Box 2: matchFace -
Find similar has two working modes, "matchPerson" and "matchFace". "matchPerson" is the default mode that it tries to find faces of the same person as possible by using internal same-person thresholds. It is useful to find a known person's other photos. Note that an empty list will be returned if no faces pass the internal thresholds. "matchFace" mode ignores same-person thresholds and returns ranked similar faces anyway, even the similarity is low. It can be used in the cases like searching celebrity-looking faces.
Reference:
https://docs.microsoft.com/en-us/rest/api/faceapi/face/findsimilar

Comments

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Jenny1
Highly Voted 3 years, 6 months ago
Correct.
upvoted 20 times
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PHD_CHENG
Highly Voted 2 years, 7 months ago
Facelist ID up to 1,000 faces; LargeFaceListId up to 1,000,000 faces https://docs.microsoft.com/en-us/rest/api/faceapi/large-face-list
upvoted 12 times
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famco
Most Recent 3 months, 1 week ago
Another of the detective style finding answers from hidden clues in the english language usage. Microsoft is a truly remarkable org. Similar face, must find and employes. Similar face and Must find might point to matchFace, but for employees it should be matchPerson (we need the person not similar looking). Now, what will you choose? Very hard. Remarkable piece of hmm sweetness.
upvoted 1 times
famco
3 months, 1 week ago
And the fact that this remarkable org created a largeFaceList and a faceList and expects one to remember that piece of bad design. The size of the facelist should not be in the client calls, but at the server. Now if the facelist increases in size the clients need to change. What kind of org creates these kind of things and shamelessly ask that in certification exam. Microsoft is the answer.
upvoted 1 times
famco
3 months, 1 week ago
I will go for matchFace considering the other clue "similar face" instead of person. Man, this question should be taken to court and microsoft should be whipped
upvoted 1 times
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rookiee1111
5 months, 3 weeks ago
LargeFaceIdList matchFace - reason why not matchPerson - becomes matchPerson compares agains larger person group and not one to one, here we are doing matchFace to find similar faces based on one to one analysis.
upvoted 2 times
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HaraTadahisa
5 months, 3 weeks ago
1. LargeFaceListId 2. matchFace
upvoted 1 times
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nanaw770
6 months, 3 weeks ago
1. LargeFaceListId 2. matchFace
upvoted 1 times
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varinder82
8 months, 3 weeks ago
Final Answer: 1. LargeFaceListId 2. matchFace ( matchPerson could return an empty list, but matchFace will not.)
upvoted 4 times
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Ody
8 months, 3 weeks ago
The key is "must find". matchPerson could return an empty list, but matchFace will not.
upvoted 1 times
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rdemontis
1 year, 1 month ago
correct answer: https://learn.microsoft.com/en-us/rest/api/faceapi/face-list?view=rest-faceapi-v1.0
upvoted 1 times
rdemontis
1 year, 1 month ago
Sorry but I have to laugh off my previous answer: "matchPerson" is the default mode that it tries to find faces of the same person as possible by using internal same-person thresholds. It is useful to find a known person's other photos. Note that an empty list will be returned if no faces pass the internal thresholds. "matchFace" mode ignores same-person thresholds and returns ranked similar faces anyway, even the similarity is low. It can be used in the cases like searching celebrity-looking faces" https://learn.microsoft.com/en-us/rest/api/faceapi/face/find-similar?view=rest-faceapi-v1.0&tabs=HTTP
upvoted 1 times
rdemontis
1 year, 1 month ago
in this case we are talking about finding the faces of people who are employees of an organization. We are not talking about famous people. So the recognition will have to be done by an internal set of images of the faces whose faces are to be matched in the corporate photo gallery. Also set maxNumOfCandidatesReturned = 1. Which means that it is also acceptable not to find matches. Which is not the case with matchFace because it also tolerates a low confidence coefficient. Considering what is reported in the article I think the second answer to the question is more correct matchParson.
upvoted 2 times
rdemontis
1 year, 1 month ago
Sorry, but after further investigation I am not sure that this is the case. Frankly, the Microsoft documentation in this case doesn't seem to be very satisfactory.
upvoted 1 times
famco
3 months, 1 week ago
Although Microsoft is known for bad products, confusing naming conventions, no-alignment across products, confusing documentation and useless certification questions, this is a case of wrong question.
upvoted 1 times
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Eltooth
2 years, 4 months ago
I'm leaning towards: largeFaceListId and matchedPerson https://docs.microsoft.com/en-us/rest/api/faceapi/face/find-similar?tabs=HTTP#find-similar-results-example "matchPerson" is the default mode that it tries to find faces of the same person as possible by using internal same-person thresholds. It is useful to find a known person's other photos. Note that an empty list will be returned if no faces pass the internal thresholds. "matchFace" mode ignores same-person thresholds and returns ranked similar faces anyway, even the similarity is low. It can be used in the cases like searching celebrity-looking faces.
upvoted 7 times
makciek
1 year, 3 months ago
it says "The call must find similar faces from an existing list named employeefaces", similar being the keyword here so matchFace i think is correct.
upvoted 1 times
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ccie_pgh
11 months, 3 weeks ago
Agree since code also has "maxNumOfCandidatesReturned", which would be ignored by "matchFace"... both "matchFace" and "matchPerson" find similars but only "matchPerson" will use internal thresholds.
upvoted 2 times
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PHD_CHENG
2 years, 6 months ago
Was on exam 7 Jun 2022
upvoted 3 times
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luishenriquesb
2 years, 6 months ago
it's should be largeFaceListId not LargeFaceListId (Capitalized). It's wouldn't work in a http request...
upvoted 5 times
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gursimran_s
2 years, 7 months ago
The 1000 face parameter is for the faceIds and not the faceListId.So, it could be faceListId as well.
upvoted 1 times
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gursimran_s
2 years, 7 months ago
Why not faceListId? Nothing specific mentioned on MS docs.
upvoted 1 times
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klion
2 years, 10 months ago
"matchPerson" Find similar results example Sample Request HTTP POST {Endpoint}/face/v1.0/findsimilars Ocp-Apim-Subscription-Key: {API key} Request Body JSON { "faceId": "c5c24a82-6845-4031-9d5d-978df9175426", "largeFaceListId": "sample_list", "maxNumOfCandidatesReturned": 1, "mode": "matchPerson" } https://docs.microsoft.com/en-us/rest/api/faceapi/face/find-similar
upvoted 2 times
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sumanshu
2 years, 11 months ago
In Question it's given we have to find similar faces - So we have to use "matchFace" and because there are large list , so we have to use LargeFaceListID
upvoted 5 times
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mikegsm
3 years, 1 month ago
Seems Correct
upvoted 2 times
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