HOTSPOT -
You are building a model that will be used in an iOS app.
You have images of cats and dogs. Each image contains either a cat or a dog.
You need to use the Custom Vision service to detect whether the images is of a cat or a dog.
How should you configure the project in the Custom Vision portal? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Hot Area:
Box 1: Classification -
Incorrect Answers:
An object detection project is for detecting which objects, if any, from a set of candidates are present in an image.
Box 2: Multiclass -
A multiclass classification project is for classifying images into a set of tags, or target labels. An image can be assigned to one tag only.
Incorrect Answers:
A multilabel classification project is similar, but each image can have multiple tags assigned to it.
Box 3: General -
General: Optimized for a broad range of image classification tasks. If none of the other specific domains are appropriate, or if you're unsure of which domain to choose, select one of the General domains.
Reference:
https://cran.r-project.org/web/packages/AzureVision/vignettes/customvision.html
The third choice should be General compact, in other that the model can be exported to be used in iOS device
it seems the general compact is for edge device not ios. https://docs.microsoft.com/en-us/azure/cognitive-services/custom-vision-service/select-domain#image-classification
So general compact is correct since ios device is an edge device.
How about this article? https://learn.microsoft.com/en-us/azure/ai-services/custom-vision-service/export-your-model
thanks for sharing the documentation.
agree with you
Classification Multiclass General (compact)
1. Classification 2. Multiclass 3. General (compact) https://learn.microsoft.com/en-us/azure/cognitive-services/custom-vision-service/getting-started-build-a-classifier - Select Classification under Project Types. Then, under Classification Types, choose either Multilabel or Multiclass, depending on your use case. Multilabel classification applies any number of your tags to an image (zero or more), while multiclass classification sorts images into single categories (every image you submit will be sorted into the most likely tag). You'll be able to change the classification type later if you want to.
- Next, select one of the available domains. Each domain optimizes the model for specific types of images, as described in the following table. You can change the domain later if you wish. -- Generic Optimized for a broad range of image classification tasks. If none of the other domains are appropriate, or you're unsure of which domain to choose, select the Generic domain. -- Compact domains Optimized for the constraints of real-time classification on mobile devices. The models generated by compact domains can be exported to run locally.
I also think that General(compact) https://docs.microsoft.com/en-us/azure/cognitive-services/custom-vision-service/export-your-model 1. It can be running offline 2. Real time locally
1. Classification 2. Multiclass 3. General (compact)
1. Classification 2. Multiclass 3. General (compact)
Classification Multiclass General (compact)
classification multiclass General (compact): Since the model will be used in an iOS app, a compact model is preferred for performance and size reasons. The "General (compact)" domain is suitable for a wide range of image classification tasks and is optimized for mobile and edge devices.
1. Classification 2. Multiclass 3. General (compact)
1 - Classification 2 - Multiclass (single tag per image) 3 - General (compact) Custom Vision Service only exports projects with compact domains. The models generated by compact domains are optimized for the constraints of real-time classification on mobile devices. Classifiers built with a compact domain may be slightly less accurate than a standard domain with the same amount of training data.
Final Answer: Classification Multiclass General (compact)
Correct