Discover how to select the ideal Azure Vision API for e-commerce applications requiring object detection, text extraction, and face recognition. Perfect for AI-102 exam prep and real-world solutions.
Table of Contents
Question
You are an application developer at Nutex Inc. You have been tasked with developing an e-commerce application that allows users to upload images after purchase to provide product reviews. The platform needs to perform the following tasks:
- Object Detection: Detect and highlight specific objects within the images (e.g., identify products, logos, or other relevant items).
- Text Extraction: Extract text from product labels, packaging, or any visible text within the images.
- Face Recognition: Recognize and verify the faces of registered users for personalized experiences.
The solution should be accurate, reliable, and able to handle many concurrent requests. You plan to use the Azure cognitive service for Vision to achieve the objective.
Which of the following Vision APIs is BEST to use in the given scenario?
A. Custom Vision
B. Face service
C. Computer Vision
D. Azure Machine Learning
Answer
C. Computer Vision
Explanation
In the given scenario, the Computer Vision API is the best one to use. This API provides pre-trained models for image analysis, object detection, and optical character recognition (OCR). It is suitable for scenarios where you need accurate and reliable computer vision capabilities out of the box.
The custom vision API is not the best choice in the given scenario. This API allows you to build custom image classification models using your own labeled data. However, it may not meet the scalability needs for the described scenario. You can create custom models with specific classes and labels based on your data. While it can handle moderate workloads, it may not be suitable for large-scale image analysis. This API is not ideal for the real-time processing of a high volume of images.
The face service API is not the best choice in the given scenario. It is specialized for face detection, recognition, and analysis. However, it is not designed for general-purpose computer vision tasks. The Azure face service API focuses exclusively on face-related tasks, such as identifying faces, verifying identities, and analyzing facial attributes. It does not cover broader computer vision scenarios such as object detection and OCR.
Azure Machine Learning is not the best choice in the given scenario. Azure Machine Learning is a versatile service that allows you to construct, train, and establish machine learning models. However, it is not specifically tailored for computer vision tasks. Azure Machine Learning serves various machine learning scenarios, including regression, classification, clustering, and time-series forecasting. You can create custom models using your algorithms and data, but this requires significant effort in model training, hyperparameter tuning, and feature engineering.
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