AI-102 Implement computer vision solutions Practice Question
Which TWO Azure AI services can be used to detect objects in images?
⚠ Common exam trap
Many candidates confuse the general-purpose Computer Vision Object Detection API (which is pre-trained on common objects) with Custom Vision (which requires custom training), but both are valid for object detection depending on the scenario, and the question asks for two services that can detect objects, making both C and E correct.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Custom Vision
Custom Vision (C) is correct because it is an Azure AI service that lets you train and deploy custom image classification and object detection models, returning bounding boxes for detected objects in images. Computer Vision Object Detection API (E) is correct because the Azure AI Vision (Computer Vision) service provides a prebuilt object detection capability that identifies common objects and their bounding box coordinates in an image. Video Indexer (A) is not the right fit here since it focuses on analyzing and indexing video and audio content rather than being an image object detection service. Face API (B) only detects and analyzes human faces (and related attributes), not general objects. Azure AI Document Intelligence (D) extracts text, key-value pairs, and structured data from documents, so it does not perform general object detection in images.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Video Indexer
Why it's wrong here
Video Indexer extracts insights from video and audio streams, such as speech, faces and topics, rather than detecting objects in still images. It is tempting because it does analyse visual media, and it would be correct for indexing and searching a video library.
- ✗
Face API
Why it's wrong here
The Face API returns attributes such as age, emotion and identity for detected human faces; it does not perform general object detection across arbitrary classes. It is tempting because it does process images and locate faces, but that is face-specific detection, not the broad object detection Custom Vision or Computer Vision provides.
- ✓
Custom Vision
Why this is correct
Custom Vision trains a bespoke object detection model on your own labelled images, returning bounding boxes per class. It satisfies the stem's requirement to detect objects, unlike classification-only or face-based services, because you control the labelled dataset and exported model.
- ✗
Azure AI Document Intelligence
Why it's wrong here
Document Intelligence extracts text, key-value pairs and tables from documents; it performs no object detection in images. It is tempting because it is a vision-adjacent AI service, and it would be correct for processing forms, invoices and receipts.
- ✓
Computer Vision Object Detection API
Why this is correct
The Computer Vision Object Detection API returns bounding-box coordinates for multiple object classes within an image, satisfying the stem's requirement to detect objects rather than merely classify or caption them. It suits scenarios needing spatial localisation of several items in a single frame, unlike image classification, which assigns one label per image.
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