This AI-102 practice question tests your understanding of implement computer vision solutions. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
Refer to the exhibit.
```json
{
"url": "https://example.com/image.jpg",
"visualFeatures": ["Categories", "Tags", "Description", "Faces", "ImageType", "Color", "Adult"],
"details": ["Celebrities", "Landmarks"],
"language": "en"
}
```You call the Azure Computer Vision Analyze API with the above request body. The response includes a 'description' object with captions. Which parameter is responsible for generating captions?
Refer to the exhibit.
```json
{
"url": "https://example.com/image.jpg",
"visualFeatures": ["Categories", "Tags", "Description", "Faces", "ImageType", "Color", "Adult"],
"details": ["Celebrities", "Landmarks"],
"language": "en"
}
```Description
Generates captions describing the image.
Categories
Why wrong: Returns category hierarchy.
Adult
Why wrong: Detects adult/racy content.
Tags
Why wrong: Returns content tags.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Description
The 'description' parameter in the Azure Computer Vision Analyze API request body explicitly requests the service to generate human-readable captions and tags that describe the image content. When set to true, it enables the 'description' object in the response, which contains an array of captions with confidence scores. This is the direct mechanism for caption generation.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Description
Why this is correct
Generates captions describing the image.
Related concept
Read the scenario before looking for a memorised answer.
Categories
Why it's wrong here
Returns category hierarchy.
Adult
Why it's wrong here
Detects adult/racy content.
Tags
Why it's wrong here
Returns content tags.
Common exam traps
The trap here is that candidates confuse 'tags' (single-word labels) with 'captions' (full sentences), assuming that enabling tags will also produce descriptive text, but only the 'description' parameter triggers the caption generation pipeline.
Detailed technical explanation
Under the hood, the 'description' parameter triggers a deep neural network that combines object detection, scene understanding, and natural language generation to produce captions. The API returns up to 10 captions in the 'captions' array, each with a 'text' string and a 'confidence' score between 0 and 1. In real-world scenarios, you might use this for accessibility features (e.g., generating alt text for images) or for automated content summarization in media libraries.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
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FAQ
Implement computer vision solutions — This question tests Implement computer vision solutions — Read the scenario before looking for a memorised answer..
The correct answer is: Description — The 'description' parameter in the Azure Computer Vision Analyze API request body explicitly requests the service to generate human-readable captions and tags that describe the image content. When set to true, it enables the 'description' object in the response, which contains an array of captions with confidence scores. This is the direct mechanism for caption generation.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
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