AI-102 Implement computer vision solutions Practice Question
Exhibit
Refer to the exhibit.
{
"url": "https://example.com/image.jpg",
"features": [
"tags",
"objects",
"caption"
],
"language": "en",
"model-version": "latest",
"gender-neutral-caption": true
}You are calling the Azure AI Vision Image Analysis API with the above JSON request. The API returns a response that includes tags, objects, and a caption. However, the caption does not describe the image accurately. Which change should you make to improve the caption quality?
⚠ Common exam trap
Candidates often assume caption quality is always improved by newer models or additional features like OCR, when in fact the issue is a specific configuration parameter (`gender-neutral-caption`) that directly controls the level of detail in person descriptions.
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
✓
Set gender-neutral-caption to false
Setting `gender-neutral-caption` to false forces the Azure AI Vision Image Analysis API to generate captions that include gender-specific terms (e.g., 'man' or 'woman') instead of neutral terms like 'person'. This improves caption accuracy when the image clearly depicts a person whose gender is identifiable, because the default (true) may produce a vague description that fails to capture the subject's characteristics.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Change model-version to a newer version
Why it's wrong here
The latest version is already being used.
- ✗
Add 'read' feature to the request
Why it's wrong here
The 'read' feature is for OCR, not for improving captions.
- ✓
Set gender-neutral-caption to false
Why this is correct
Gender-neutral captions may omit descriptive terms, reducing accuracy.
- ✗
Set language to 'en-US'
Why it's wrong here
The language 'en' is sufficient for English captions.
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