AI-102 Implement computer vision solutions Practice Question
Which TWO actions should you take to reduce the latency of an Azure AI Computer Vision OCR call on a large image?
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
✓
Resize the image to a smaller resolution before calling the API.
Options B and D are correct. B: Resizing reduces processing time. D: Using the Read API asynchronously allows the client to poll, avoiding timeout. A: Increasing timeout doesn't reduce latency. C: Using CPU doesn't help. E: Cognitive Services container on-premises might add network latency.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use a CPU-bound compute instance.
Why it's wrong here
CPU doesn't accelerate OCR.
- ✓
Resize the image to a smaller resolution before calling the API.
Why this is correct
Smaller images process faster.
- ✗
Increase the API timeout value.
Why it's wrong here
Timeout does not affect processing speed.
- ✓
Use the Read API asynchronously.
Why this is correct
Async operation allows the server to process without blocking the client.
- ✗
Deploy the Cognitive Services container on-premises.
Why it's wrong here
On-premises may add latency if not properly configured.
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