Background
The quality of prompt words directly impacts object detection performance, and a well-designed prompt strategy can significantly improve detection accuracy.
Optimization methods
- Principle of Specification::
- Use specific quantifiers (e.g., ”test 3 people” instead of ”test people”)
- Add a distinctive feature (e.g., ”the person wearing a red hat”)
- Structured tips::
- For complex scenarios, use step-by-step instructions (first ”locate all vehicles,” then ”identify left-turning vehicles”).
- Use relational descriptions (e.g., ”the phone on the table” rather than detecting objects individually)
- negative exclusion::
- Explicitly exclude interfering items (e.g., ”detect automobiles but exclude trucks”)
- Use contrasting descriptions (e.g., ”detect abnormal areas”)
Practice Tips
- Save effective prompt templates for reuse in similar scenarios
- Share and discover high-quality prompt examples in the VisionAgent Discord community.
- For critical testing tasks, prepare 2-3 differently phrased prompts for comparative use.
Effectiveness evaluation
Through systematic prompt optimization, detection accuracy can be improved by 30%-50% while reducing duplicate detection instances.
This answer comes from the articleAgentic Object Detection: A Visual Object Detection Tool without Annotation and TrainingThe
May not be reproduced without permission:AI productivity tools " How to optimize the effect of cue words when using Agentic Object Detection?
