Computer vision for visual inspection
Support repeatable image review with evaluation tied to actual capture and operating conditions.
The situation.
People inspect images or video for a defined object, condition or defect. The model must be evaluated against the lighting, viewpoints, motion and image quality it will encounter, with an explicit response when the evidence is uncertain.
A practical approach.
- 01
Specify the visual task
Define categories, capture conditions, annotation rules and the cost of a missed detection.
- 02
Build representative data
Plan collection and evaluation splits that reflect the intended environment.
- 03
Integrate review
Connect model outputs to review, escalation and monitoring of changing capture conditions.
What to validate
- Measure performance separately for important operating conditions.
- Retain a review path for uncertain or unfamiliar inputs.
Typical outputs
- Image and annotation requirements
- Condition-specific evaluation report
- Perception and review integration design
Example measures
- Missed and incorrect detections
- Performance by capture condition
- Human review volume and latency
Agree a baseline and acceptance criteria for the specific project.
Illustrative scenario and conceptual imagery. Scope, deliverables and acceptance evidence are agreed for each engagement; example measures are not achieved results.