01
Help reviewers start with an organized queue
Inspection teams may receive photos of packaging, returned products, or equipment conditions. StayCharted AMT can learn photo categories your reviewers have already assigned, helping organize incoming pictures for the next review step.
This is image classification for triage. It does not locate defects within a picture, measure their size, or determine whether equipment is safe to use.
| Illustrative photo | Team-assigned category |
|---|---|
| Carton with a crushed corner | Packaging damage |
| Product casing with a visible scratch | Surface damage |
| Inspection photo without an apparent issue | No visible issue |
02
Use your inspection team’s labels
Choose one clearly defined classification task. Agree on what each label means, and have qualified reviewers resolve ambiguous examples. Include normal conditions as well as the visible issue categories you want to distinguish.
Include variation in camera angle, lighting, background, and product type. A “no visible issue” label describes the picture only; it is not a certification that the item is undamaged or safe.
03
Choose how your image model learns
With the Vision add-on, an AI Image Classifier Model uses ready-made vision AI to read pictures and a private classifier to learn your categories. The ready-made AI does not train on your uploaded pictures.
A Dedicated AI Image Model, on Business with Vision, trains the vision AI itself on your pictures. Training takes longer. Compare both approaches on the same set-aside pictures to choose for your task; dedicated training does not guarantee better accuracy.
04
Prepare pictures your model can learn from
Upload a ZIP with one folder per category, or a spreadsheet of public HTTPS picture links and category labels. Use consistent labels and examples that represent the lighting, angles, backgrounds, and quality of future pictures.
StayCharted AMT checks for category mismatches, conflicting labels, near-duplicates, and unreadable links. Review those findings before training. Hidden image metadata is removed on upload; this does not hide faces, personal information, or text visible in a picture.
05
Keep the final decision with your reviewers
- New inspection photo
- StayCharted AMT category and confidence
- Your application creates a review item
- Reviewer confirms the finding
- Your team decides the next action
Use file results or API predictions to prepare review queues. Your application controls assignments and actions. Low-confidence or unfamiliar pictures need review, and high confidence does not remove the possibility of error.
Evaluate missed issues as well as incorrect flags on unseen photos. Do not use photo categories alone for safety approval, claim eligibility, or other consequential decisions.
06
Common questions about visual inspection
Can it find a hairline crack or a tiny defect? Fine details may be lost during image processing. Evaluate your actual photos and defect sizes; this workflow does not promise detection of small or hidden damage.
Does it draw a box around the damage? No. These models classify the picture into your categories; they do not provide defect localization or segmentation.
Can a dedicated image model improve the result? It is an option to evaluate when category differences are subtle. Compare measured results on the same set-aside photos rather than assuming it will perform better.
Can it approve an inspection automatically? The supported use here is categorization and triage. Qualified people and your existing inspection process determine the final outcome.