First Image & Recipe Test (Repeat to creating first recipe)
This guide helps you capture your first image, configure basic Image Settings, and test a simple classifier recipe using the OV20i, following the official user manual steps.
Prerequisites
- Camera powered and connected (all 4 LEDs are green)
- You can access the camera's UI (e.g.,
http://192.168.0.100
) - Sample part placed under the camera's view
- Proper lighting is configured
Step 1: Create & Activate a New Classifier Recipe
- In the UI, go to Recipes > All Recipes.
- Click + New Recipe, name it (e.g., "TestRecipe"), and select Classifier type.
- On the new recipe listed, click Actions > Activate, then hit Activate.
Step 2: Configure Image Settings
- Click Edit then Open Editor.
- Select Configure Imaging (bottom left of editor).
- Adjust:
- Focus (slider or manual value)
- Exposure
- LED Light Pattern (top/down, brightness)
- Gamma for contrast
- Click Save Imaging Settings to apply.
Step 3: Template Image & Alignment
- Navigate to Template Image and Alignment.
- Capture the current view as the template.
- For now, click Skip Aligner (optional).
- Click Save.
Step 4: Inspection Setup – Create ROI
- Navigate to Inspection Setup.
- Add your part or defect class.
- Draw the Region of Interest (ROI) around the relevant area.
- Click Save to apply.
Step 5: Train the Classifier
- Go to Classification block in the Recipe Editor.
- For each class (e.g., Good/Bad), capture ≥5 diverse images.
- Click Train Classification Model.
- In the prompt, choose Fast (trial) or Accurate (production).
- Adjust iterations as needed.
- Click Start Training.
- When done, click Live Preview to test the model.
Step 6: Evaluate Results
- "PASS" appears when a correct part is shown.
- "FAIL" appears for other objects or defective parts.
- Use Live Preview to watch real-time inference.
Troubleshooting Tips
- No video feed? → Check Ethernet and LEDs.
- Capture disabled? → Ensure Imaging settings are saved.
- ROI not applying? → Redraw and click Save.
- Model not training? → Verify all classes have ≥5 labeled samples.