Create Your First Recipe (OV10i)

Time: 30-45 minutes

This is where your camera becomes an AI inspector. A recipe is a complete package (image settings, alignment, inspection regions, AI model, and output rules) bundled together for one specific inspection task.

You can have as many recipes as you want on a camera. Each one can be saved, backed up, transferred to other cameras, and version controlled.

Before you start: remember the waterfall

Everything in this section follows the Waterfall Principle. You'll go through six steps in order. Don't skip ahead. Verify each step works before moving to the next.

1

Image Settings

Exposure, Gain, LEDs

2

Template & Aligner

Capture, Align

3

Inspection Regions

Draw ROIs

4

AI Training

Label, Train

5

Output Rules

Pass/Fail, IO

6

Deploy!

Activate, Verify

Create a new recipe

1. Go to All Recipes in the left sidebar (this is also the landing page when you open the camera)
2. Click + New
3. Give it a name (e.g., "Screw Presence Check")
4. The OV10i uses classification recipes (pass/fail, presence/absence, or multi-category decisions)
5. Click Activate to enter the recipe editor

Classification only

The OV10i supports classifiers only. For pixel-level defect detection (segmentation), you need an OV20i or OV80i.

The OV10i supports classifiers only

If your inspection requires pixel-level defect detection (segmentation), where the AI highlights the exact shape and location of each defect, you will need an OV20i or OV80i. The OV10i is designed for classification tasks: pass/fail, presence/absence, and multi-category decisions. Plan your camera selection accordingly before investing time in recipe setup.

Now follow the six steps:

Start with Development Mode enabled

Development Mode lets you test your recipe without affecting production output. Use it throughout the setup process to verify each step works correctly. Switch to Production Mode only after you have confirmed accuracy across a representative set of test parts.

Step 1: Image Settings

Full guide: Image Settings

Get your camera image looking clean and consistent. Adjust exposure, gain, white balance, and, critically, enable lens distortion correction if you're using a wide-angle lens.

Key settings:

• Exposure: How long the sensor captures light. Higher = brighter but more motion blur
• Gain: Digital brightness boost. Higher = brighter but noisier
• Lens Correction: Fixes barrel distortion from wide-angle lenses. Enable this now if applicable. Don't skip it
• LED settings (OV10i): Adjust intensity and pattern to reduce glare

Verify before moving on: Click Live Preview. The image should be sharp, well-lit, and consistent shot to shot.

Step 2: Template Image & Alignment

Full guide: Alignment Explained

This is the step most customers find challenging, and the one that makes the biggest difference. The aligner is what makes your inspection regions automatically track your part as it moves around in the image.

The short version:

1. Capture a template image of a good part
2. Place 2-3 small template regions on features that never change (strong edges, corners, holes)
3. Place them as far apart as possible on the part
4. Clean up noisy edges with the Ignore tool
5. Save, then test with Live Preview. Move the part around and verify the alignment tracks it

Read Alignment Explained for the full walkthrough. This is the most important page in this documentation.

Step 3: Inspection Regions (ROIs)

Full guide: Inspection Regions

Now draw the areas where the AI will actually inspect. These are your Regions of Interest (ROIs).

The critical rule: Keep ROIs as small as possible. This is the second biggest source of customer issues. Read Why ROI Size Matters to understand why.

The short version:

1. Create an Inspection Type (e.g., "Screws") with your expected classes (e.g., "present", "absent")
2. Draw rectangular ROIs on each location you want to inspect
3. Make them just big enough to contain the feature, no bigger
4. Name them descriptively (e.g., "Screw_Top_Left")

Step 4: Train Your AI Model

Full guide: Training Your AI

Label a few images and train your first model.

The short version:

1. Start with 3-5 images per class. Don't over-collect
2. Double-check every label before training (one mislabel can ruin your model)
3. Train in Development Mode first (~30 seconds) to check the signal
4. Test with Live Preview. Try to break it
5. Add targeted data where it fails, retrain
6. When development mode works well, switch to Production Mode (5-10 minutes)

Step 5: Output Rules (IO Block)

Full guide: Setting Up Outputs

Define what happens when the AI makes its decision.

Basic Mode: Set rules for pass/fail. The simplest setup: all ROIs must pass for a global pass. That single binary result gets sent to your PLC, HMI, or output.

Advanced Mode (Node-RED): For anything beyond simple pass/fail: custom dashboards, time-series logic, data routing to MES systems, barcode integration, and more. Use tools.overview.ai to generate Node-RED flows from plain English descriptions.

Step 6: Deploy and verify

1. Activate your recipe
2. Set your trigger mode (manual, hardware sensor, PLC, or interval)
3. Run test parts through the system
4. Verify the pass/fail output matches your expectations
5. Check edge cases, the parts that are hardest to classify

Congratulations! You now have a running AI inspection.

Recipe checklist

Before moving on, confirm:

• New recipe created and named
• Image settings configured: sharp, well-lit, consistent
• Alignment set up and tracking reliably
• Inspection regions drawn: small, well-positioned, named
• AI model trained and tested in development mode
• Output rules configured: pass/fail matches expectations
• Recipe activated and deployed with correct trigger mode

What's next?

• Improving Your Model: How to keep your AI getting better over time
• Troubleshooting & FAQ: Common issues and quick fixes