Count Unique Apple Colors in a Photo with Revdoku
Count Unique Apple Colors in a Photo with Revdoku
Step 1: Open the apple photo in Revdoku.
The 12-apples.png file is open in the viewer — a grid of 12 apples (green, yellow, red, variegated) photographed top-down on a wooden surface. The checklist banner reads Apple Detection and Color Analysis. Click the purple Review button in the top-right to start.

Step 2: Write the apple color checklist rule.
In the checklist editor, paste a one-line rule that tells Revdoku to detect every apple in the image, analyze its surface area for the dominant color, and save the check value as one of Red, Green, Yellow, or Variegated for each apple. Click Save Changes.

Step 3: Run the review.
Back in the Review Envelope dialog, confirm the Apple Detection and Color Analysis checklist is selected, leave the AI model on Google Gemini Standard US, and click Run Review. Revdoku walks through Preparing, Analyzing, Reviewing, and Finalizing on the single image page.

Step 4: Read the per-apple color breakdown.
All 12 checks pass at 100% compliance. Every apple is outlined with a green region and tagged with its color value — four variegated apples, three red, three yellow, and two green — each linked to the matching apple in the photo.

Step 5: Open the envelope script editor.
Click the more menu in the top-right of the envelope and pick Edit Script. In the Edit Envelope Script dialog, open the Sample Scripts dropdown and pick Group by category and sum — it parses each check’s color value, groups by color, and sums how many apples fell into each group. Click Save.

Step 6: Read the computed per-color totals.
The script output lists every color with its count — Green 2, Red 3, Variegated 4, Yellow 3 — plus a Total of 12 apples at the bottom. The photo below shows the same 12 checks outlined in green for easy verification.

What You Learned
This case showed how Revdoku can take a document, apply a structured checklist, and surface specific findings — all in under a minute. No manual line-by-line reading required.
Disclosure: Sample documents in this use case were generated using AI and contain intentional errors for demonstration purposes. All names, companies, and details are fictional.
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