Evaluate OMR answer sheets with Gemini vision AI and Google Sheets

✅ What problem does this workflow solve?

Manual checking of OMR (Optical Mark Recognition) answer sheets is time-consuming, error-prone, and difficult to scale—especially for schools, coaching institutes, and exam centers. This workflow automates OMR evaluation end-to-end using AI, from reading a scanned answer sheet image to calculating scores and storing structured results in Google Sheets.

---

⚙️ What does this workflow do?

1. Accepts a scanned OMR answer sheet image via webhook. 2. Uses AI vision to extract only the marked answers from the sheet. 3. Extracts basic student details (Name, Roll Number, Class). 4. Compares extracted answers with a predefined answer key. 5. Calculates: - Total questions - Correct answers - Incorrect answers - Score percentage 6. Generates question-wise binary results (1 = correct, 0 = incorrect). 7. Stores the complete result in Google Sheets. 8. Returns a structured JSON response to the calling system.

---

🧠 How It Works – Step by Step

1. 📥 Webhook Trigger (Student OMR Upload) - A client uploads the OMR image via a POST request. - Image is received as form-data (key: file).