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feat: add PantryChef MVP with Roboflow inference and GPT-4o-mini reci… - #28

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feat: add PantryChef MVP with Roboflow inference and GPT-4o-mini reci…#28
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@supriyavikramsingh-sudo supriyavikramsingh-sudo commented Jun 9, 2026

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…pe generation

  • Express backend with /api/detect (Roboflow) and /api/recipes (OpenAI) endpoints
  • React/Vite frontend with image upload, canvas bounding box overlay, ingredient chips, recipe cards
  • Integrated james-elcock/fridge-detection-ojugs/6 (77 classes, mAP 82.9%) after evaluating and rejecting deluxeviper/fridge-ingredients/2 (apple-dominated dataset)
  • Confidence threshold at 0.35 with deduplication by class before chip render and recipe API call
  • Upgraded multer to 2.x (CVE fix from 1.x)
  • Bounding box scaling uses naturalWidth/clientWidth ratio for correct canvas alignment
  • Recipe card splitting anchored on "estimated cook time" phrase to avoid GPT markdown variance
  • API keys in server/.env, gitignored
  • add detection and recipe images to assets

Model evaluation findings documented in README

What does this PR do?

Related Issue(s):

Type of Change

  • Bug fix (non-breaking change that fixes an issue)
  • New feature (non-breaking change that adds functionality)
  • Breaking change (fix or feature that would cause existing functionality to not work as expected)
  • Documentation update
  • Refactoring (no functional changes)
  • Other:

Testing

  • I have tested this change locally
  • I have added/updated tests for this change

Test details:

Checklist

  • My code follows the style guidelines of this project
  • I have performed a self-review of my own code
  • I have commented my code where necessary, particularly in hard-to-understand areas
  • My changes generate no new warnings or errors
  • I have updated the documentation accordingly (if applicable)

Additional Context

…pe generation

- Express backend with /api/detect (Roboflow) and /api/recipes (OpenAI) endpoints
- React/Vite frontend with image upload, canvas bounding box overlay, ingredient chips, recipe cards
- Integrated james-elcock/fridge-detection-ojugs/6 (77 classes, mAP 82.9%) after evaluating and rejecting deluxeviper/fridge-ingredients/2 (apple-dominated dataset)
- Confidence threshold at 0.35 with deduplication by class before chip render and recipe API call
- Upgraded multer to 2.x (CVE fix from 1.x)
- Bounding box scaling uses naturalWidth/clientWidth ratio for correct canvas alignment
- Recipe card splitting anchored on "estimated cook time" phrase to avoid GPT markdown variance
- API keys in server/.env, gitignored
- add detection and recipe images to assets

Model evaluation findings documented in README
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socket-security Bot commented Jun 9, 2026

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