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AI Services for Culinergy

Setup

Installation dependencies

pip install -r requirements.txt

Start flask server

python app.py

Start docker:

sudo docker-compose up

API Docs

Server Usage:

  1. Ingredient Detection:

    • Method: POST

    • URL: http://127.0.0.1:5000/detect/

    • Example input: base64 encoding of this image in key-value format.

      Example input image

      { "image": "/9j/4...5//Z" }
    • Example output: id with base64 encoding of cropped ingredient images. id=-1 mean the original image with bounding box of detected ingredients.

       [
          {
             "ingredient_id": -1,
             "image": "/9j/4...5//Z"
          },
          {
             "ingredient_id": 1789,
             "image": "/9j/4...2P/Z"
          },
          {
             "ingredient_id": 1789,
             "image": "/9j/4...2Q=="
          },
          {
             "ingredient_id": 2478,
             "image": "/9j/4...2Q=="
          }
       ]
  2. Food Recommendation:

    • Method: POST

    • URL: http://127.0.0.1:5000/recommend/

    • Example input: 1789 (Cheese), 2478 (Corn)

      { "ingredient_ids": [1789, 2478] }
    • Example output:

      {"food_ids": [8756, 9718, 2728, ... , 1189, 1418]}

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