Several Dishes Recognition

Learn more about how to preprocess your images in our Image Pre-processing Tutorial page.

Plan & Token Requirements

Feature available in the following LogMeal Plans:

Accessible by the following User Types:

What It Does

Several Dishes Recognition analyzes an image containing multiple foods (like a meal with multiple items in multiple plates, beverages and any type of food container) and splits it into distinct dish regions.
Each region is then classified with dish-level predictions, food types and food groups.

Whan submitting a meal with this feature its nutritional details will be associated with the user profile performing the request, which will allow building an image-based food diary.

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When to Use It / Outcomes

• You have meal images with more than one dish (e.g., main + sides + drinks).
• You want to separate portions for better tracking, analysis, or dietary reporting.
• You want to submit a new intake for a food diary for being able to analyse the ingredients, quantities and nutrition for the meal later on.
• Output: JSON containing:
  • Bounding boxes and segments/regions for each detected dish region
  • Predictions (dish labels, probability scores)
  • Food type per dish
  • Food groups per dish

Feature-Specific Details

• The system uses image segmentation to identify multiple items.
• Each dish is independently classified as a separate food item.
• Results include dish names, confidence scores, associated food type and associated food groups.
• Can be combined with Ingredients Analysis and Nutritional Analysis for downstream insights.

Related Endpoints

Use the following endpoint for multi-dish recognition:

• POST /image/segmentation/complete → 🔴 Performs dish segmentation and returns all dishes detected with predictions and groups.

Remember to check applicable request limitations inside each of the endpoints. These endpoints are available to 🔴 APIUser tokens and are included in Analyse plans or above.

Related Use Cases

Copy-Paste Recipes

Set profile data once to improve label language and regional dishes:

Send the image to segmentation to obtain regions and top dish candidates per region. Display the top 5 candidate dishes and ask the user for confirmation: