Several Dishes Recognition

Recognize which dishes or food items are present in an image. LogMeal's Food API is capable of identifying more than 1300 different local and international dishes from cuisines all around the world.

Moreover, our AI models are continuously learning, as we incorporate new dishes and food items daily to enhance food recognition and tracking performance.

[New] Personalized Recognition using Historical Intakes

Boost accuracy by tailoring predictions to each end‑user. LogMeal gently adjusts the probability of each dish based on that user’s confirmed eating history and by meal occasion (e.g., breakfast, lunch, dinner).

Feature available in the following LogMeal Plans:

Analyse
Monitor
Recommend
Custom

LogMeal API is the most advanced AI and Deep Learning API in the world for AI Food Detection, Recognition & Tracking. It is capable of providing nutritional information about a meal by simply taking a picture.

Whether you're eating at a restaurant or at home, it is common to have different dishes in your meal. Thanks to food segmentation, just by taking a single photo, the LogMeal algorithm will recognize the dishes individually and provide their nutritional information.

The total number of dishes currently available for recognition are more than 1300. They are different local and international dishes from any cuisine around the world.

Given an image, it segments and detects each food item or food region appearing on it. Then the most probable dishes are recognized for each of the regions separately. Thanks to this functionality, it is possible to obtain the nutritional information from an entire menu all at once (including beverages and desserts).

Personalized Recognition using Historical Intakes - How personalization works

  1. Your users capture a meal and confirm the detected dishes.
  2. LogMeal remembers confirmed items (per occasion) and builds a frequency profile.
  3. On future meal reports, that profile subtly boosts likely dishes for faster, more accurate results.

Tip: keep collecting confirmations to get the best experience. If there’s not enough history, recognition falls back to the standard visual model automatically.

several dishes recognition multilabel combination dish dutch food
several dishes recognition multilabel combination dish hummus

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