LogMeal is a company specializing in food recognition technology. They offer an API that can detect over 1300 different dishes using the largest food image dataset in the world. Their team has over 30 years of experience in computer vision and has been developing Deep Learning algorithms for over 7 years. Their solutions have been applied in various contexts, including food tracking for the elderly, medical solutions for nutrition estimation for diabetes or renal disease patients, and autonomous checkout devices for self-service restaurants. The API provides semantic tagging, including food group, dish, and ingredients recognition, as well as nutritional information analysis. It can detect prepared food, drinks, fresh vegetables and fruit, non-food items, and basic food groups. It can also recognize and list all food items present in a picture, extract the list of ingredients and their quantities, and provide an ingredients-based nutritional analysis of the picture. The API is available for free with limited usage during a trial period, and users can upgrade to paid plans for more features and usage.
⚡Top 5 LogMeal Features:
Feature 1: Over 1300 different dishes detection using the biggest food image dataset in the world.
Feature 2: Published 25 international papers about food recognition.
Feature 3: 30 years of experience in computer vision in both industrial and academic sectors.
Feature 4: Developing Deep Learning algorithms for over 7 years.
Feature 5: Applied on several projects and contexts, including food tracking for the elderly and medical solutions for diabetes or renal disease patients.
⚡Top 5 LogMeal Use Cases:
Use Case 1: Food tracking for the elderly or people who want to follow a healthy lifestyle.
Use Case 2: Medical solutions like nutrition estimation for diabetes or renal disease patients.
Use Case 3: Autonomous checkout devices for self-service restaurants.
Use Case 4: Ingredients Information Extraction for food logging solutions.
Use Case 5: Food detection based on images with semantic tagging including food group, dish, and ingredients recognition, as well as nutritional information analysis.
