The MIT team’s pic2recipe system uses neural networks to determine the recipe of a given food, in an attempt to gain “valuable insight into health habits and dietary preferences,” based on images of food pulled from social media.pic2recipe was built using the Food-101 Data Set, a food-identifying algorithm built by Swiss scientists in 2014, using a database of 101,000 food images. That information is cross-referenced with the CSAIL team’s own Recipe1M database of one million recipes pulled from popular sites like All Recipes and Food.com.
The system is not 100% perfect yet because one of the main problem is the images.Speaking to the TechCrunch “It’s mostly an issue of getting the scale correct,” coauthor Nick Hynes told TechCrunch. “When people take pictures of food, there’s a lot of variation in style: whether taken from close up or far away; whether it’s of the single item, multiples, part of a complete dish. Of course, that’s not unreasonable, since even a human might think that a single cookie is a pancake when zoomed out.”
Lets see how successful it is because we can trust the product designed by MIT like there research’s did before.This is the system very helpful for the users when one wants to customize its recipe by adding his/her most wanted ingredients and get a full recipe in front of the table.