Originally published in Synced, June 20, 2019
Imagine snapping a pic of your tasty restaurant entree or the magnificent lasagna in a foodie post, and up pops a recipe for said dish. Facebook AI has now transformed that gourmand’s fantasy into reality.
Facebook’s AI’s new “Inverse Cooking” AI system reverse-engineers recipes from food images, predicting both the ingredients in the dish and their preparation and cooking instructions. The technique improves on former ingredient prediction baselines with the large-scale Recipe1M data set; and Facebook says the recipes are more accurate than traditional retrieval-based approaches.
The image-to-recipe system recognizes individual ingredients and infers what happened to them on the way to the plate. It predicts the ingredients by extracting visual features from the input image and ingredient co-occurrences. Researchers first pretrain an image encoder and an ingredients decoder to predict ingredients, then train the system to produce dish title, preparation and cooking instructions. Prediction and model generation is the final step, where the system feeds predicted ingredients into an advanced sequence generation model to come up with a recipe.