Style Transfer – Real-Time Food Category Changer
One interesting project I came across on the internet involving machine learning and artificial intelligence is called “Real-time Food Category Change”. It is a food style transfer project lead by Ryosuke Tanno and presented at the European Conference for Computer Vision in 2018. The idea of is nothing grandiose, it simply allows users to change the “appearance of a given food photo according to the given category [among ten typical Japanese Food].” For example, you can transfer a bowl of ramen noodle to curry rice by exchanging the texture while still preserving the shape.
Here are some sample image results:
More at: https://negi111111.github.io/FoodTransferProjectHP/
The results are achieved by using a Conditional Cycle GAN on a colossal food image database. 230,000 food images were collected from Twitter stream which were grouped into 10 categories for image transformation. The algorithm – Conditional Cycle GAN is an extension of CycleGAN with the addition of some conditional inputs. This modification is necessary to overcome CycleGAN’s disadvantage on only learning image transformation between two fixed paired domains. More algorithmic method and technical considerations can be found in this paper: Magical Rice Bowl: A Real-time Food Changer.
As someone who enjoys taking photos and eating food, I personally found this implementation to be a lot of fun. Additionally, the fact that such food image transformation can be done in real time on both smartphones as well as PCs is quite impressive. There are even practical future applications of this idea which is to combine this with virtual reality to unlock new eating experience. An example would be if people are on diet and try to restrict high-calorie food intakes, they can eat low-calorie foods in reality while still enjoying high-calorie foods in their VR glasses.