Picpan is a computer vision algorithm that recognizes what dish is on the picture (the user snap a picture of a dish and the algorithm recognizes what it is). The idea is to use this capability to output the recipe (and video tutorial) or suggest vegetarian substitutes.
Over the last few years, we have seen an increased focus on health and how to develop healthy (healthier) lifestyles. Encouraging and empowering people to cook at home is the idea underlying this project. PicPan leverages technology to gamify the process of home-cooking and make it seamless, therefore more likely.
Research has shown that food cooked at home (homemade vs. industrially made) was much more nutritious (leading to better health) than food prepared by industrials. Interestingly, those conclusions were confirmed even when controlling for income (poor households that cooked had better nutrition than rich households that didn’t).
To train our model, we used the Food 101 dataset (https://www.vision.ee.ethz.ch/datasets_extra/food-101/): 101,000 pictures of the 101 most cited dish downloaded from foodspotting.com. The beauty of this dataset is that they are real life pictures taken by everyday people. The data fits perfectly with the object of the project.