Recipe Recommendation Using Image Classification

As the digital era develops, smart food technologies are more in demand because they make meal planning and preparation simpler and more enjoyable. Recipe recommendation systems have become widespread in order to provide clients with customized recipe recommendations based on their dietary preferences, level of cooking proficiency, and availability of ingredients. On the other hand, the majority of recipe recommendation systems rely on textual inputs or pre-defined categories of ingredients, which might not accurately reflect what the user has in their pantry. This research study proposes a recipe suggestion system based on user-provided images of readily available ingredients that combine image recognition and convolutional neural networks (CNNs). It will recommend recipes based on the image provided. This will make finding recipes more quick and simple than it would otherwise be. In this instance, text-to-speech guided technology is used so that the user can just replay the procedure as needed rather than reading it repeatedly. This research work will include additional elements like redirecting to a grocery cart by clicking a link. This concept will be very helpful to those who don't know what to cook. Thanks to this initiative, users won't have to waste time thinking about the recipes.