Crafting Culinary Adventures
with Image-Driven Recipe Generation!
Tech: Machine Learning, Deep Learning, Neural Networks, Computer Vision, App Development
The primary objective of our project is to develop a cutting-edge recipe recommendation system that harnesses the potential of deep learning and natural language processing using machine learning technologies. Our innovative system is crafted explicitly for the culinary landscape, catering to individuals who desire tailored and visually captivating recipe recommendations. By seamlessly incorporating advanced image recognition, our goal is to create a user-friendly platform that not only suggests recipes based on user preferences but also addresses the issue of food waste.
Through visual analysis of raw materials, our system takes a proactive approach to minimizing food waste by providing recommendations that align precisely with users' specific preferences and dietary requirements. This not only enhances the user experience by offering more accurate and customized culinary suggestions but also contributes to sustainability efforts in reducing unnecessary food waste. As users engage with our platform, they not only discover delightful recipes but also effectively take part in a more sustainable approach to cooking and consumption.Through this project, we plan on extracting features from the available images using Convolutional Neural Networks algorithms like Alexnet or VGG16. Simultaneously, the feature extraction from the listed recipe dataset will be done by using term-extract or topic modeling using natural language processing packages like NLTK, Spacy, and gensim models. This will be followed by appropriate image classification models to identify objects in the picture. We finally plan on combining results from the above models to create a recommendation system that takes images as input and provides corresponding recipes as output.
.png)
Follow this GitHub Repository Link to learn about the process in detail!