Nutritional Optimization: Recipe Creation for Dietary Restrictions

The prevailing systems exhibit flaws in accurately generating Indian food recipes and there calories and nutritional facts, indicating a notable limitation. To mitigate these flaws, a sophisticated machine learning-powered cooking recipe generator and nutritional fact checker is proposed. This generator prioritizes users diverse dietary preferences and food choices, with a specific focus on Indian cuisine. The primary objectives entail developing a robust machine learning model capable of comprehensively analyzing food images to generate detailed and customized recipes. The goal is to transform culinary experiences to visually impaired by automating recipe creation through the analysis of provided food images. The model assimilate essential additional features to become a comprehensive culinary tool by including nutritional facts alongside recipes. Furthermore, proposed method aims to seamlessly integrate with online video sharing platform YouTube, offering personalized video recommendations to magnify user experiences. Moreover, emphasis is placed on cultural sensitivity by accurately identifying and classifying vegetarian and non-vegetarian dishes. This empowers users to plan their meals ahead. Proposed model has demonstrated an accuracy of nearly 75% compared to existing models ResNet (43%) and Inception v3 (52%), emphasizing its superiority in predicting Indian food recipes.