A LEARNING BASED CLASSIFICATION MODEL FOR VEGETABLES RECOGNITION AND RECIPES RECOMMENDATIONS
Gaurang Solanki, Kartik Mahawar, Piyush Kumar Singh, Puneet Puneet · International Journal of Engineering Applied Sciences and Technology · 2022
This paper presents the building of a classification model using Transfer learning, deployment of the model on the webpage, and recipes Recommendation using web scrapping. First, the vegetable classification model was built using transfer learning on the Pre-trained model MobilenetV2, which was originally trained on the Image Net dataset with 1.4 Million images and 1000 classes of web images. We used this as our base model to train our vegetable dataset and classify the images of 26 different vegetables. Second, the Model was deployed on a webpage using Tensor flow. JS. The model takes an image as input, classifies the image, and gives the vegetable name as output. Images can be taken from the webcam as well as from the storage. Third, based on model outputs, the web scraping script is used to fetch links for top-rated recipes from the internet.