We have prepared a model to classify image of tomato leaf based on their moisture content in plant which then predict the moisture content in any tomato plant and provide recommendation based on the optimum criteria obtained from primary data to provide maximum productivity. We have deployed the final model as a web application using flask .
MobileNetV2 is used as a pretrained model to train images.
This project can be applied to determine the moisture content in the tomato plant and predicts the probable production.