Prediction of Guava Plant Diseases Using Deep Learning

Abstract

Plant pathology is a field which deals with the analysis, diagnosis and treatment of diseases in plants. These days agriculture is the main source of income in the Indian economy as well as important for livelihood. Identification of diseases in plants and crops are quite difficult unless someone have great knowledge and experience. Diseases in plants might cause severe damage to whole crop that leads to loss of income for farmers and results in descend of revenue for agriculture in Indian economy, if not identified and controlled forefront. Early prediction can help this situation. This documentation represents the prediction of plant diseases using images of the leaves that are given as input by the user and predicts the type of disease. In background we have used convolution neural network algorithm followed by image classification and deep learning techniques. The accuracy is obtained with the help of confusion matrix. The algorithm is implemented using Python language which uses Flask as the micro web framework for graphical user interface (GUI). User gives the input image and the predicted disease is printed.