Yield infections are a significant danger to food security, but its recognizable proof is troublesome because of absence of foundation. This paper presents a survey of different image processing and deep learning techniques used in the identification of plant disease based on images of disease infected plants. Distinguishing and recognizing infection from the plants pictures is one of the fascinating examination territories in PC and agribusiness field. The performance of cnn is the powerful tool to diagnose and predict the infections. The principal objective of the undertaking is to assist farmers with recognizing the illness and to forestall the plant in early stage. Plant sickness is the acknowledgement model, in a view of leaf picture arrangement, created utilizing convolutional neural networks (CNN).The created model perceives 7 distinct sorts of plant illness. The prepared model accomplishes a 99.15%of accuracy. Keywords: Deep learning, predict, image processing, convolutional neural networks.



Software And Hardware

• Hardware: Processor: i3 ,i5 RAM: 4GB Hard disk: 16 GB • Software: operating System : Windws2000/XP/7/8/10 Anaconda,jupyter,spyder,flask Frontend :-python Backend:- MYSQL