Deploy Cotton Plant Disease Prediction Application using CNN and Flask

The use of deep learning models to identify lesions on cotton leaves on the premise of images of the crop within the field is proposed in this article. Its cultivation in tropical regions has made it the target of a large spectrum of agricultural pests and diseases, and efficient economical solutions are needed. Moreover, the symptoms of the main pests and diseases cannot be differentiated within the initial stages, and also the correct identification of a lesion can be troublesome for the producer. To help resolve the problem, the present research provides a solution based on deep learning in the screening of cotton leaves that builds it attainable to watch the health of the cotton crop and make higher choices for its management. For this approach, Automatic classifier CNN will be used for classification based on learningwith some training samples of that twocategories. Finally the simulated result shows that used network classifier provides minimum error during training and better accuracy in classification. Keywords: Plant disease, deep learning, CNN, Classification.