Mango Disease Classification using CNN

Mango is a profitable agricultural product and widely consumed fruit. Mango production is significantly reduced when disease attacks the plant, which makes it difficult for farmers to sell their harvest. This issue drove us to create innovative methods for identifying diseases that damage mango plants. In order to maximise output and quality, it is imperative to stop these dangerous diseases early on. in our nation most many farmers lack literacy. They are unable to find correct information about illnesses as a result. It needs a knowledgeable advisor or agriculture officer. But reaching every farmer can be difficult for a professional counsellor or agricultural authority. So, in this project we are suggesting a trained model that will identify the disease of any mango plant by just providing its picture to the model. We have used Convolutional Neural Networks (CNN) to classify the images and we have trained the model on 4000 images and 8 different diseases. Accuracy of the model is around 98% and is giving accurate results.