Real-time-plant-disease-detection-system

This Deep learning project uses real time data to categorise image as diseased or not diseased using CNN. The image dataset can be found out from the link here: https://www.kaggle.com/emmarex/plantdisease with a modification of categorising them into 2 main groups:

1. Diseased
2. Normal

70% of the images of each category is for training the model under the TRAIN folder 30% of the remaining images of each category is for validating the model unser the VALIDATION folder The TEST folder contains images that is not seen by the model and is the real-time image that is given using either WEBCAM or via mobile The webcam is to be operated as follows:

1. For taking pictures, press the 'SPACE bar' successively
2. when all the pictures are taken, press the 'ESC' key to continue with the model prediction