CNN Model which classifies pomegranate based on leaves images into one of the three categories namely BACTERIAL, FUNGAL or HEALTHY.
We are given the dataset having 238 images consisting of three folders - i) 88 Healthy images ii) 46 Fungal infected images iii) 104 Bacterially infected images We are supposed to build a model and train it on this dataset in such a way that given a new image of a leaf, the model should classify it into one of the three categories.
CNN Model development phases Step-1 Data pre-processing Step-2 Train test and validation split Step-3 Building the model Step-4 Training the model Step-5 Testing the model