We have collected the Papaya image dataset by a survey. We created a form and for filling the form papaya images are stored in our google drive then we use the best quality images and it is all about 234images. Now, 184images are for training where disease images are 150 and fresh images are 34, the validation we have used 19images are disease and 9images are for fresh images, and for testing we have used 22images of papaya.
There are different types of image data and we know that Convolutional Neural Network (CNN) doesn’t work on different types of image data. So we converted all the image data into a single size as 200x200 as target_size and we also fixed the input size as 200x200 when we buildup CNN model.
- There are differents types of sopt are counted as disease and that's are
(i) Black Spot,
(ii) Brown Spot
- There are differents types of blight are counted as disease and that's are
(i) Phytophthora,
(ii) Anthracnose