PSFD-Musa DATASET
Description
Three dataset folders are presented here that include the Banana variety, Banana Disease, and Banana Deficiency. The dataset of "banana variety" consists of 7 classes (namely: Malbhog fruit (Musa assamica), Malbhog leaf (Musa assamica), Jahaji fruit (Musa chinensis), Jahaji stem (Musa chinensis), Jahaji leaf (Musa chinensis), Kachkol fruit (Musa paradisiaca L.), Bhimkol leaf (M. Balbisiana Colla)). The dataset of "banana disease" consists of 7 classes (namely: Bacterial Soft Rot, Banana Fruit Scarring Beetle, Black Sigatoka, Yellow Sigatoka, Panama disease, Banana Aphids, and PseudoStem Weevil). The dataset of "banana deficiency" consists of 1 class (namely: Potassium deficiency). The images are resized into 256 x 256 dimensions using Python OpenCV programming. As the raw image data are very less, therefore we have augmented it and now the dataset consists of about 8000+ image data. The augmentation is performed using Python programming. All the images are in RGB and .jpg format.
Files
Steps to reproduce
1) Raw image data were collected from the Banana plantation of Assam in India. 2) Image data were acquired using a mobile phone camera and a digital camera. 3) The data were collected under average sunlight. 4) The data are in RGB and .jpg format. 5) Different varieties of the Banana plant are separated with respect to its Stem, Leaf, and Fruit. 6) Different diseases of the Banana plant are categorized and kept in different folders. 7) The images are resized into 256 x 256 dimensions using Python OpenCV programming. 8) As the raw image data are very less, therefore we have augmented it and now the dataset consists of about 8000+ image data. The augmentation is performed using Python programming. 9) The dataset can be really helpful to researchers for scientific modeling.