Mango and Banana Dataset (Ripe Unripe)
Description
This dataset of 5000 photos of bananas and mangoes focuses on identifying ripe and unripe fruits. Each photograph has metadata that identifies whether or not the banana in the image is considered ripe. The data set was gathered in indoor as well as outdoor lighting conditions, to identify ripe and unripe Bananas and Mangoes. Each image in this dataset has a YOLO.txt label attached to it. This data can be used to train all YOLO Object Detection models. The dataset has been divided into two sections: Train and Test each of which contains 80% and 20% of the total data. Train folder contains 4000 images with labels and Test folder contains 1000 images with labels. Dimensions of image : 640 x 480
Files
Steps to reproduce
We have manually collected the above data. Using our webcam, we continuously collected photos using the OPENcv Python library. On a few photographs from the collection, we used image augmentation to expand the dataset.