https://ieee-dataport.org/open-access/fruitsgb-top-indian-fruits-quality

Image Processing ,  Computer Vision ,  Artificial Intelligence ,  Machine Learning

INDIA is the second-largest fruit and vegetable exporter in the world after China. It ranked first in the production of Bananas, Papayas, and Mangoes. Public datasets of fruits are available but they are limited to general fruit classes and failed to classify the fruits according to the fruit quality. To overcome this problem, we have created a dataset named FruitsGB (Fruits Good/Bad) dataset. The main objectives to create this dataset were: 1) Target the top six Indian fruits which are exported or highly consumed. 2) Create a dataset for fruit classification with the quality of fruit. 3) Dataset consists of 12000 high-quality images of 12 different classes of fruits. We use mobile phones rear camera to take the images of fruits. The dataset consists of total 12000 images with 12 classes namely, Bad Apple, Good Apple, Bad Banana, Good Banana, Bad Guava, Good Guava, Bad Lime, Good Lime, Bad Orange, Good Orange, Bad Pomegranate, and Good Pomegranate. In the dataset, each class consists of 1000 images of size 256x256. The images had taken with different angles, with different backgrounds, and in different lighting conditions. As we considered the most consumed fruits this dataset is very useful for researchers. Instructions: The data set contains 12 classes of fruits namely Bad Apple, Good Apple, Bad Banana, Good Banana, Bad Guava, Good Guava, Bad Lime, Good Lime, Bad Orange, Good Orange, Bad Pomegranate, and Good Pomegranate.

Country Applicable

India

Target Audience

Researchers Data Analyst Image Processing Specialist

Authors/Contributors

Vishal Meshram Koravat Thanomliang Supawadee Ruangkan Prawit Chumchu Kailas Patil