10.21227/EFPT-GC69
Vishal Meshram
Vishal
Meshram
https://orcid.org/0000-0001-9950-584X
Vishwakarma University, India
Panyawat Sakulvilaingam
Panyawat
Sakulvilaingam
Kasetsart University, Thailand
Supawadee Ruangkan
Supawadee
Ruangkan
Kasetsart University, Thailand
Prawit Chumchu
Prawit
Chumchu
Kasetsart University, Thailand
Kailas Patil
Kailas
Patil
https://orcid.org/0000-0002-1046-9860
Vishwakarma University, India
Top Indian Fruits with quality
IEEE DataPort
2020
Artificial Intelligence
Computer Vision
Machine Learning
convolutional neural network
computer vision
Deep Learning
fruit classification
Machine Learning
2020-07-08
Open Access Dataset
Creative Commons Attribution
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. The main objectives to create this dataset were: 1) Target the top Indian fruits which are exported or highly consumed. 2) Create a dataset for fruit classification with the quality of fruit. 3) Dataset consists of high-quality images.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.