An Extensive Image Dataset for Classifying Rice Varieties in Bangladesh

Published: 3 June 2024| Version 1 | DOI: 10.17632/2fgv99854n.1
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Description

This dataset contains a carefully collected set of low-resolution images of 38 well-known rice varieties from BINA and IRRI. It helps in identifying the unique features of these rice types for accurate classification. #Dataset Composition# The dataset includes images of 38 different types of rice, specifically: BD33, BD30, BD39, BD56, BD93, BD91, BD49, BD51, BD52, BD76, BD95, BD57, BD87, BD70, BD85, BD72, BD79, BD75, Binadhan7, Binadhan8, Binadhan10, Binadhan11, Binadhan12, Binadhan14, Binadhan16, Binadhan17, Binadhan19, Binadhan20, Binadhan21, Binadhan23, Binadhan24, Binadhan25, Binadhan26, BR22, BR23, BRRI67, BRRI74, and BRRI102. There are 19,000 original JPG images and 76,000 augmented images in total. #Image Capture and Dataset Organization# Images were taken using high-power 1600x and 1000x digital microscope cameras between January 15 and February 28, 2024. The dataset is divided into two main parts: Original images and Augmented images. Each part has 38 folders, one for each rice variety. #Original Image Dataset# The main set includes 19,000 JPG images, each sized at 640x480 pixels. The uncompressed file size is 1.52 GB, reduced to 1.47 GB after compression. #Augmented Image Dataset# To increase the number of images for deep learning models, data augmentation techniques were used. These include rotations (90° left, 90° right, 180°), shear range and flips, creating 76,000 more images. These images are also in JPG format, sized at 640x480 pixels, and were initially 1.98 GB, reduced to 1.89 GB after compression. #Dataset Storage and Access# The raw and augmented datasets are stored in two separate zip files, 'Original.zip' and 'Augmented.zip'. Each zip file contains 38 folders, one for each rice variety mentioned above.

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Institutions

East West University

Categories

Computer Vision, Image Processing, Machine Learning, Rice, Image Classification, Deep Learning

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