JujubeImageBD: A Comphrehensive Image Dataset of Jujubes Varieties in Bangladesh for Identification and Classification Using Machine Learning and Computer Vision

Type of data: 1024 x 1024 px images of jujubes.
Data format: JEPG.

Dataset contents: Original images of different varieties of jujubes in Bangladesh from single-fruit perspective.

Number of classes: Five jujube varieties - (1) Apple Kul, (2) Ball Sundari Kul, (3) Bau Kul, (4) Deshi Kul, and (5) Narkeli Kul.

Total number of images in the dataset: (A) In Original Dataset = 1,716 images and (B) In Augmented Dataset = 17,160 images.

Distribution of instances:
(A) Number of images in Original Dataset (Jujube Dataset):
(1) Apple Kul = 289.
(2) Ball Sundari Kul = 303.
(3) Bau Kul = 356.
(4) Deshi Kul = 356.
(5) Narkeli Kul = 412.

(B) Number of images in Augmented Dataset (Augmented Jujube Dataset):
(1) Apple Kul = 2,890.
(2) Ball Sundari Kul = 3,030.
(3) Bau Kul = 3,560.
(4) Deshi Kul = 3,560.
(5) Narkeli Kul = 4,120.

Dataset size: (A) Total size of the Original Dataset is 41.7 MB and the compressed ZIP file size is 39.6 MB. (B) Total size of the Augmented Dataset is 1.2 GB and the compressed ZIP file size is 1.11 GB.

Data acquisition process: Images of jujube are captured using a high-definition smartphone camera from different angles.

Data source location: Local wholesale and retail fruit markets located in different areas of Dhaka, Bangladesh.

Where applicable: Training and evaluating machine learning and deep learning models to distinguish jujube varieties in Bangladesh to support automated identification and classification systems of various jujube varieties which can be utilized in areas of computer vision, smart agriculture and horticulture, precision farming, supply chain automation, food industry, AI-based fruit recognition, ecology and ecosystem health monitoring, biodiversity efforts, botanical research, environmental conservation, educational resources, ecology research.