ColoredFlowersBD: A Comphrehensive Image Dataset of Colored Flowers in Bangladesh for Identification and Classification Using Machine Learning and Computer Vision

Published: 18 February 2025| Version 1 | DOI: 10.17632/d22kghy9xb.1
Contributors:
Md Hasanul Ferdaus,
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Description

Type of data: 720 x 720 px images of colored flowers. Data format: JEPG Dataset contents: Original images of different varieties of colored flowers in Bangladesh from single flower and bulk-flower perspectives. Number of classes: Thirteen colored flower varieties - (1) Chandramallika, (2) Cosmos Phul, (3) Gada, (4) Golap, (5) Jaba, (6) Kagoj Phul, (7) Noyontara, (8) Radhachura, (9) Rangan, (10) Salvia, (11) Sandhyamani, (12) Surjomukhi, and (13) Zinnia. Total number of images in the dataset: 7,993. Distribution of instances: (1) Chandramallika = 620 images in total. Single = 306, Bulk = 314. (2) Cosmos Phul = 620 images in total. Single = 307, Bulk = 313. (3) Gada = 617 images in total. Single = 304, Bulk = 313. (4) Golap = 605 images in total. Single = 302, Bulk = 303. (5) Jaba = 604 images in total. Single = 300, Bulk = 304. (6) Kagoj Phul = 612 images in total. Single = 301, Bulk = 311. (7) Noyontara = 609 images in total. Single = 303, Bulk = 306. (8) Radhachura = 617 images in total. Single = 309, Bulk = 308. (9) Rangan = 606 images in total. Single = 305, Bulk = 301. (10) Salvia = 634 images in total. Single = 313, Bulk = 321. (11) Sandhyamani = 615 images in total. Single = 305, Bulk = 310. (12) Surjomukhi = 621 images in total. Single = 310, Bulk = 311. (13) Zinnia = 613 images in total. Single = 307, Bulk = 306. Dataset size: The total size of the dataset is 2.79 GB and the compressed ZIP file size is 2.71 GB. Data acquisition process: Images of colored flowers are captured using a high-definition smartphone camera from different angles and two perspectives: single-flower and bulk-flower. Data source location: Plant nurseries, local gardens, and flower shops located in different areas of Dhaka and Gazipur districts of Bangladesh. Where applicable: Training and evaluating machine learning and deep learning models to distinguish colored flower varieties in Bangladesh to support automated identification and classification systems of various colored flowers which can be utilized in areas of computer vision, botanical research, floral biodiversity monitoring, agriculture and horticulture, environmental conservation, AI-based flower recognition, educational resources, food industry, pollination and ecology research, aesthetic and design applications.

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Institutions

East West University, Bangladesh Ministry of Agriculture

Categories

Chemistry, Biochemistry, Ecology, Pharmacology, Horticulture, Computer Vision, Environmental Science, Plant Biology, Botany, Image Processing, Pharmaceutical Science, Object Detection, Machine Learning, Biodiversity, Image Classification, Pharmaceutical Industry, Medicinal and Aromatic Plants, Flower, Beverage Industry, Food Industry, Deep Learning, Crafts (Arts), Agriculture

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