A dataset of bee on blooming sunflower images for object detection

Published: 3 March 2021| Version 1 | DOI: 10.17632/wzyhfbtf8s.1


The dataset is composed of 91 images of bees on sunflowers. The photos were taken in the new community of Taichung City, Taiwan from 3:35 to 3:40 pm on Monday, November 04, 2019 with the iPhone XR mobile phone. The image after shooting is 1478*1108 pixels and the format is .jpg file. In order to train the model more effectively, we use multi-angle rotation to perform data enhancement and expand the number of data sets to three times of the original. Use Matlab to manually mark the region of interest in the image, a total of 412 annotations, and the annotation image is saved in a .mat file.


Steps to reproduce

Step 1: Collect the images of the data set, mainly based on 91 images taken by ourselves. Step 2: Do data enhancement based on the collected image. Rotate the image at three angles of 90 degrees, 180 degrees, and 270 degrees to expand the data set by three times, a total of 364 images. Step 3: Manually mark the region of interest annotations with Image Labeler in Matlab, which corresponds to 412 annotations. Finally, the marked images are input into the model for training and testing.


Image Analysis