Strawberry-DS

- An annotated benchmark image dataset for training and validation of strawberry ripeness detection systems based on Machine learning (ML) and, Deep Learning (DL).
- 247 Raw RGB digital images (.jpg) of strawberry fruits were taken in an orchard of the Central Laboratory for Agricultural Climate (CLAC), Agricultural Research Center, Cairo - Egypt.
-The images have been captured from the fruit top view considering different view angles using Sony Xperia Z2 LTE-A D6503 smartphone 20.7 MP camera with a CMOS sensor system and resolution of 3840 x 2160 pixels (Mpix).
The dataset images, which contain both fully-visible strawberry fruits and partially-visible strawberry fruits concealed by leaves or by other fruits, were manually annotated, using Roboflow Annotate annotation tool. The data formats of files in Strawberry-DS dataset are RGB digital images (.jpg) and their corresponding YOLO format (.txt) annotation files.

一项针对基于机器学习（ML）和深度学习（DL）的草莓成熟度检测系统训练与验证的标注基准图像数据集。该数据集包含247张草莓果实的原始RGB数字图像（.jpg），这些图像在开罗埃及农业气候中心（CLAC）的果园中拍摄。图像从草莓顶部视角以不同视角捕捉，使用搭载CMOS传感器系统、分辨率为3840 x 2160像素（Mpix）的索尼Xperia Z2 LTE-A D6503智能手机20.7 MP相机拍摄。数据集中的图像既包括完全可见的草莓果实，也包括被叶子或其他果实部分遮挡的草莓果实，均经过人工标注，使用Roboflow Annotate标注工具进行。Strawberry-DS数据集中的文件数据格式为RGB数字图像（.jpg）及其对应的YOLO格式（.txt）标注文件。