STEM_DETECTION_DATASET

The stem detection dataset includes RGB images that were collected specifically for training and validation of stem detection algorithms. There are a total of 573 RGB images, 508 of which were used for training and 65 for validation. These images were taken with an Intel Realsense D435 camera positioned at a variable distance of 20 to 50 centimeters from the grapes. The images' resolution is set to 1920 x 1080 pixels, resulting in a detailed and comprehensive visual dataset for the development and evaluation of stem detection algorithms.  All of the data were collected at Ktima Gerovassiliou in Epanomi, Thessaloniki.

Below, there are three separate folders with the training data (which can be merged into one) and one folder containing the validation data. Every image has a txt file containing the image's stem annotations. The first number represents the annotation's class (0 for stem), and the remaining numbers are the normalized (in the image's shape) coordinates of the stem's mask.

本茎秆检测数据集包含专为茎秆检测算法训练与验证采集的RGB图像。数据集共计573张RGB图像，其中508张用于训练，65张用于验证。所有图像均由Intel Realsense D435相机拍摄，相机与葡萄的拍摄距离在20至50厘米范围内可变。图像分辨率设定为1920×1080像素，由此构建了一套细节丰富、覆盖全面的视觉数据集，可用于茎秆检测算法的开发与评估。所有数据均采集自塞萨洛尼基市埃帕诺米镇的Ktima Gerovassiliou酒庄。

数据集包含三个独立的训练数据文件夹（可合并为一个）以及一个验证数据文件夹。每张图像均对应一个存储了该图像茎秆标注信息的txt文件：文件首个数字代表标注类别（0代表茎秆），其余数字为该茎秆掩码基于图像尺寸归一化后的坐标值。