GRAPE_DETECTION_DATASET

The dataset consists of three distinct groups of RGB images, each designed for training and validation purposes. The groups were separated based on the camera sensor used to collect the data. The first set contains 151 images, with 101 for training and 50 for validation. The first group is contained in the C1 folder. These images were taken with a ZED Mini camera held by hand at a constant distance of one meter from the vineyard. The resolution varies within this set, with images available in 1024 x 1024 or 2208 x 1242 pixels. The second collection encompasses 236 RGB images, of which 155 are designated for training and 81 for validation. The second group is contained in the C2 and C3 folders. These images were taken with an Intel Realsense D435 camera, capturing shots of the grapes positioned 20 to 50 cm away from the camera. The resolution for this set is standardized at 1920 x 1080 pixels, with the camera securely mounted on one of the robot's arms. The third and final group consists of 1320 images, with 1092 allocated for training and 228 for validation. This group is splitted in the I1, I2 and I3 folders. Captured using a ZED2 camera, these images were obtained by an inspection platform located 1 meter away from the vineyard, maintaining a resolution of 1920 x 1080 pixels. Together, these diverse sets form a comprehensive RGB dataset for the development and assessment of vineyard-related algorithms. This dataset used for detecting the grapes in the images. All of the data were collected at Ktima Gerovassiliou in Epanomi, Thessaloniki. Below, there are six 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 grapes annotations. The first number represents the annotation's class (0 for grape), the second and third numbers are the normalized (in the image's shape) coordinates of the grape's bounding box up left edge, and the fourth and fifth numbers are the bounding box's width and height accordingly.

搜集汇总

背景与挑战

背景概述

GRAPE_DETECTION_DATASET是一个专为葡萄检测算法开发设计的RGB图像数据集，包含三组不同相机拍摄的图像，总计1707张（训练1348张，验证359张），覆盖多种拍摄条件和分辨率，并附带详细的葡萄边界框标注信息。数据集由BACCHUS H2020项目资助，数据采集于希腊塞萨洛尼基的Ktima Gerovassiliou。