Saipullah K M, Saad W H M, Wong Q L, Husni M S M, Idris M I, Razak M S J A
Fakulti Kejuruteraan Elektronik dan Kejuruteraan Komputer (FKEKK), Universiti Teknikal Malaysia Melaka (UTeM), Durian Tunggal, 76100, Melaka, Malaysia.
Strukture Robotics Sdn Bhd, Rekascape, 63000 Cyberjaya, Malaysia.
Data Brief. 2023 Oct 23;51:109714. doi: 10.1016/j.dib.2023.109714. eCollection 2023 Dec.
This paper presents a dataset of bird's eye chilies in a single farm for semantic segmentation. The dataset is generated using two cameras that are aligned left and right forming a stereo-vision video capture. By analyzing the disparity between corresponding points in the left and right images, algorithms can calculate the relative distance of objects in the scene. This depth information is useful in various applications, including 3D reconstruction, object tracking, and autonomous navigation. The dataset consists of 1150 left and right compressed images extracted from ten sets of stereo videos taken at ten different locations within the chili farm from the same ages of the bird's eye chilies. Since the dataset is used for semantic segmentation, the ground truth images of manually semantic segmented images are also provided in the dataset. The dataset can be used for 2D and 3D semantic segmentation of the bird's eye view chili farm. Some of the object classes in this dataset are the sky, living things, plantation, flat, construction, nature, and misc.
本文展示了一个用于语义分割的单一农场中鸟眼辣椒的数据集。该数据集是使用两个左右对齐的摄像头生成的，形成立体视觉视频捕获。通过分析左右图像中对应点之间的视差，算法可以计算场景中物体的相对距离。这种深度信息在各种应用中都很有用，包括三维重建、目标跟踪和自主导航。该数据集由1150张左右压缩图像组成，这些图像从辣椒农场内十个不同位置拍摄的十组立体视频中提取，拍摄的是相同生长阶段的鸟眼辣椒。由于该数据集用于语义分割，数据集中还提供了手动语义分割图像的地面真值图像。该数据集可用于鸟瞰辣椒农场的二维和三维语义分割。该数据集中的一些物体类别包括天空、生物、种植园、平地、建筑、自然和杂物。
