RGB-D stair dataset
Description
We provide an RGB-D dataset with stair line labels and stair step surface labels for stair detection research. The images in the training set and the validation set are from Stair dataset with depth maps [1]. Based on this dataset, we remove the RGB images taken under no light source conditions, and finally retain 2276 RGB-D image pairs as the training set and 556 RGB-D image pairs as the validation set. All the images in the training set and the validation set are padded and scaled to 512 × 512. To implement point cloud reconstruction, we use the RealSense D435i depth camera to collect 154 RGB-D image pairs with a resolution of 640 × 480 as the test set. During the collection, we record the camera's pose and the linear transformation relationship of depth map generation for point cloud reconstruction. The labels include stair line labels and stair step surface labels, The stair line labels have the following format: cls x1 y1 x2 y2/n ... Where cls represents the class of the stair line, 0 represents a convex line and 1 represents a concave line. X1 and y1 represent the coordinates of the left endpoint of the stair line, and x2 and y2 represent the coordinates of the right endpoint of the stair line. The label of an image is stored in a text file and associated by the file name. The stair step surface labels contain the annotation of semantic segmentation for stair step surfaces. The segmentation label is stored in a gray image with a size of 512 × 512, and the classifications include stair riser surface (pixels with 128 value in the gray image), stair tread surface (pixels with 255 value in the gray image) and background (pixels with 0 value in the gray image). For the folder structure, the train file, val file and test file store the training set, the validation set and the test set, respectively. And in train and val files, there are images file, depthes file, labels file and segmentations file, which store the RGB images, the depth images, the stair line labels and stair step surface labels, respectively. In test file, there are images file, depthes file, extrinsicses file, pcds file, plys file, which store the RGB images, the depth images, the linear transformations for depth map generation, the point clouds with pcd format and the point clouds with ply format, respectively. [1] Wang, Chen; Pei, Zhongcai; Qiu, Shuang; Tang, Zhiyong (2023), “Stair dataset with depth maps”, Mendeley Data, V3, doi: 10.17632/p28ncjnvgk.3