InLUT3D: Indoor Lodz University of Technology Point Cloud Dataset

This resource contains Indoor Lodz University of Technology Point Cloud Dataset (InLUT3D) - a point cloud dataset tailored for real object classification and both semantic and instance segmentation tasks. Comprising of 321 scans, some areas in the dataset are covered by multiple scans. All of them are captured using the Leica BLK360 scanner. The points are divided into 18 distinct categories outlined in the label.yaml file along with their respective codes and colors. Among categories you will find: ceiling, floor, wall, stairs, column, chair, sofa, table, storage, door, window, plant, dish, wallmounted, device, radiator, lighting, other. Several challenges are intrinsic to the presented dataset: Extremely non-uniform categories distribution across the dataset. Presence of virtual images, particularly in reflective surfaces, and data exterior to windows and doors. Occurrence of missing data due to scanning shadows (certain areas were inaccessible to the scanner's laser beam). High point density throughout the dataset. The structure of the dataset is the following: inlut3d.tar.gz/├─ setup_0/│  ├─ projection.jpg│  ├─ segmentation.jpg│  ├─ setup_0.pts├─ setup_1/│  ├─ projection.jpg│  ├─ segmentation.jpg│  ├─ setup_1.pts... projection.jpg A file containing a spherical projection of a corresponding PTS file. segmentation.jpg A file with objects marked with unique colours. setup_x.pts A file with point cloud int the textual PTS format. Each PTS file contains 8 columns: Column ID Description 1 X Cartesian coordinate 2 Y Cartesian coordinate 3 Z Cartesian Coordinate 4 Red colour in RGB space in the range [0, 255] 5 Green colour in RGB space in the range [0, 255] 6 Blue colour in RGB space in the range [0, 255] 7 Category code 8 Instance ID本资源包含罗兹工业大学室内点云数据集（Indoor Lodz University of Technology Point Cloud Dataset，简称InLUT3D）——一款专为真实物体分类、语义分割与实例分割任务定制的点云数据集。该数据集共包含321组扫描数据，部分区域存在多扫描覆盖的情况，所有数据均通过Leica BLK360扫描仪采集。 数据点被划分为18个独立类别，相关信息（含类别代码与配色方案）均在label.yaml文件中列明。涵盖的类别包括：天花板、地板、墙面、楼梯、立柱、椅子、沙发、桌子、储物设施、门、窗户、植物、餐具、壁挂式物件、设备、散热器、照明设施及其他。 该数据集存在多项固有挑战：类别分布极不均匀；存在虚拟成像现象，尤其在反射表面以及门窗外侧区域；因扫描阴影（扫描仪激光束无法覆盖部分区域）导致数据缺失；全数据集点云密度较高。 数据集的目录结构如下： inlut3d.tar.gz/ ├─ setup_0/ │ ├─ projection.jpg │ ├─ segmentation.jpg │ ├─ setup_0.pts ├─ setup_1/ │ ├─ projection.jpg │ ├─ segmentation.jpg │ ├─ setup_1.pts ... 各文件说明如下： projection.jpg：存储对应PTS文件的球形投影图像。 segmentation.jpg：使用唯一配色标记物体的分割标注图像。 setup_x.pts：采用文本PTS格式存储的点云文件。 每个PTS文件包含8列数据，各列详情如下： | 列ID | 说明 | | ---- | ---- | | 1 | X轴笛卡尔坐标 | | 2 | Y轴笛卡尔坐标 | | 3 | Z轴笛卡尔坐标 | | 4 | RGB色彩空间中的红色分量，取值范围为[0, 255] | | 5 | RGB色彩空间中的绿色分量，取值范围为[0, 255] | | 6 | RGB色彩空间中的蓝色分量，取值范围为[0, 255] | | 7 | 类别代码 | | 8 | 实例ID