Solutions for identifying and modeling interior architectural elements
To achieve fast identification and modeling, the following steps need to be followed:
- Environmental Preparation:First make sure the system meets the basic requirements of Python 3.11, Pytorch 2.4.1 and CUDA 12.4
- Data Acquisition:Collect indoor scene data using a regular camera, depth camera, or LIDAR, ensuring that the Z-axis of the point cloud data is vertically upward
- Model runs:Execute the inference command "python inference.py", the model will automatically recognize the walls, doors, windows and other architectural elements.
- Visualization of results:Use the rerun tool to view the 3D model with annotations to verify the recognition effect
To improve the recognition accuracy, it is recommended to collect the data in a well-lit environment and perform simple pre-processing of the point cloud data.
This answer comes from the articleSpatialLM: Sweep the room, AI automatically draws 3D models for youThe
May not be reproduced without permission:AI productivity tools " How to use SpatialLM for fast identification and 3D modeling of interior architectural elements?
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