🚀Scan to Model Pipeline (SMP)

3D scan data such as PCD (point cloud data) to model (ply) conversion.
The scan to model pipeline (SMP) is an open source tool that automatically generates mesh model files (PLY) by filtering and clustering data in LAS, a point cloud format. Using this, you can automate the extraction of buildings, ground, and trees from PCD. It is structured as a pipeline, so you can easily adjust parameters for each data processing step. This open source can be used to generate statistical numerical, low LoD level model files of objects from large number of PCD files.

• PCD filtering using color map, CSF, DBScan, RTree.
• Clustering such as house, tree, ground
• Footprint extraction
• Spreadsheet including ID, area, height of building, etc
• Pipeline config file support (refer to pipeline config section)
• LAS, PLY support

Revision history

It's still in its early stages, but if you have the will, you can improve the parts that are lacking.

• 0.1: 2024.1. draft version. basic functions supports.
• 0.15: 2024.8. add pipeline stage architecture.

Examples

Install

To install the required dependencies, you can use:

pip install -r requirements.txt

Config

pipeline

The pipeline consists of stages such as clustring with CSF, footprint and LoD generation. Each stage has parameters depending on stage's algorithm. Refer to the below example.

[
	{            
		"name": "csf",
		"config": {
			"cloth_resolution": 1.0, 
			"rigidness": 3,
			"time_step": 0.65, 
			"class_threshold": 0.5, 
			"interations": 500 
		},
		"output_tag": "{segment}_{cloth_resolution}"
	}, 
	{
		"name": "cluster",
		"input_filter": ".*non_ground.*",
		"config": {
			"eps": 3.0, 
			"min_samples": 10,
			"remove_samples": 100,
			"random_color": false 
		}, 
		"output_tag": "{segment}"
	}, 
	{
		"name": "footprint",
		"config": {
			"alpha_shape_factor": 0.2, 
			"simplify_tolerance": 0.1
		}, 
		"output_tag": "{segment}"
	}, 
	{
		"name": "LoD",
		"config": {
			"csf.ground": "$ground"
		}
	},
	{
		"name": "sheet",
		"config": {
			"merge": true
		}
	}
]

color map

Color maps can be used for PCD clustering, but the current version is not complete.

{
    "name": "color map filter",
    "version": "1.0.0",
    "description": "segmentation using color map",
    "author": "",
    "email": "",
    "segment": [
        {
            "name": "house",
            "RGB1": [95, 108, 118],
            "RGB2": [167, 171, 189]
        }, 
        {
            "name": "tree",
            "RGB1": [30, 50, 30],
            "RGB2": [140, 150, 60]
        }, 
        {
            "name": "other"
        }
    ]
}

Acknowledge

Deng, D., 2020, September. DBSCAN clustering algorithm based on density. In 2020 7th international forum on electrical engineering and automation (IFEEA) (pp. 949-953). IEEE.
Zhang, W., Qi, J., Wan, P., Wang, H., Xie, D., Wang, X. and Yan, G., 2016. An easy-to-use airborne LiDAR data filtering method based on cloth simulation. Remote sensing, 8(6), p.501.
Beckmann, N., Kriegel, H.P., Schneider, R. and Seeger, B., 1990, May. The R*-tree: An efficient and robust access method for points and rectangles. In Proceedings of the 1990 ACM SIGMOD international conference on Management of data (pp. 322-331).

Author

Ph.D, Kang. [email protected]
linkedin

License

MIT License