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cloth-simulation-filter-1.1.4


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توضیحات

CSF: Ground Filtering based on Cloth Simulation
ویژگی مقدار
سیستم عامل -
نام فایل cloth-simulation-filter-1.1.4
نام cloth-simulation-filter
نسخه کتابخانه 1.1.4
نگهدارنده ['Jianbo Qi']
ایمیل نگهدارنده ['jianboqi@126.com']
نویسنده Jianbo Qi
ایمیل نویسنده -
آدرس صفحه اصلی http://ramm.bnu.edu.cn/projects/CSF/
آدرس اینترنتی https://pypi.org/project/cloth-simulation-filter/
مجوز Apache-2.0
![csf1](https://github.com/jianboqi/CSF/blob/master/CSFDemo/CSF1.png) ![csf2](https://github.com/jianboqi/CSF/blob/master/CSFDemo/CSF2.png) # CSF Airborne LiDAR filtering method based on Cloth Simulation. This is the code for the article: W. Zhang, J. Qi*, P. Wan, H. Wang, D. Xie, X. Wang, and G. Yan, “An Easy-to-Use Airborne LiDAR Data Filtering Method Based on Cloth Simulation,” Remote Sens., vol. 8, no. 6, p. 501, 2016. (http://www.mdpi.com/2072-4292/8/6/501/htm) **New feature has been implemented:** Now, We has wrapped a Python interface for CSF with swig. It is simpler to use now. This new feature can make CSF easier to be embeded into a large project. For example, it can work with Laspy (https://github.com/laspy/laspy). What you do is just read a point cloud into a python 2D list, and pass it to CSF. The following example shows how to use it with laspy. ```python # coding: utf-8 import laspy import CSF import numpy as np inFile = laspy.read(r"in.las") # read a las file points = inFile.points xyz = np.vstack((inFile.x, inFile.y, inFile.z)).transpose() # extract x, y, z and put into a list csf = CSF.CSF() # prameter settings csf.params.bSloopSmooth = False csf.params.cloth_resolution = 0.5 # more details about parameter: http://ramm.bnu.edu.cn/projects/CSF/download/ csf.setPointCloud(xyz) ground = CSF.VecInt() # a list to indicate the index of ground points after calculation non_ground = CSF.VecInt() # a list to indicate the index of non-ground points after calculation csf.do_filtering(ground, non_ground) # do actual filtering. outFile = laspy.LasData(inFile.header) outFile.points = points[np.array(ground)] # extract ground points, and save it to a las file. out_file.write(r"out.las") ``` **Reading data from txt file:** If the lidar data is stored in txt file (x y z for each line), it can also be imported directly. ```python import CSF csf = CSF.CSF() csf.readPointsFromFile('samp52.txt') csf.params.bSloopSmooth = False csf.params.cloth_resolution = 0.5 ground = CSF.VecInt() # a list to indicate the index of ground points after calculation non_ground = CSF.VecInt() # a list to indicate the index of non-ground points after calculation csf.do_filtering(ground, non_ground) # do actual filtering. csf.savePoints(ground,"ground.txt") ``` ### How to use CSF in Python Download the source code. under python folder: ```python python setup.py build python setup.py install ``` ### How to use CSF in Matlab see more details from file `demo_mex.m` under matlab folder. ### How to use CSF in R Thanks to the nice work of @Jean-Romain, through the collaboration, the CSF has been made as a R package, the details can be found in the [RCSF repository](https://github.com/Jean-Romain/RCSF). This package can be used easily with the [lidR package](https://github.com/Jean-Romain/lidR): ```r library(lidR) las <- readLAS("file.las") las <- lasground(las, csf()) ``` ### How to use CSF in C++ Now, CSF is built by CMake, it produces a static library, which can be used by other c++ programs. #### linux To build the library, run: ```bash mkdir build #or other name cd build cmake .. make sudo make install ``` or if you want to build the library and the demo executable `csfdemo` ```bash mkdir build #or other name cd build cmake -DBUILD_DEMO=ON .. make sudo make install ``` #### Windows You can use CMake GUI to generate visual studio solution file. ### Binary Version For binary release version, it can be downloaded at: http://ramm.bnu.edu.cn/projects/CSF/download/ Note: This code has been changed a lot since the publication of the corresponding paper. A lot of optimizations have been made. We are still working on it, and wish it could be better. ### Cloudcompare Pulgin At last, if you are interested in Cloudcompare, there is a good news. our method has been implemented as a Cloudcompare plugin, you can refer to : https://github.com/cloudcompare/trunk ### Related project A tool named `CSFTools` has been recently released, it is based on CSF, and provides dem/chm generation, normalization. Please refer to: https://github.com/jianboqi/CSFTools ### License CSF is maintained and developed by Jianbo QI. It is now released under Apache 2.0.


نحوه نصب


نصب پکیج whl cloth-simulation-filter-1.1.4:

    pip install cloth-simulation-filter-1.1.4.whl


نصب پکیج tar.gz cloth-simulation-filter-1.1.4:

    pip install cloth-simulation-filter-1.1.4.tar.gz