CloudComPy_Conda310_MacOS_20240613
CloudComPy For macOS, Python 3.10 - June 13, 2024
This version is based on CloudCompare 2.13.1 (official release, March 20, 2024).
Built and tested on macOS SONOMA 14.5. Compatible with macOS 12.7 and later.
This application is self contained, signed and notarized. Please post issues on CloudComPy GitHub in case of problem.
Please read the installation instructions on GitLab
CloudCompare works as it is (no specific environment). It is located in CloudComPy310/CloudCompare/CloudCompare.app
and can be launched from the Finder.
CloudComPy needs a Python 3.10 configuration with at least the following packages, either with conda or not:numpy
scipy
requests
psutils
matplotlib
quaternion
You can create an environment for CloudComPy with conda, from the terminal
(here, I chose to activate conda environment on demand: please adapt the instructions to your installation)
The following package list corresponds to the building environment, but you can adjust the list
(at least the above list):conda activate
conda update -y -n base -c defaults conda
If your environment CloudComPy310 does not exist:conda create --name CloudComPy310 python=3.10
# --- erase previous env with the same name if existing
Add or update the packages:conda activate CloudComPy310
conda config --add channels conda-forge
conda config --set channel_priority strict
conda
install "boost" "cgal" cmake draco ffmpeg "gdal" jupyterlab laszip
"matplotlib" "mysql=8.0" "numpy" "opencv" "openssl=3.0.8" "pcl" "pdal"
"psutil" pybind11 quaternion "qhull=2020.2" "qt=5.15.8" "scipy" sphinx_rtd_theme
spyder tbb tbb-devel "xerces-c=3.2" xorg-libx11 || error_exit "conda
environment ${CONDA_ENV} cannot be completed"
This version brings the following features:
- (issue #162) SAVE ccMesh <CC_FILE_ERROR.CC_FERR_BROKEN_DEPENDENCY_ERROR: 13>
- (issue #163) Add default arguments to ICP function
- (issue #167) Distance map: try to use the same scalar field names as CloudCompare
- (issue #170) Color scale: select in a list, edit
- (issue #172) add quaternion input for transformations (requires numpy quaternion package to be useful)
- some small fixes.