Releases: ssciwr/afwizard
AFWizard v1.0.0
AFWizard is a Python package to enhance the productivity of ground point filtering workflows in archaeology and beyond.
It provides a Jupyter-based environment for "human-in-the-loop" tuned, spatially heterogeneous ground point filterings.
Core features:
- Working with Lidar datasets directly in Jupyter notebooks
- Loading/Storing of LAS/LAZ files
- Visualization using hillshade models and slope maps
- Applying of ground point filtering algorithms
- Cropping with a map-based user interface
- Accessibility of existing filtering algorithms under a unified data model:
- Access to predefined filter pipeline settings
- Crowd-sourced library of filter pipelines at https://github.com/ssciwr/afwizard-library/
- Filter definitions can be shared with colleagues as files
- Spatially heterogeneous application of filter pipelines
- Assignment of filter pipeline settings to spatial subregions in map-based user interface
- Command Line Interface for large scale application of filter pipelines
AFwizard v.1.0.0b9
AFWizard is a Python package to enhance the productivity of ground point filtering workflows in archaeology and beyond.
It provides a Jupyter-based environment for "human-in-the-loop" tuned, spatially heterogeneous ground point filterings.
Core features:
- Working with Lidar datasets directly in Jupyter notebooks
- Loading/Storing of LAS/LAZ files
- Visualization using hillshade models and slope maps
- Applying of ground point filtering algorithms
- Cropping with a map-based user interface
- Accessibility of existing filtering algorithms under a unified data model:
- Access to predefined filter pipeline settings
- Crowd-sourced library of filter pipelines at https://github.com/ssciwr/afwizard-library/
- Filter definitions can be shared with colleagues as files
- Spatially heterogeneous application of filter pipelines
- Assignment of filter pipeline settings to spatial subregions in map-based user interface
- Command Line Interface for large scale application of filter pipelines
This is a beta release of afwizard. You are welcome to test the library and report any issues you might find.
AFwizard v.1.0.0b7
AFWizard is a Python package to enhance the productivity of ground point filtering workflows in archaeology and beyond.
It provides a Jupyter-based environment for "human-in-the-loop" tuned, spatially heterogeneous ground point filterings.
Core features:
- Working with Lidar datasets directly in Jupyter notebooks
- Loading/Storing of LAS/LAZ files
- Visualization using hillshade models and slope maps
- Applying of ground point filtering algorithms
- Cropping with a map-based user interface
- Accessibility of existing filtering algorithms under a unified data model:
- Access to predefined filter pipeline settings
- Crowd-sourced library of filter pipelines at https://github.com/ssciwr/afwizard-library/
- Filter definitions can be shared with colleagues as files
- Spatially heterogeneous application of filter pipelines
- Assignment of filter pipeline settings to spatial subregions in map-based user interface
- Command Line Interface for large scale application of filter pipelines
This is a beta release of afwizard. You are welcome to test the library and report any issues you might find.
AFwizard v.1.0.0b6
AFWizard is a Python package to enhance the productivity of ground point filtering workflows in archaeology and beyond.
It provides a Jupyter-based environment for "human-in-the-loop" tuned, spatially heterogeneous ground point filterings.
Core features:
- Working with Lidar datasets directly in Jupyter notebooks
- Loading/Storing of LAS/LAZ files
- Visualization using hillshade models and slope maps
- Applying of ground point filtering algorithms
- Cropping with a map-based user interface
- Accessibility of existing filtering algorithms under a unified data model:
- Access to predefined filter pipeline settings
- Crowd-sourced library of filter pipelines at https://github.com/ssciwr/afwizard-library/
- Filter definitions can be shared with colleagues as files
- Spatially heterogeneous application of filter pipelines
- Assignment of filter pipeline settings to spatial subregions in map-based user interface
- Command Line Interface for large scale application of filter pipelines
This is a beta release of afwizard. You are welcome to test the library and report any issues you might find.
AFwizard v.1.0.0b5
AFWizard is a Python package to enhance the productivity of ground point filtering workflows in archaeology and beyond.
It provides a Jupyter-based environment for "human-in-the-loop" tuned, spatially heterogeneous ground point filterings.
Core features:
- Working with Lidar datasets directly in Jupyter notebooks
- Loading/Storing of LAS/LAZ files
- Visualization using hillshade models and slope maps
- Applying of ground point filtering algorithms
- Cropping with a map-based user interface
- Accessibility of existing filtering algorithms under a unified data model:
- Access to predefined filter pipeline settings
- Crowd-sourced library of filter pipelines at https://github.com/ssciwr/afwizard-library/
- Filter definitions can be shared with colleagues as files
- Spatially heterogeneous application of filter pipelines
- Assignment of filter pipeline settings to spatial subregions in map-based user interface
- Command Line Interface for large scale application of filter pipelines
This is the third beta release of afwizard. You are welcome to test the library and report any issues you might find.
AFWizard v.1.0.0b2
AFWizard is a Python package to enhance the productivity of ground point filtering workflows in archaeology and beyond.
It provides a Jupyter-based environment for "human-in-the-loop" tuned, spatially heterogeneous ground point filterings.
Core features:
- Working with Lidar datasets directly in Jupyter notebooks
- Loading/Storing of LAS/LAZ files
- Visualization using hillshade models and slope maps
- Applying of ground point filtering algorithms
- Cropping with a map-based user interface
- Accessibility of existing filtering algorithms under a unified data model:
- Access to predefined filter pipeline settings
- Crowd-sourced library of filter pipelines at https://github.com/ssciwr/afwizard-library/
- Filter definitions can be shared with colleagues as files
- Spatially heterogeneous application of filter pipelines
- Assignment of filter pipeline settings to spatial subregions in map-based user interface
- Command Line Interface for large scale application of filter pipelines
This is the third beta release of afwizard. You are welcome to test the library and report any issues you might find.
adaptivefiltering v1.0.0b1
adaptivefiltering is a Python package to enhance the productivity of ground point filtering workflows in archaeology and beyond.
It provides a Jupyter-based environment for "human-in-the-loop" tuned, spatially heterogeneous ground point filterings.
Core features:
- Working with Lidar datasets directly in Jupyter notebooks
- Loading/Storing of LAS/LAZ files
- Visualization using hillshade models and slope maps
- Applying of ground point filtering algorithms
- Cropping with a map-based user interface
- Accessibility of existing filtering algorithms under a unified data model:
- Access to predefined filter pipeline settings
- Crowd-sourced library of filter pipelines at https://github.com/ssciwr/adaptivefiltering-library/
- Filter definitions can be shared with colleagues as files
- Spatially heterogeneous application of filter pipelines
- Assignment of filter pipeline settings to spatial subregions in map-based user interface
- Command Line Interface for large scale application of filter pipelines
This is the second beta release of adaptivefiltering. You are welcome to test the library and report any issues you might find.
adaptivefiltering v1.0.0b0
adaptivefiltering is a Python package to enhance the productivity of ground point filtering workflows in archaeology and beyond.
It provides a Jupyter-based environment for "human-in-the-loop" tuned, spatially heterogeneous ground point filterings.
Core features:
- Working with Lidar datasets directly in Jupyter notebooks
- Loading/Storing of LAS/LAZ files
- Visualization using hillshade models and slope maps
- Applying of ground point filtering algorithms
- Cropping with a map-based user interface
- Accessibility of existing filtering algorithms under a unified data model:
- Access to predefined filter pipeline settings
- Crowd-sourced library of filter pipelines at https://github.com/ssciwr/adaptivefiltering-library/
- Filter definitions can be shared with colleagues as files
- Spatially heterogeneous application of filter pipelines
- Assignment of filter pipeline settings to spatial subregions in map-based user interface
- Command Line Interface for large scale application of filter pipelines
This is the first beta release of adaptivefiltering. You are welcome to test the library and report any issues you might find.