New version 26.1 of Global Mapper Pro® includes interface changes, point cloud classification updates, fine-tuning for vehicle detection, and more! Global Mapper’s iconic toolbar stack has been refined to include a scripting toolbar and a condensed lidar toolbar, both boasting new tools. The Lidar QC tool provides users the ability to adjust utilized GCPs to ensure the most accurate calculations Additionally, Pixels to Points® now supports 3 different Color Harmonization methods from openMVG.
Keep an eye out for our next blog about what’s new in the standard version of Global Mapper!
Fine-Tuning for Vehicle Detection with the Global Mapper Insight and Learning Engine
Global Mapper Insight and Learning Engine™(beta) is a deep learning-powered image analysis toolset. The suite of tools provides trained models for land cover classification, vehicle identification, and building extraction. Fine-tuning allows users to re-train layers of a model to improve the analysis results on specific datasets. In version 26.1, Vehicle Detection is now supported in fine-tuning and training, providing users with the ability to use their own truth data to tailor models to their needs. Other updates include improved handling of canceled training data, allowing users to easily use the same experiment name again.
Configuration Settings for the Insight and Learning Engine
A new dedicated configuration dialog is now available for user control over models, including downloading, sharing, and updating models. Blue Marble Geographics provides some built-in models for the Insight and Learning Engine tools, such as building and vehicle detection. Due to file size, a separate download is required. Updates for the models are provided periodically, and in v26.1 are now available for download within the Configuration menu.
Vehicle Detection in the Insight and Learning Engine can now be fine-tuned.
Ease-of-Use Updates in the Scripting Toolbar
A Scripting toolbar has been added to provide easy access to the Script Builder, Script Editor, and a new Favorite Scripts functionality. Use the Favorite Script Manager to list frequently used scripts. Running a tool or workflow is now as easy as choosing a script from the dropdown and clicking the run button. Scripting is also available in the standard version of Global Mapper, with expected functionality limitations.
Accessed from the Scripting toolbar or Tools menu, the Favorite Scripts Manager provides an easy menu for managing frequently used scripts. Compatible with both Global Mapper and Python, scripts can be saved in the Favorite Scripts menu to be executed at any time.
Use the manager to choose which scripts you would like easy access to from within the Scripting toolbar. Once added to the favorites list, a copy of the script is stored in your Global Mapper library, separate from the original file. Use the tools within the Favorite Scripts tool to manage your scripts and streamline your Global Mapper workflow.
The Favorite Scripts Manager stores chosen Global Mapper scripts for ease of use.
Streamlined Lidar Tools
All of the point cloud tools in Global Mapper are now organized into one toolbar, condensing the previously separate toolbars. This new comprehensive Lidar toolbar in Global Mapper Pro contains all point cloud tools, grouped by similar functions together in mini-menus. These dropdown sections of the toolbar hold related tools for Classification and Selection. The deprecated Manual classification toolbar can still be enabled from the View menu, but those buttons have been replaced by the new Manual Classification toolset.
The Selection dropdown includes Select by Class, Select by Distance, Find Duplicate Lidar, and Select by Segment.
New Lidar Manual Classification Toolset
In place of the Manual Classification Toolbar, the manual classification buttons have been combined into the Manual Classification toolset. A new “unclassified” classification button is also included, along with the ability to specify additional classes from the dropdown menu as shown in the image below. These additional classes can be created through the Custom Classification tool, or in the Lidar tab in Configuration.
The Manual Classification tool supports a lidar edit mode where the chosen class will be applied to any points selected while in the editing mode. This allows for continuous editing without the need for hotkeys. Additionally, as a result of the separate selection functionality, you can have multiple tools enabled simultaneously; the digitizer in the Manual classification tool can be enabled at the same time as the Path Profile tool, along with the Select by Area tool within the Path Profile window. Happen to classify the wrong points? Use Global Mapper’s trusty Undo function (ctrl + z). The new Manual Classification tool makes point cloud cleanup in Global Mapper Pro so, so easy.
All existing and new manual classification buttons are included in the Manual Classification tool.
Classify Powerlines using the Maximum Likelihood Method
Maximum Likelihood is a classification method that leverages geometric segmentation to identify which class a feature is most likely to represent. This method is now available for use when identifying powerlines – providing a more advanced method for powerline classification. The Maximum Likelihood method can identify linear segments within the point cloud. This gives it the strength to better discern powerlines from surrounding vegetation.
The Maximum Likelihood method can discern powerline points apart from surrounding vegetation.
Point Cloud Reports
Global Mapper Pro v26.1 includes the option to save your classification settings for future use and to view a summary report of automatic point cloud processing results. When this checkbox is enabled, a text file summary of the report will display in Global Mapper upon the completion of the classification process. This file will also be saved at the specified location, along with a .JSON file. To reimport these settings, choose the option to Enable Custom Feature Models and use the Load Models button to navigate to the .JSON file.
This provides a method of saving your settings to apply to another workspace or in the future, without having to translate them into a script file.