Label | Explanation | Data Type |
Input Model Definition
| The point cloud classification models and batch sizes that will be used during the evaluation process. | Value Table |
Reference Point Cloud
| The point cloud that will be used to evaluate the classification models. | LAS Dataset Layer; File |
Target Folder
| The directory that will store the files which summarize the evaluation results. | Folder |
Base Name
| The file name prefix that will be used for each of the output files summarizing the evaluation results. | String |
Processing Boundary
(Optional) | The polygon feature that delineates the portions of the reference point cloud that will be used for evaluating the classification models. | Feature Layer |
Point Cloud Class Remapping
(Optional) | The class codes from the reference point cloud must match the class codes in the models being evaluated. When the class codes do not match, use this parameter to associate the differing class codes in the point cloud with the classes that are supported in the models being evaluated. | Value Table |
Reference Surface
(Optional) | The raster surface that will be used to provide relative height values for each point in the point cloud data. Points that do not overlap with the raster will be omitted from the analysis. | Raster Layer |
Excluded Class Codes
(Optional) | The class codes that will be excluded from processing. Any value in the range of 0 to 255 can be specified. | Long |
Derived Output
Label | Explanation | Data Type |
Output Confusion Matrices | The CSV format table storing the confusion matrix for each class code in each input model. | Text File |
Output Model Statistics | The CSV format table that summarizes the overall statistics of the input models. | Text File |
Output Class Code Statistics | The CSV format table that summarizes the statistics for each class code in each input model. | Text File |