Merge remote-tracking branch 'origin/master' into lazperf

.github/workflows/conda.yml

@@ -13,7 +13,7 @@ jobs:
         platform: ['ubuntu-latest','windows-latest','macos-latest']
 
     env:
-      PLATFORM: ${{ matrix.platform }}
+      PDAL_PLATFORM: ${{ matrix.platform }}
 
     steps:
     - uses: actions/checkout@v2

.github/workflows/docker.yml

@@ -8,7 +8,7 @@ jobs:
   containers:
     runs-on: ubuntu-latest
     env:
-      PUSH_PACKAGES: ${{ github.repository_owner == 'PDAL' }}
+      PUSH_PACKAGES: ${{ github.repository_owner == 'PDAL' && github.event_name != 'pull_request'  }}
     steps:
       - uses: actions/checkout@v2
       - name: Lint

CMakeLists.txt

@@ -129,7 +129,6 @@ include(${PDAL_CMAKE_DIR}/gdal.cmake)
 include(${PDAL_CMAKE_DIR}/geotiff.cmake)  # Optional (not really)
 include(${PDAL_CMAKE_DIR}/lazperf.cmake)  # Optional
 include(${PDAL_CMAKE_DIR}/laszip.cmake)  # Optional
-include(${PDAL_CMAKE_DIR}/draco.cmake)  # Optional
 include(${PDAL_CMAKE_DIR}/threads.cmake)
 include(${PDAL_CMAKE_DIR}/zlib.cmake)
 include(${PDAL_CMAKE_DIR}/lzma.cmake)

cmake/draco.cmake

@@ -1,19 +1,6 @@
 #
-option(WITH_DRACO "Choose if Draco support should be built" TRUE)
-find_package(Draco EXACT 1.3.6)
+# the `pkg_check_modules` function is created with this call
+find_package(PkgConfig REQUIRED)
+pkg_check_modules(DRACO REQUIRED draco>1.4.0)
 
-if (WITH_DRACO)
-    set_package_properties(Draco PROPERTIES TYPE RECOMMENDED
-        PURPOSE "Provides Draco compression")
-    if(Draco_FOUND)
-        include_directories(${draco_INCLUDE_DIR})
-        set(CMAKE_REQUIRED_LIBRARIES ${draco_LIBRARIES})
-        set(PDAL_HAVE_DRACO 1)
-        set(BUILD_PLUGIN_DRACO 1)
-        set(DRACO_LIBRARY "draco")
-    else()
-        set(WITH_DRACO FALSE)
-    endif()
-else()
-        set(WITH_DRACO FALSE)
-endif()
+set(PDAL_HAVE_DRACO 1)

cmake/gdal.cmake

@@ -12,17 +12,17 @@ function(gdal_find_version _version)
     set(${_version} ${MAJOR}.${MINOR}.${REV} PARENT_SCOPE)
 endfunction(gdal_find_version)
 
-find_package(GDAL 2.2.0 REQUIRED)
+find_package(GDAL 3.0 REQUIRED)
 set_package_properties(GDAL PROPERTIES TYPE REQUIRED
     PURPOSE "Provides general purpose raster, vector, and reference system support")
 if (GDAL_FOUND)
     gdal_find_version(GDAL_VERSION)
     #
     # Older versions of FindGDAL.cmake don't properly set GDAL_VERSION
     #
-    if (GDAL_VERSION VERSION_LESS 2.2.0)
+    if (GDAL_VERSION VERSION_LESS 3.0.0)
         message(FATAL_ERROR
-            "Found GDAL version ${GDAL_VERSION}.  Version 2.2+ is required")
+            "Found GDAL version ${GDAL_VERSION}.  Version 3.0+ is required")
     endif()
     mark_as_advanced(CLEAR GDAL_INCLUDE_DIR)
     mark_as_advanced(CLEAR GDAL_LIBRARY)

doc/apps/chamfer.rst

@@ -21,8 +21,8 @@ distance :math:`d_{CD}(X,Y)` is
 
 ::
 
-    --source arg     Non-positional option for specifying filename of source file.
-    --candidate arg  Non-positional option for specifying filename to test against source.
+    --source arg     Source filename
+    --candidate arg  Candidate filename
 
 The algorithm makes no distinction between source and candidate files (i.e.,
 they can be transposed with no affect on the computed distance).

doc/apps/eval.rst

@@ -0,0 +1,70 @@
+.. _eval_command:
+
+********************************************************************************
+eval
+********************************************************************************
+
+The ``eval`` command is used to compare the ``Classification`` dimensions of two
+point clouds.
+::
+
+    $ pdal eval <predicted> <truth> --labels <labels>
+
+::
+
+    --predicted arg     Positional argument specifying point cloud filename containing predicted labels.
+    --truth arg         Positional argument specifying point cloud filename containing truth labels.
+    --labels arg        Comma-separated list of classification labels to evaluate.
+
+The command returns 0 along with a JSON-formatted classification report
+summarizing various classification metrics.
+
+In the provided example below, the truth and predicted point clouds contain
+points classified as ground (class 2) and medium vegetation (class 4) in
+accordance with the LAS specification. Both point clouds also contain some
+number of classifications that are either unlabeled or do not fall into the
+specificied classes.
+
+::
+
+    $ pdal eval predicted.las truth.las --labels 2,4
+    {
+      "confusion_matrix": "[[5240537,3860,24102],[268015,3179304,326677],[111453,115516,2950315]]",
+      "f1_score": 0.944,
+      "labels": [
+        {
+          "accuracy": 0.967,
+          "f1_score": 0.973,
+          "intersection_over_union": 0.947,
+          "label": "1",
+          "precision": 0.951,
+          "sensitivity": 0.995,
+          "specificity": 0.929,
+          "support": 5268499
+        },
+        {
+          "accuracy": 0.934,
+          "f1_score": 0.914,
+          "intersection_over_union": 0.842,
+          "label": "2",
+          "precision": 0.999,
+          "sensitivity": 0.842,
+          "specificity": 0.999,
+          "support": 3773996
+        }
+      ],
+      "mean_intersection_over_union": 0.894,
+      "overall_accuracy": 0.931,
+      "pdal_version": "2.2.0 (git-version: 6e80b9)",
+      "predicted_file": "predicted.las",
+      "truth_file": "truth.las"
+    }
+
+Most of the returned metrics will be self explanatory, with scores reported
+both for individual classes and at a summary level. The returned confusion
+matrix is presented in row-major order, where each row corresponds to a truth
+label (the last row is a catch-all for any unlabeled or ignored entries).
+Similarly, confusion matrix columns correspond to predicted labels where the
+last column is once again a catch-all for unlabeled entries. Although
+unlabeled/ignored truth labels are reported in the confusion matrix, they are
+excluded from all computed scores.

doc/apps/hausdorff.rst

@@ -25,8 +25,8 @@ supremum and infimum respectively.
 
 ::
 
-    --source arg     Non-positional option for specifying filename of source file.
-    --candidate arg  Non-positional option for specifying filename to test against source.
+    --source arg     Source filename
+    --candidate arg  Candidate filename
 
 The algorithm makes no distinction between source and candidate files (i.e.,
 they can be transposed with no affect on the computed distance).

doc/stages/filters.assign.rst

@@ -23,8 +23,8 @@ assignment
   to the dimension value as set when the filter began processing. [Required]
 
 condition
-  A list of :ref:`ranges <ranges>` that a point's values must pass in order
-  for the assignment to be performed. [Default: none]
+  A single :ref:`ranges <ranges>` that a point's values must pass in order
+  for the assignment to be performed. [Default: none] [Deprecated - use 'value']
 
 value
   A list of :ref:`assignment expressions <Assignment Expressions>` to be applied to points.

doc/stages/filters.cluster.rst

@@ -46,3 +46,5 @@ is3d
   By default, clusters are formed by considering neighbors in a 3D sphere, but
   if ``is3d`` is set to false, it will instead consider neighbors in a 2D
   cylinder (XY plane only). [Default: true]
+
+.. include:: filter_opts.rst

doc/stages/filters.icp.rst

@@ -63,10 +63,10 @@ The metadata output might start something like:
             "filters.icp":
             {
                 "centroid": "    583394  5.2831e+06   498.152",
-                "composed": "           1  2.60209e-18 -1.97906e-09       -0.374999  8.9407e-08            1  5.58794e-09      -0.614662 6.98492e -10 -5.58794e-09            1   0.033234           0            0            0            1",
+                "composed": "           1  2.60209e-18 -1.97906e-09       -0.374999  8.9407e-08            1  5.58794e-09      -0.614662 6.98492e-10 -5.58794e-09            1   0.033234           0            0            0            1",
                 "converged": true,
                 "fitness": 0.01953125097,
-                "transform": "           1  2.60209e-18 -1.97906e-09       -0.375  8.9407e-08            1  5.58794e-09      -0.5625 6.98492e -10 -5.58794e-09            1   0.00411987           0            0            0            1"
+                "transform": "           1  2.60209e-18 -1.97906e-09       -0.375  8.9407e-08            1  5.58794e-09      -0.5625 6.98492e-10 -5.58794e-09            1   0.00411987           0            0            0            1"
             }
 
 
@@ -89,7 +89,7 @@ would be similar to:
         },
         {
             "type": "filters.transformation",
-            "matrix": "1  2.60209e-18 -1.97906e-09       -0.375  8.9407e-08            1  5.58794e-09      -0.5625 6.98492e -10 -5.58794e-09            1   0.00411987           0            0            0            1"
+            "matrix": "1  2.60209e-18 -1.97906e-09       -0.375  8.9407e-08            1  5.58794e-09      -0.5625 6.98492e-10 -5.58794e-09            1   0.00411987           0            0            0            1"
         },
         {
             "type": "filters.transformation",

doc/stages/filters.zsmooth.rst

@@ -0,0 +1,52 @@
+.. _filters.zsmooth:
+
+filters.zsmooth
+===============================================================================
+
+The **Zsmooth Filter** computes a new Z value as another dimension that is based
+on the Z values of neighboring points.
+
+All points within some distance in the X-Y plane from a reference point are ordered by Z value.
+The reference point's new smoothed Z value is chosen to be that of the Nth median value of
+the neighboring points, where N is specified as the _`medianpercent` option.
+
+Use :ref:`filters.assign` to assign the smoothed Z value to the actual Z dimension if
+desired.
+
+Example
+-------
+
+Compute the smoothed Z value as the median Z value of the neighbors within 2 units and
+assign the value back to the Z dimension.
+
+[
+    "input.las",
+    {
+        "type": "filters.zsmooth",
+        "radius": 2,
+        "dim": "Zadj"
+    },
+    {
+        "type": "filters.assign",
+        "value": "Z = Zadj"
+    },
+    "output.las"
+]
+
+Options
+-------------------------------------------------------------------------------
+
+radius
+  All points within `radius` units from the reference point in the X-Y plane are considered
+  to determine the smoothed Z value. [Default: 1]
+
+medianpercent
+  A value between 0 and 100 that specifies the relative position of ordered Z values of neighbors
+  to use as the new smoothed Z value. 0 specifies the minimum value. 100 specifies the
+  maximum value. 50 specifies the mathematical median of the values. [Default: 50]
+
+dim
+  The name of a dimension to use for the adjusted Z value. Cannot be 'Z'. [Required]
+
+.. include:: filter_opts.rst
+

doc/stages/readers.ept.rst

@@ -109,9 +109,8 @@ polygon
 
     When using ``pdal info --summary``, using the ``polygon`` option will cause the resulting bounds to be clipped to the maximal extents of all provided polygons, and the resulting number of points to be an upper bound for this polygon selection.
 
-threads
-    Number of worker threads used to download and process EPT data.  A
-    minimum of 4 will be used no matter what value is specified.
+requests
+    Maximum number of simultaneous requests for EPT data. [Minimum: 4] [Default: 15]
 
 .. _Entwine Point Tile: https://entwine.io/entwine-point-tile.html
 .. _Entwine: https://entwine.io/

doc/stages/readers.las.rst

@@ -110,3 +110,8 @@ ignore_vlr
 fix_dims
   Make invalid dimension names valid by converting disallowed characters to '_'. Only
   applies to names specified in an extra-bytes VLR. [Default: true]
+
+nosrs
+  Don't read the SRS VLRs. The data will not be assigned an SRS. This option is
+  for use only in special cases where processing the SRS could cause performance
+  issues. [Default: false]

doc/stages/readers.mrsid.rst

@@ -3,6 +3,10 @@
 readers.mrsid
 =============
 
+.. note::
+
+    The MrSID reader is deprecated and will be removed in a future release.
+
 Implements MrSID 4.0 LiDAR Compressor. It requires the `Lidar_DSDK`_ to be able to
 decompress and read data.
 

doc/stages/writer_opts.rst

@@ -0,0 +1,13 @@
+where
+    An :ref:`expression <PDAL expression>` that limits points passed to a writer.
+    Points that don't pass the
+    expression skip the stage but are available to subsequent stages in a pipeline.
+    [Default: no filtering]
+
+where_merge
+    A strategy for merging points skipped by a '`where'` option when running in standard mode.
+    If ``true``, the skipped points are added to the first point view returned by the skipped
+    filter. If ``false``, skipped points are placed in their own point view. If ``auto``,
+    skipped points are merged into the returned point view provided that only one point view
+    is returned and it has the same point count as it did when the writer was run.
+    [Default: ``auto``]

doc/stages/writers.draco.rst

@@ -72,7 +72,7 @@ quantization
     "GENERIC": 8
 }
 
-
+.. include:: writer_opts.rst
 
 .. _PDAL's Type specification: https://github.com/PDAL/PDAL/blob/master/pdal/DimUtil.hpp
-.. _Draco: https://github.com/google/draco
+.. _Draco: https://github.com/google/draco

doc/stages/writers.raster.rst

@@ -89,3 +89,4 @@ nodata
     [Default: depends on the data_type_.  -9999 for double, float, int and short, 9999 for
     unsigned int and unsigned short, 255 for unsigned char and -128 for char]
 
+.. include:: writer_opts.rst

doc/tutorial/iowa.json

@@ -2,7 +2,7 @@
     "pipeline": [
         {
 "bounds": "([-10425171.940, -10423171.940], [5164494.710, 5166494.710])",
-"filename": "https://s3-us-west-2.amazonaws.com/usgs-lidar-public/IA_FullState",
+"filename": "https://s3-us-west-2.amazonaws.com/usgs-lidar-public/IA_FullState/ept.json",
 "type": "readers.ept",
 "tag": "readdata"
         },

filters/CropFilter.cpp

@@ -202,8 +202,7 @@ void CropFilter::transform(const SpatialReference& srs)
     // if it is missing we assign it from the point data.
     assert(!m_args->m_assignedSrs.empty());
     if (srs.empty() || m_args->m_assignedSrs.empty())
-        throwError("Unable to transform crop geometry to point "
-            "coordinate system.");
+        throwError("Unable to transform crop geometry to point coordinate system.");
 
     for (auto& box : m_boxes)
     {

filters/FarthestPointSamplingFilter.cpp

@@ -72,9 +72,16 @@ PointViewSet FarthestPointSamplingFilter::run(PointViewPtr inView)
 {
     // Return empty PointViewSet if the input PointView has no points.
     PointViewSet viewSet;
-    if (!inView->size() || (inView->size() < m_count))
+    if (!inView->size())
         return viewSet;
 
+    // Return inView if input PointView has fewer than count points.
+    if (inView->size() < m_count)
+    {
+        viewSet.insert(inView);
+        return viewSet;
+    }
+
     PointIdList ids = Segmentation::farthestPointSampling(*inView, m_count);
 
     PointViewPtr outView = inView->makeNew();

filters/GpsTimeConvert.cpp

@@ -102,17 +102,15 @@ void GpsTimeConvert::initialize()
 }
 
 
-std::tm GpsTimeConvert::gpsTime2Date(const double seconds)
+std::tm GpsTimeConvert::gpsTime2Date(int seconds)
 {
     std::tm gpsZero = {};
     gpsZero.tm_year = 80;
     gpsZero.tm_mon = 0;
     gpsZero.tm_mday = 6;
     gpsZero.tm_hour = 0;
     gpsZero.tm_min = 0;
-    gpsZero.tm_sec = 0;
-
-    gpsZero.tm_sec += seconds;
+    gpsZero.tm_sec = seconds;
 
     // refresh struct
     std::mktime(&gpsZero);

filters/GpsTimeConvert.hpp

@@ -57,7 +57,7 @@ class PDAL_DLL GpsTimeConvert : public Filter
     void gpsTime2WeekSeconds(PointView& view);
     void gpsTime2GpsTime(PointView& view);
 
-    std::tm gpsTime2Date(const double seconds);
+    std::tm gpsTime2Date(int seconds);
     int weekStartGpsSeconds(std::tm date);
     void unwrapWeekSeconds(PointView& view);
     void wrapWeekSeconds(PointView& view);