add comment to example + try to recode example

macro/ex_filtering_points.py

@@ -9,7 +9,9 @@
 def parse_args():
     parser = argparse.ArgumentParser("Tool to apply pdal pipelines to modify classification")
     parser.add_argument("--input", "-i", type=str, required=True, help="Input las file")
-    parser.add_argument("--output", "-o", type=str, required=True, help="Output las file")
+    parser.add_argument("--output_las", "-o", type=str, required=True, help="Output cloud las file")
+    parser.add_argument("--output_dsm", "-s", type=str, required=True, help="Output dsm tiff file")
+    parser.add_argument("--output_dtm", "-t", type=str, required=True, help="Output dtm tiff file")
     return parser.parse_args()
 
 
@@ -18,38 +20,75 @@ def parse_args():
 
     pipeline = pdal.Reader.las(args.input)
 
-    # step 1 a 9
-    pipeline = macro.add_radius_assign(pipeline, 1, False, "Classification==2", macro.build_condition("Classification", [4,5]), "Classification=102")
-    pipeline = macro.add_radius_assign(pipeline, 1, False, "Classification==102", "Classification==2", "Classification=2")
-    pipeline = macro.add_radius_assign(pipeline, 1, False, "Classification==3", "Classification==5", "Classification=103")
+    ## 1 - recherche des points max de végétation (4,5) sur une grille régulière, avec prise en compte des points sol (2) et basse
+    ##     vegetation (3) proche de la végétation : on les affecte en 100
+
+    # bouche trou : assigne les points sol en 102 à l'intérieur de la veget (4,5)
+    pipeline = macro.add_radius_assign(pipeline, 1, False, condition_src="Classification==2", condition_ref=macro.build_condition("Classification", [4,5]), condition_out="Classification=102")
+    pipeline = macro.add_radius_assign(pipeline, 1, False, condition_src="Classification==102", condition_ref="Classification==2", condition_out="Classification=2")
+
+    # selection des points de veget basse proche de la veget haute : assigne 103
+    pipeline = macro.add_radius_assign(pipeline, 1, False, condition_src="Classification==3", condition_ref="Classification==5", condition_out="Classification=103")
+
+    # max des points de veget (et surement veget - 102,103) sur une grille régulière : assigne 100
     pipeline |= pdal.Filter.gridDecimation(resolution=0.75, value="Classification=100", output_type="max", where=macro.build_condition("Classification", [4,5,102,103]))
+
+    # remise à zero des codes 102 et 103
     pipeline |= pdal.Filter.assign(value="Classification=2", where="Classification==102")
     pipeline |= pdal.Filter.assign(value="Classification=3", where="Classification==103")
+
+    ## 2 - sélection des points pour DTM et DSM
+
+    # selection de points DTM (max) sur une grille régulière
     pipeline |= pdal.Filter.gridDecimation(resolution=0.5, value="Classification=102", output_type="max", where="Classification==2")
+
+    # selection de points DSM (max) sur une grille régulière
     pipeline |= pdal.Filter.gridDecimation(resolution=0.5, value="Classification=200", output_type="max", where=macro.build_condition("Classification", [2,3,4,5,6,9,17,64,100]))
-    pipeline = macro.add_radius_assign(pipeline, 1.5, False, "Classification==102", macro.build_condition("Classification", [4,5,6,9,17,64,100]), "Classification=100")
+
+    # assigne des points sol sélectionnés (102) en 100 : les points proches de la végaétation, des ponts, de l'eau et 64
+    pipeline = macro.add_radius_assign(pipeline, 1.5, False, condition_src="Classification==102",
+                                       condition_ref=macro.build_condition("Classification", [4,5,6,9,17,64,100]), condition_out="Classification=100")
+
+    # remise à zero du code 102
     pipeline |= pdal.Filter.assign(value="Classification=2", where="Classification==102")
 
-    # step 10
-    pipeline = macro.add_radius_assign(pipeline, 1.5, False, "Classification==2", "Classification==17", "Classification=102")
-    pipeline = macro.add_radius_assign(pipeline, 1.5, False, "Classification==102", macro.build_condition("Classification", [2,3,4,5]), "Classification=2")
+    ## 3 - gestion des ponts
+
+
+
+    # bouche trou : on élimine les points sol (2) au milieu du pont en les mettant à 102
+    pipeline = macro.add_radius_assign(pipeline, 1.5, False, condition_src="Classification==2", condition_ref="Classification==17", condition_out="Classification=102")
+    pipeline = macro.add_radius_assign(pipeline, 1.5, False, condition_src="Classification==102",
+                                       condition_ref=macro.build_condition("Classification", [2,3,4,5]), condition_out="Classification=2")
+
+    # bouche trou : on élimine les points basse végétation (3) au milieu du pont en les mettant à 103
+    pipeline = macro.add_radius_assign(pipeline, 1.5, False, condition_src="Classification==3", condition_ref="Classification==17", condition_out="Classification=103")
+    pipeline = macro.add_radius_assign(pipeline, 1.5, False, condition_src="Classification==103",
+                                       condition_ref=macro.build_condition("Classification", [2,3,4,5]), condition_out="Classification=3")
+
+    # bouche trou : on élimine les points moyenne végétation (4) au milieu du pont en les mettant à 104
+    pipeline = macro.add_radius_assign(pipeline, 1.5, False, condition_src="Classification==4", condition_ref="Classification==17", condition_out="Classification=104")
+    pipeline = macro.add_radius_assign(pipeline, 1.5, False, condition_src="Classification==104",
+                                       condition_ref=macro.build_condition("Classification", [2,3,4,5]), condition_out="Classification=4")
+
+    # bouche trou : on élimine les points haute végétation (5) au milieu du pont en les mettant à 105
+    pipeline = macro.add_radius_assign(pipeline, 1.5, False, condition_src="Classification==5", condition_ref="Classification==17", condition_out="Classification=105")
+    pipeline = macro.add_radius_assign(pipeline, 1.5, False, condition_src="Classification==105",
+                                       condition_ref=macro.build_condition("Classification", [2,3,4,5]), condition_out="Classification=5")
 
-    # step 11
-    pipeline = macro.add_radius_assign(pipeline, 1.5, False, "Classification==3", "Classification==17", "Classification=103")
-    pipeline = macro.add_radius_assign(pipeline, 1.5, False, "Classification==103", macro.build_condition("Classification", [2,3,4,5]), "Classification=3")
+    # bouche trou : on élimine les points eau (9) au milieu du pont en les mettant à 109
+    pipeline = macro.add_radius_assign(pipeline, 1.5, False, condition_src="Classification==9", condition_ref="Classification==17", condition_out="Classification=109")
+    pipeline = macro.add_radius_assign(pipeline, 1.5, False, condition_src="Classification==109",
+                                       condition_ref="Classification==9", condition_out="Classification=9")
 
-    # step 12
-    pipeline = macro.add_radius_assign(pipeline, 1.5, False, "Classification==4", "Classification==17", "Classification=104")
-    pipeline = macro.add_radius_assign(pipeline, 1.5, False, "Classification==104", macro.build_condition("Classification", [2,3,4,5]), "Classification=4")
+    # step 15 et supression des points ??
 
-    # step 13
-    pipeline = macro.add_radius_assign(pipeline, 1.5, False, "Classification==5", "Classification==17", "Classification=105")
-    pipeline = macro.add_radius_assign(pipeline, 1.5, False, "Classification==105", macro.build_condition("Classification", [2,3,4,5]), "Classification=5")
+    # 4 - export du nuage
+    pipeline |= pdal.Writer.las(extra_dims="all",minor_version=4,dataformat_id=6,filename=args.output_las)
 
-    # step 14
-    pipeline = macro.add_radius_assign(pipeline, 1.5, False, "Classification==9", "Classification==17", "Classification=109")
-    pipeline = macro.add_radius_assign(pipeline, 1.5, False, "Classification==109", "Classification==9", "Classification=9")
+    # export des DSM/DTM
+    pipeline |= pdal.Writer.gdal(gdaldriver="GTiff", output_type="max", resolution=2.0, filename=args.output_dtm, where=macro.build_condition("Classification", [2,66]))
+    pipeline |= pdal.Writer.gdal(gdaldriver="GTiff", output_type="max", resolution=2.0, filename=args.output_dsm, where=macro.build_condition("Classification", [2,3,4,5,5,17,64]))
 
-    pipeline |= pdal.Writer.las(extra_dims="all",minor_version=4,dataformat_id=6,filename=args.output)
     pipeline.execute()
 

macro/ex_filtering_points2.py

@@ -0,0 +1,72 @@
+import argparse
+import pdal
+import macro
+
+"""
+This tool shows how to use functions of macro in a pdal pipeline
+"""
+
+def parse_args():
+    parser = argparse.ArgumentParser("Tool to apply pdal pipelines to modify classification")
+    parser.add_argument("--input", "-i", type=str, required=True, help="Input las file")
+    parser.add_argument("--output_las", "-o", type=str, required=True, help="Output cloud las file")
+    parser.add_argument("--output_dsm", "-s", type=str, required=True, help="Output dsm tiff file")
+    parser.add_argument("--output_dtm", "-t", type=str, required=True, help="Output dtm tiff file")
+    return parser.parse_args()
+
+
+if __name__ == "__main__":
+    args = parse_args()
+
+    pipeline = pdal.Reader.las(args.input)
+
+    ## 1 - recherche des points max de végétation (4,5) sur une grille régulière, avec prise en compte des points sol (2) et basse
+    ##     vegetation (3) proche de la végétation
+    ##     pour le calcul du DSM
+
+    pipeline |= pdal.Filter.ferry(dimensions=f"=>PT_GRID_DSM, =>PT_DSM, =>PT_GRID_DTM")
+    pipeline |= pdal.Filter.assign(value=["PT_DSM = 1 WHERE " + macro.build_condition("Classification", [4,5])])
+
+    # bouche trou : assigne les points sol à l'intérieur de la veget (4,5)
+    pipeline = macro.add_radius_assign(pipeline, 1, False, condition_src="Classification==2", condition_ref=macro.build_condition("Classification", [4,5]), condition_out="PT_DSM=1")
+    pipeline = macro.add_radius_assign(pipeline, 1, False, condition_src="PT_DSM==1 && Classification==2", condition_ref="Classification==2", condition_out="Classification=2")
+
+    # selection des points de veget basse proche de la veget haute
+    pipeline = macro.add_radius_assign(pipeline, 1, False, condition_src="Classification==3", condition_ref="Classification==5", condition_out="PT_DSM=1")
+
+    # max des points de veget (et surement veget) sur une grille régulière :
+    pipeline |= pdal.Filter.gridDecimation(resolution=0.75, value="PT_GRID_DSM=1", output_type="max", where="PT_DSM==1")
+
+
+    ## 2 - sélection des points pour DTM et DSM
+
+    # selection de points DTM (max) sur une grille régulière
+    pipeline |= pdal.Filter.gridDecimation(resolution=0.5, value="PT_GRID_DTM=1", output_type="max", where="Classification==2")
+
+    # selection de points DSM (max) sur une grille régulière
+    pipeline |= pdal.Filter.gridDecimation(resolution=0.5, value="PT_GRID_DSM=1", output_type="max", where=macro.build_condition("Classification", [2,3,4,5,6,9,17,64,100]))
+
+    # assigne des points sol sélectionnés : les points proches de la végétation, des ponts, de l'eau, 64 et 100
+    pipeline = macro.add_radius_assign(pipeline, 1.5, False, condition_src="PT_GRID_DTM==1",
+                                       condition_ref= "(" + macro.build_condition("Classification", [4,5,6,9,17,64]) + ") && PT_GRID_DSM==1",
+                                       condition_out="PT_DSM=1")
+
+
+    ## 3 - gestion des ponts
+    #      bouche trou : on filtre les points (2,3,4,5,9) au milieu du pont en les mettant à PT_ON_BRIDGE=1
+    pipeline |= pdal.Filter.ferry(dimensions=f"=>PT_ON_BRIDGE")
+    pipeline = macro.add_radius_assign(pipeline, 1.5, False, condition_src=macro.build_condition("Classification", [2,3,4,5,9]), condition_ref="Classification==17", condition_out="PT_ON_BRIDGE=1")
+    pipeline = macro.add_radius_assign(pipeline, 1.5, False, condition_src="PT_ON_BRIDGE==1",
+                                       condition_ref=macro.build_condition("Classification", [2,3,4,5]), condition_out="PT_ON_BRIDGE=0")
+
+    # step 15 et supression des points ??
+
+    # 4 - export du nuage
+    pipeline |= pdal.Writer.las(extra_dims="all", minor_version=4, dataformat_id=6, filename=args.output_las)
+
+    # export des DSM/DTM
+    pipeline |= pdal.Writer.gdal(gdaldriver="GTiff", output_type="max", resolution=2.0, filename=args.output_dtm, where=macro.build_condition("Classification", [2,66]))
+    pipeline |= pdal.Writer.gdal(gdaldriver="GTiff", output_type="max", resolution=2.0, filename=args.output_dsm, where=macro.build_condition("Classification", [2,3,4,5,5,17,64]))
+
+    pipeline.execute()
+