V.0 script example

IGNF · May 24, 2024 · 55da6b1 · 55da6b1
1 parent c436a0c
commit 55da6b1
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Showing 2 changed files with 23 additions and 20 deletions.
diff --git a/macro/ex_filtering_points.py b/macro/ex_filtering_points.py
@@ -39,7 +39,7 @@ def parse_args():
 
     ## 2 - sélection des points pour DTM et DSM
 
-    # selection de points DTM (max) sur une grille régulière
+    # selection de points sol (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
@@ -88,7 +88,7 @@ def parse_args():
 
     # 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.gdal(gdaldriver="GTiff", output_type="max", resolution=2.0, filename=args.output_dsm, where=macro.build_condition("Classification", [2,3,4,5,17,64]))
 
     pipeline.execute()
 
diff --git a/macro/ex_filtering_points2.py b/macro/ex_filtering_points2.py
@@ -20,22 +20,25 @@ def parse_args():
 
     pipeline = pdal.Reader.las(args.input)
 
+    # 0 - ajout d'attributs temporaires
+    pipeline |= pdal.Filter.ferry(dimensions=f"=>PT_GRID_DSM, =>PT_VEG_DSM, =>PT_GRID_DTM, =>PT_ON_BRIDGE")
+
+
     ## 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])])
+    pipeline |= pdal.Filter.assign(value=["PT_VEG_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")
+    pipeline = macro.add_radius_assign(pipeline, 1, False, condition_src="Classification==2", condition_ref=macro.build_condition("Classification", [4,5]), condition_out="PT_VEG_DSM=1")
+    pipeline = macro.add_radius_assign(pipeline, 1, False, condition_src="PT_VEG_DSM==1 && Classification==2", condition_ref="Classification==2", condition_out="PT_VEG_DSM=0")
 
     # 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")
+    pipeline = macro.add_radius_assign(pipeline, 1, False, condition_src="Classification==3", condition_ref="Classification==5", condition_out="PT_VEG_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")
+    # max des points de veget (PT_VEG_DSM==1) sur une grille régulière :
+    pipeline |= pdal.Filter.gridDecimation(resolution=0.75, value="PT_GRID_DSM=1", output_type="max", where="PT_VEG_DSM==1")
 
 
     ## 2 - sélection des points pour DTM et DSM
@@ -44,29 +47,29 @@ def parse_args():
     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]))
+    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]) + ") || PT_GRID_DSM==1")
 
-    # assigne des points sol sélectionnés : les points proches de la végétation, des ponts, de l'eau, 64 et 100
+    # assigne des points sol sélectionnés : les points proches de la végétation, des ponts, de l'eau, 64
     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")
+                                       condition_ref=macro.build_condition("Classification", [4,5,6,9,17,64]),
+                                       condition_out="PT_GRID_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")
+    pipeline |= pdal.Filter.assign(value=["PT_GRID_DSM = 0 WHERE " + macro.build_condition("Classification", [2,3,4,5,9]) + " && PT_ON_BRIDGE==1"])
 
-    # 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)
+    # 4 - export du nuage et des DSM
 
-    # 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_las)
+    pipeline |= pdal.Writer.gdal(gdaldriver="GTiff", output_type="max", resolution=2.0, filename=args.output_dtm, where="PT_GRID_DTM==1")
+    pipeline |= pdal.Writer.gdal(gdaldriver="GTiff", output_type="max", resolution=2.0, filename=args.output_dsm, where="PT_GRID_DTM==1 || PT_GRID_DSM==1")
 
     pipeline.execute()