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un coup de black
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alavenant committed Jul 17, 2024
1 parent 8b14397 commit 7c6d248
Showing 1 changed file with 9 additions and 9 deletions.
Original file line number Diff line number Diff line change
Expand Up @@ -100,8 +100,12 @@ def mark_points_to_use_for_digital_models_with_new_dimension(
pipeline,
1,
False,
condition_src="PT_ON_VEGET==1 && ( "+macro.build_condition("Classification", [6, 67]) + " )",
condition_ref="PT_ON_VEGET==0 && ( "+macro.build_condition("Classification", [6, 67]) + " )",
condition_src="PT_ON_VEGET==1 && ( "
+ macro.build_condition("Classification", [6, 67])
+ " )",
condition_ref="PT_ON_VEGET==0 && ( "
+ macro.build_condition("Classification", [6, 67])
+ " )",
condition_out="PT_ON_VEGET=0",
max2d_above=0.5, # ne pas prendre les points qui sont au dessus des points pont (condition_ref)
max2d_below=0.5, # prendre tous les points qui sont en dessous des points pont (condition_ref)
Expand Down Expand Up @@ -175,7 +179,7 @@ def mark_points_to_use_for_digital_models_with_new_dimension(
resolution=0.5,
output_dimension=dtm_dimension,
output_type="max",
where="(Classification==2 || PT_ON_SOL==0 && Classification==9)"
where="(Classification==2 || PT_ON_SOL==0 && Classification==9)",
)

# selection de points DSM (max) sur une grille régulière
Expand Down Expand Up @@ -240,9 +244,7 @@ def mark_points_to_use_for_digital_models_with_new_dimension(
max2d_above=0.5, # ne pas prendre les points qui sont au dessus des points pont (condition_ref)
max2d_below=0.5, # prendre tous les points qui sont en dessous des points pont (condition_ref)
)
pipeline |= pdal.Filter.assign(
value=[f"{dsm_dimension}=0 WHERE PT_ON_BRIDGE==1"]
)
pipeline |= pdal.Filter.assign(value=[f"{dsm_dimension}=0 WHERE PT_ON_BRIDGE==1"])

# 4 - point pour DTM servent au DSM également
# HOMOGENEISER L UTILISATION DE PT_VEG_DSM POUR LES POINT SOL SOUS VEGET AVEC PT_ON_VEGET
Expand All @@ -253,9 +255,7 @@ def mark_points_to_use_for_digital_models_with_new_dimension(
)

# 5 - Ajout de la classe 66 pts virtuels dans DTM et DSM
pipeline |= pdal.Filter.assign(
value=[f"{dtm_dimension}=1 WHERE (Classification==66)"]
)
pipeline |= pdal.Filter.assign(value=[f"{dtm_dimension}=1 WHERE (Classification==66)"])

# 6 - export du nuage et des DSM

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