Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Update script mnx #19

Merged
merged 4 commits into from
Jul 18, 2024
Merged

Update script mnx #19

Changes from 2 commits
Commits
Show all changes
4 commits
Select commit Hold shift + click to select a range
e052095
new version algo
alavenant Jul 17, 2024
75e8f0c
un coup de black
alavenant Jul 17, 2024
14a1591
update code
alavenant Jul 17, 2024
bae2e2b
fix mnx script
leavauchier Jul 18, 2024
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
75 changes: 55 additions & 20 deletions pdal_ign_macro/mark_points_to_use_for_digital_models_with_new_dimension.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -89,14 +89,14 @@ def define_marking_pipeline(input_las, output_las, dsm_dimension, dtm_dimension)
pipeline = pdal.Pipeline() | pdal.Reader.las(input_las)

# 0 - ajout de dimensions temporaires et de sortie
temporary_dimensions = ["PT_VEG_DSM", "PT_ON_BRIDGE", "PT_ON_BUILDING", "PT_ON_VEGET"]
temporary_dimensions = ["PT_VEG_DSM", "PT_ON_BRIDGE", "PT_ON_BUILDING", "PT_ON_VEGET", "PT_ON_SOL"]
added_dimensions = [dtm_dimension, dsm_dimension] + temporary_dimensions

pipeline |= pdal.Filter.ferry(dimensions="=>" + ", =>".join(added_dimensions))

# 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
# vegetation (3) proches de la végétation
# pour le calcul du DSM

pipeline |= pdal.Filter.assign(
Expand All @@ -116,7 +116,7 @@ def define_marking_pipeline(input_las, output_las, dsm_dimension, dtm_dimension)
pipeline,
1,
False,
condition_src=macro.build_condition("Classification", [6, 17]),
condition_src=macro.build_condition("Classification", [6, 9, 17, 67]),
condition_ref=macro.build_condition("Classification", [4, 5]),
condition_out="PT_ON_VEGET=1",
max2d_above=0, # ne pas prendre les points qui sont au dessus des points pont (condition_ref)
Expand All @@ -134,8 +134,12 @@ def define_marking_pipeline(input_las, output_las, dsm_dimension, dtm_dimension)
pipeline,
1,
False,
condition_src="PT_ON_VEGET==1 && Classification==6",
condition_ref="Classification==6 && PT_ON_VEGET==0",
condition_src="PT_ON_VEGET==1 && ( "
alavenant marked this conversation as resolved.
Show resolved Hide resolved
+ 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 All @@ -150,6 +154,16 @@ def define_marking_pipeline(input_las, output_las, dsm_dimension, dtm_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 = macro.add_radius_assign(
pipeline,
1,
False,
condition_src="PT_ON_VEGET==1 && Classification==9",
condition_ref="Classification==9 && PT_ON_VEGET==0",
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)
)

# selection des points de veget basse proche de la veget haute
pipeline = macro.add_radius_assign(
Expand All @@ -169,13 +183,37 @@ def define_marking_pipeline(input_las, output_las, dsm_dimension, dtm_dimension)

# 2 - sélection des points pour DTM et DSM

###########################################################################################################################################
# Voir pour l'eau sous le sol dans les dévers corse
pipeline = macro.add_radius_assign(
pipeline,
1.25,
False,
condition_src="Classification==9",
condition_ref="Classification==2",
condition_out="PT_ON_SOL=1",
max2d_above=0,
max2d_below=900,
alavenant marked this conversation as resolved.
Show resolved Hide resolved
)
pipeline = macro.add_radius_assign(
pipeline,
1,
False,
condition_src="PT_ON_SOL==1",
condition_ref="PT_ON_SOL==0 && Classification==9",
condition_out="PT_ON_SOL=0",
max2d_above=0.5,
max2d_below=0.5,
)
###########################################################################################################################################

# selection de points DTM (max) sur une grille régulière
# TODO: remplacer par GridDecimation une fois le correctif mergé dans PDAL
pipeline |= pdal.Filter.grid_decimation_deprecated(
resolution=0.5,
output_dimension=dtm_dimension,
output_type="max",
where="Classification==2",
where="(Classification==2 || PT_ON_SOL==0 && Classification==9)",
)

# selection de points DSM (max) sur une grille régulière
Expand All @@ -189,13 +227,13 @@ def define_marking_pipeline(input_las, output_las, dsm_dimension, dtm_dimension)
+ f") || {dsm_dimension}==1)",
)

# assigne des points sol sélectionnés : les points proches de la végétation, des ponts, de l'eau, 64
# assigne des points sol sélectionnés : les points proches de la végétation, des ponts, de l'eau, 67
pipeline = macro.add_radius_assign(
pipeline,
1.5,
False,
condition_src=f"{dtm_dimension}==1",
condition_ref=macro.build_condition("Classification", [4, 5, 6, 9, 17, 64]),
condition_ref=macro.build_condition("Classification", [4, 5, 6, 17, 67]),
condition_out=f"{dsm_dimension}=0",
)
# Test proximité batiment
Expand All @@ -217,12 +255,12 @@ def define_marking_pipeline(input_las, output_las, dsm_dimension, dtm_dimension)
condition_out=f"{dsm_dimension}=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
# bouche trou : on filtre les points au milieu du pont en les mettant à PT_ON_BRIDGE=1
pipeline = macro.add_radius_assign(
pipeline,
1.5,
False,
condition_src=macro.build_condition("Classification", [2, 3, 4, 5, 6, 9]),
condition_src=macro.build_condition("Classification", [2, 3, 4, 5, 6, 9, 67]),
condition_ref="Classification==17",
condition_out="PT_ON_BRIDGE=1",
max2d_above=0, # ne pas prendre les points qui sont au dessus des points pont (condition_ref)
Expand All @@ -232,31 +270,28 @@ def define_marking_pipeline(input_las, output_las, dsm_dimension, dtm_dimension)
pipeline,
1.25,
False,
# condition_ref=macro.build_condition("Classification", [2, 3, 4, 5]),
condition_src="PT_ON_BRIDGE==1",
condition_ref="PT_ON_BRIDGE==0 && ( "
+ macro.build_condition("Classification", [2, 3, 4, 5, 6, 9])
+ macro.build_condition("Classification", [2, 3, 4, 5, 6, 9, 67])
+ " )",
condition_out="PT_ON_BRIDGE=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)
)
# pipeline |= pdal.Filter.assign(value=[f"{dsm_dimension}=0 WHERE (PT_ON_BRIDGE==1 && NOT(Classification==17))"])
pipeline |= pdal.Filter.assign(
value=[f"{dsm_dimension}=0 WHERE PT_ON_BRIDGE==1"]
# value=["dsm_marker=0 WHERE (PT_ON_BRIDGE==1 AND ( " + macro.build_condition("Classification", [2,3,4,5,6,9]) + " ))"]
)
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
pipeline |= pdal.Filter.assign(
value=[
f"{dsm_dimension}=1 WHERE ({dtm_dimension}==1 && PT_VEG_DSM==0 && PT_ON_BRIDGE==0 && PT_ON_BUILDING==0 )"
f"{dsm_dimension}=1 WHERE ({dtm_dimension}==1 && PT_VEG_DSM==0 && PT_ON_BRIDGE==0 && PT_ON_BUILDING==0 && PT_ON_VEGET==0)"
]
)
# ERREUR EN 4!###############################################################################################!
# 5 - export du nuage et des DSM

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

# 6 - export du nuage et des DSM
pipeline |= pdal.Writer.las(extra_dims="all", forward="all", filename=output_las)

return pipeline, temporary_dimensions
Expand Down