TensorToMesh: Node to convert a vertices and faces tensor into a mesh.

SConstruct

@@ -1119,12 +1119,12 @@ libraries = {
 		"envAppends" : {
 			"CPPPATH" : [ "$ONNX_ROOT/include" ],
 			"LIBPATH" : [ "$ONNX_ROOT/lib" ],
-			"LIBS" : [ "Gaffer", "GafferImage", "onnxruntime" ],
+			"LIBS" : [ "Gaffer", "GafferImage", "onnxruntime", "GafferScene", "IECoreScene$CORTEX_LIB_SUFFIX" ],
 		},
 		"pythonEnvAppends" : {
 			"CPPPATH" : [ "$ONNX_ROOT/include" ],
 			"LIBPATH" : [ "$ONNX_ROOT/lib" ],
-			"LIBS" : [ "GafferBindings", "GafferImage", "GafferML", "onnxruntime" ],
+			"LIBS" : [ "GafferBindings", "GafferImage", "GafferML", "onnxruntime", "GafferScene", "IECoreScene$CORTEX_LIB_SUFFIX" ],
 		},
 		"requiredOptions" : [ "ONNX_ROOT" ],
 	},

include/GafferML/TensorToMesh.h

@@ -0,0 +1,87 @@
+//////////////////////////////////////////////////////////////////////////
+//
+//  Copyright (c) 2024, Lucien Fostier All rights reserved.
+//
+//  Redistribution and use in source and binary forms, with or without
+//  modification, are permitted provided that the following conditions are
+//  met:
+//
+//      * Redistributions of source code must retain the above
+//        copyright notice, this list of conditions and the following
+//        disclaimer.
+//
+//      * Redistributions in binary form must reproduce the above
+//        copyright notice, this list of conditions and the following
+//        disclaimer in the documentation and/or other materials provided with
+//        the distribution.
+//
+//      * Neither the name of John Haddon nor the names of
+//        any other contributors to this software may be used to endorse or
+//        promote products derived from this software without specific prior
+//        written permission.
+//
+//  THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS
+//  IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
+//  THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
+//  PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
+//  CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
+//  EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+//  PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
+//  PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
+//  LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
+//  NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+//  SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+//
+//////////////////////////////////////////////////////////////////////////
+
+#pragma once
+
+#include "GafferML/Export.h"
+#include "GafferML/TensorPlug.h"
+
+#include "GafferScene/ObjectSource.h"
+#include "Gaffer/TransformPlug.h"
+
+namespace Gaffer
+{
+
+IE_CORE_FORWARDDECLARE( StringPlug )
+
+} // namespace Gaffer
+
+namespace GafferML
+{
+
+class GAFFERML_API TensorToMesh : public GafferScene::ObjectSource
+{
+
+	public :
+
+		explicit TensorToMesh( const std::string &name=defaultName<TensorToMesh>() );
+		~TensorToMesh() override;
+
+		GAFFER_NODE_DECLARE_TYPE( GafferML::TensorToMesh, TensorToMeshTypeId, GafferScene::SceneNode );
+
+		TensorPlug *verticesTensorPlug();
+		const TensorPlug *verticesTensorPlug() const;
+
+		TensorPlug *facesTensorPlug();
+		const TensorPlug *facesTensorPlug() const;
+
+		void affects( const Gaffer::Plug *input, Gaffer::DependencyNode::AffectedPlugsContainer &outputs ) const override;
+
+	protected :
+
+		void hashSource( const Gaffer::Context *context, IECore::MurmurHash &h ) const override;
+		IECore::ConstObjectPtr computeSource( const Gaffer::Context *context ) const override;
+
+	private :
+
+
+		static size_t g_firstPlugIndex;
+
+};
+
+IE_CORE_DECLAREPTR( TensorToMesh )
+
+} // namespace GafferML

include/GafferML/TypeIds.h

@@ -48,6 +48,7 @@ enum TypeId
 	InferenceTypeId = 110455,
 	TensorReaderTypeId = 110456,
 	DataToTensorTypeId = 110457,
+	TensorToMeshTypeId = 110458,
 
 	LastTypeId = 110500
 };

python/GafferML/__init__.py

@@ -39,6 +39,7 @@
 
 __import__( "Gaffer" )
 __import__( "GafferImage" )
+__import__( "GafferScene" )
 
 if hasattr( os, "add_dll_directory" ) :
 	os.add_dll_directory( ( pathlib.Path( os.environ["ONNX_ROOT"] ) / "lib" ).resolve() )

python/GafferMLTest/TensorToMeshTest.py

@@ -0,0 +1,153 @@
+##########################################################################
+#
+#  Copyright (c) 2024, Lucien Fostier All rights reserved.
+#
+#  Redistribution and use in source and binary forms, with or without
+#  modification, are permitted provided that the following conditions are
+#  met:
+#
+#      * Redistributions of source code must retain the above
+#        copyright notice, this list of conditions and the following
+#        disclaimer.
+#
+#      * Redistributions in binary form must reproduce the above
+#        copyright notice, this list of conditions and the following
+#        disclaimer in the documentation and/or other materials provided with
+#        the distribution.
+#
+#      * Neither the name of John Haddon nor the names of
+#        any other contributors to this software may be used to endorse or
+#        promote products derived from this software without specific prior
+#        written permission.
+#
+#  THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS
+#  IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
+#  THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
+#  PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
+#  CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
+#  EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+#  PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
+#  PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
+#  LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
+#  NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+#  SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+#
+##########################################################################
+
+import unittest
+
+import imath
+
+import IECore
+
+import Gaffer
+import GafferTest
+import GafferScene
+import GafferML
+
+class TensorToMeshTest( GafferTest.TestCase ) :
+	def testNoInput( self ) :
+
+		node = GafferML.TensorToMesh()
+		with self.assertRaisesRegex( Gaffer.ProcessException, "Empty Vertices tensor" ) :
+			node["out"].object("/tensorMesh"),
+
+	def test( self ) :
+
+            points = [ 0.0, 0.0, 0.0, 1.0, 1.0, 1.0, 1.0, 0.0, 2.0 ]
+            vertices = IECore.FloatVectorData( points )
+            verticesTensor = GafferML.Tensor( vertices, [ 1, 3, 3 ] )
+            faces = IECore.Int64VectorData( [ 0, 1, 2 ]  )
+            facesTensor = GafferML.Tensor( faces, [ 1, 3 ] )
+            tensorToMesh = GafferML.TensorToMesh()
+            tensorToMesh["vertices"].setValue( verticesTensor )
+            tensorToMesh["faces"].setValue( facesTensor )
+
+            self.assertEqual( tensorToMesh["out"].object( "/" ), IECore.NullObject() )
+            self.assertEqual( tensorToMesh["out"].transform( "/" ), imath.M44f() )
+            self.assertEqual( tensorToMesh["out"].bound( "/" ), imath.Box3f( imath.V3f( 0 ), imath.V3f( 1, 1, 2 ) ) )
+            self.assertEqual( tensorToMesh["out"].childNames( "/" ), IECore.InternedStringVectorData( [ "tensorMesh" ] ) )
+
+            self.assertEqual( tensorToMesh["out"].transform( "/tensorMesh" ), imath.M44f() )
+            self.assertEqual( tensorToMesh["out"].bound( "/tensorMesh" ), imath.Box3f( imath.V3f( 0 ), imath.V3f( 1, 1, 2 ) ) )
+            self.assertEqual( tensorToMesh["out"].childNames( "/tensorMesh" ), IECore.InternedStringVectorData() )
+
+            mesh = tensorToMesh["out"].object( "/tensorMesh" )
+            expectedValue = [component for vec in mesh["P"].data for component in (vec.x, vec.y, vec.z)]
+
+            self.assertEqual( expectedValue, points )
+            self.assertEqual( mesh.numFaces(), 1 )
+            self.assertEqual( mesh.verticesPerFace, IECore.IntVectorData( [ 3 ] ) )
+
+	def testWrongVertexTensorDimension( self ) :
+
+            points = [ 0.0, 0.0, 0.0 , 1.0, 1.0, 0.0, 1.0, 1.0, 2.0 ]
+            vertices = IECore.FloatVectorData( points )
+            verticesTensor = GafferML.Tensor( vertices, [ 3, 3 ] )
+            faces = IECore.Int64VectorData( [ 0, 1, 2 ]  )
+            facesTensor = GafferML.Tensor( faces, [ 1, 3 ] )
+            tensorToMesh = GafferML.TensorToMesh()
+            tensorToMesh["vertices"].setValue( verticesTensor )
+            tensorToMesh["faces"].setValue( facesTensor )
+
+            with self.assertRaisesRegex( Gaffer.ProcessException, "Invalid tensor number of dimensions" ):
+                    mesh = tensorToMesh["out"].object( "/tensorMesh" )
+
+	def testWrongVertexDimension( self ) :
+
+            points = [ 0.0, 0.0, 1.0, 1.0, 1.0, 1.0 ]
+            vertices = IECore.FloatVectorData( points )
+            verticesTensor = GafferML.Tensor( vertices, [ 1, 3, 2 ] )
+            faces = IECore.Int64VectorData( [ 0, 1, 2 ]  )
+            facesTensor = GafferML.Tensor( faces, [ 1, 3 ] )
+            tensorToMesh = GafferML.TensorToMesh()
+            tensorToMesh["vertices"].setValue( verticesTensor )
+            tensorToMesh["faces"].setValue( facesTensor )
+
+            with self.assertRaisesRegex( Gaffer.ProcessException, "Invalid vertices dimensions" ):
+                    mesh = tensorToMesh["out"].object( "/tensorMesh" )
+
+	def testEmptyVertices( self ):
+            tensorToMesh = GafferML.TensorToMesh()
+
+            with self.assertRaisesRegex( Gaffer.ProcessException, "Empty Vertices tensor" ):
+                    mesh = tensorToMesh["out"].object( "/tensorMesh" )
+
+	def testEmptyFaces( self ):
+            points = [ 0.0, 0.0, 0.0, 1.0, 1.0, 1.0, 1.0, 0.0, 2.0 ]
+            vertices = IECore.FloatVectorData( points )
+            verticesTensor = GafferML.Tensor( vertices, [ 1, 3, 3 ] )
+            tensorToMesh = GafferML.TensorToMesh()
+            tensorToMesh["vertices"].setValue( verticesTensor )
+
+            with self.assertRaisesRegex( Gaffer.ProcessException, "Empty Faces tensor" ):
+                    mesh = tensorToMesh["out"].object( "/tensorMesh" )
+
+	def testWrongDataTypeVertices( self ):
+            points = [ 0, 0, 0, 1, 1, 1, 1, 0, 2 ]
+            vertices = IECore.IntVectorData( points )
+            verticesTensor = GafferML.Tensor( vertices, [ 1, 3, 3 ] )
+            faces = IECore.Int64VectorData( [ 0, 1, 2 ]  )
+            facesTensor = GafferML.Tensor( faces, [ 1, 3 ] )
+            tensorToMesh = GafferML.TensorToMesh()
+            tensorToMesh["vertices"].setValue( verticesTensor )
+            tensorToMesh["faces"].setValue( facesTensor )
+
+            with self.assertRaisesRegex( Gaffer.ProcessException, "Invalid data type input for vertices tensor" ):
+                    mesh = tensorToMesh["out"].object( "/tensorMesh" )
+
+	def testWrongDataTypeFaces( self ):
+            points = [ 0.0, 0.0, 0.0, 1.0, 1.0, 1.0, 1.0, 0.0, 2.0 ]
+            vertices = IECore.FloatVectorData( points )
+            verticesTensor = GafferML.Tensor( vertices, [ 1, 3, 3 ] )
+            faces = IECore.IntVectorData( [ 0, 1, 2 ]  )
+            facesTensor = GafferML.Tensor( faces, [ 1, 3 ] )
+            tensorToMesh = GafferML.TensorToMesh()
+            tensorToMesh["vertices"].setValue( verticesTensor )
+            tensorToMesh["faces"].setValue( facesTensor )
+
+            with self.assertRaisesRegex( Gaffer.ProcessException, "Invalid data type input for faces tensor" ):
+                    mesh = tensorToMesh["out"].object( "/tensorMesh" )
+
+if __name__ == "__main__":
+	unittest.main()

python/GafferMLTest/__init__.py

@@ -40,6 +40,7 @@
 from .InferenceTest import InferenceTest
 from .ImageToTensorTest import ImageToTensorTest
 from .TensorToImageTest import TensorToImageTest
+from .TensorToMeshTest import TensorToMeshTest
 
 if __name__ == "__main__":
 	import unittest

python/GafferMLUI/TensorToMeshUI.py

@@ -0,0 +1,58 @@
+##########################################################################
+#
+#  Copyright (c) 2024, Cinesite VFX Ltd. All rights reserved.
+#
+#  Redistribution and use in source and binary forms, with or without
+#  modification, are permitted provided that the following conditions are
+#  met:
+#
+#      * Redistributions of source code must retain the above
+#        copyright notice, this list of conditions and the following
+#        disclaimer.
+#
+#      * Redistributions in binary form must reproduce the above
+#        copyright notice, this list of conditions and the following
+#        disclaimer in the documentation and/or other materials provided with
+#        the distribution.
+#
+#      * Neither the name of John Haddon nor the names of
+#        any other contributors to this software may be used to endorse or
+#        promote products derived from this software without specific prior
+#        written permission.
+#
+#  THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS
+#  IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
+#  THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
+#  PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
+#  CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
+#  EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+#  PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
+#  PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
+#  LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
+#  NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+#  SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+#
+##########################################################################
+
+import Gaffer
+import GafferML
+
+Gaffer.Metadata.registerNode(
+
+	GafferML.TensorToMesh,
+
+	plugs = {
+
+		"vertices" : [
+
+			"nodule:type", "GafferUI::StandardNodule",
+
+		],
+		"faces" : [
+
+			"nodule:type", "GafferUI::StandardNodule",
+
+		],
+
+	}
+)

python/GafferMLUI/__init__.py

@@ -38,5 +38,7 @@
 from . import InferenceUI
 from . import ImageToTensorUI
 from . import TensorToImageUI
+from . import InferenceUI
+from . import TensorToMeshUI
 
 __import__( "IECore" ).loadConfig( "GAFFER_STARTUP_PATHS", subdirectory = "GafferMLUI" )