def testChannelData( self ) : e = GafferImage.Empty() e["format"].setValue( GafferImage.Format( 2048, 1156, 1. ) ) for chan in [ "R", "G", "B", "A", "Z", "ZBack" ] : self.assertEqual( e["out"].channelData( chan, imath.V2i( 0 ) ), IECore.FloatVectorData( [] ) )
def testMismatchThrows(self):
deep = GafferImage.Empty()
flat = GafferImage.Constant()
mix = GafferImage.Mix()
mix["mix"].setValue(0.5)
mix["in"][0].setInput(flat["out"])
mix["in"][1].setInput(flat["out"])
self.assertNotEqual(GafferImage.ImageAlgo.imageHash(mix["out"]),
GafferImage.ImageAlgo.imageHash(flat["out"]))
GafferImage.ImageAlgo.tiles(mix["out"])
mix["in"][0].setInput(deep["out"])
six.assertRaisesRegex(
self, RuntimeError,
'Mix.out.deep : Cannot mix between deep and flat image.',
GafferImage.ImageAlgo.tiles, mix["out"])
mix["in"][0].setInput(flat["out"])
mix["in"][1].setInput(deep["out"])
six.assertRaisesRegex(
self, RuntimeError,
'Mix.out.deep : Cannot mix between deep and flat image.',
GafferImage.ImageAlgo.tiles, mix["out"])
mix["in"][0].setInput(deep["out"])
GafferImage.ImageAlgo.tiles(mix["out"])
def testSampleOffsets( self ) : ts = GafferImage.ImagePlug.tileSize() e = GafferImage.Empty() e["format"].setValue( GafferImage.Format( 2048, 1156, 1. ) ) self.assertEqual( e["out"].sampleOffsets( imath.V2i( 0 ) ), IECore.IntVectorData( [ 0 ] * ts * ts ) )
def assertRaisesDeepNotSupported( self, node ) : flat = GafferImage.Constant() node["in"].setInput( flat["out"] ) self.assertNotEqual( GafferImage.ImageAlgo.imageHash( flat["out"] ), GafferImage.ImageAlgo.imageHash( node["out"] ) ) deep = GafferImage.Empty() node["in"].setInput( deep["out"] ) six.assertRaisesRegex( self, RuntimeError, 'Deep data not supported in input "in*', GafferImage.ImageAlgo.image, node["out"] )
def testFormatHash( self ) : # Check that the data and sampleOffsets hashes don't change when the format does. e = GafferImage.Empty() e["format"].setValue( GafferImage.Format( 2048, 1156, 1. ) ) channelDataHash1 = e["out"].channelDataHash( "R", imath.V2i( 0 ) ) sampleOffsetsHash1 = e["out"].sampleOffsetsHash( imath.V2i( 0 ) ) e["format"].setValue( GafferImage.Format( 1920, 1080, 1. ) ) channelDataHash2 = e["out"].channelDataHash( "R", imath.V2i( 0 ) ) sampleOffsetsHash2 = e["out"].sampleOffsetsHash( imath.V2i( 0 ) ) self.assertEqual( channelDataHash1, channelDataHash2 ) self.assertEqual( sampleOffsetsHash1, sampleOffsetsHash2 )
def testFormatDependencies( self ) : e = GafferImage.Empty() self.assertEqual( e.affects( e["format"]["displayWindow"]["min"]["x"] ), [ e["out"]["format"], e["out"]["dataWindow"] ], ) self.assertEqual( e.affects( e["format"]["pixelAspect"] ), [ e["out"]["format"] ], )
def testTileHashes( self ) : # Test that two tiles within the image have the same hash. e = GafferImage.Empty() e["format"].setValue( GafferImage.Format( 2048, 1156, 1. ) ) self.assertEqual( e["out"].channelDataHash( "R", imath.V2i( 0 ) ), e["out"].channelDataHash( "R", imath.V2i( GafferImage.ImagePlug().tileSize() ) ), ) self.assertEqual( e["out"].sampleOffsetsHash( imath.V2i( 0 ) ), e["out"].sampleOffsetsHash( imath.V2i( GafferImage.ImagePlug().tileSize() ) ), )
def testNonFlatThrows( self ) : deep = GafferImage.Empty() flat = GafferImage.Constant() merge = GafferImage.Merge() merge["in"][0].setInput( flat["out"] ) merge["in"][1].setInput( flat["out"] ) self.assertNotEqual( GafferImage.ImageAlgo.imageHash( merge["out"] ), GafferImage.ImageAlgo.imageHash( flat["out"] ) ) merge["in"][0].setInput( deep["out"] ) six.assertRaisesRegex( self, RuntimeError, 'Deep data not supported in input "in.in0"', GafferImage.ImageAlgo.image, merge["out"] ) merge["in"][0].setInput( flat["out"] ) merge["in"][1].setInput( deep["out"] ) six.assertRaisesRegex( self, RuntimeError, 'Deep data not supported in input "in.in1"', GafferImage.ImageAlgo.image, merge["out"] )
def testTileIdentity( self ) : e = GafferImage.Empty() e["format"].setValue( GafferImage.Format( 2048, 1156, 1. ) ) # The channelData() binding returns a copy by default, so we wouldn't # expect two tiles to be referencing the same object. self.assertFalse( e["out"].channelData( "R", imath.V2i( 0 ) ).isSame( e["out"].channelData( "R", imath.V2i( GafferImage.ImagePlug.tileSize() ) ) ) ) # But behind the scenes we do want them to be the same, so # check that that is the case. self.assertTrue( e["out"].channelData( "R", imath.V2i( 0 ), _copy = False ).isSame( e["out"].channelData( "R", imath.V2i( GafferImage.ImagePlug.tileSize() ), _copy = False ) ) )
def testOccludeAll( self ) : representativeImage = GafferImage.ImageReader() representativeImage["fileName"].setValue( self.representativeImagePath ) constantNodes = self.__getConstant( 0.1, 0.2, 0.3, 1, -10, -10, imath.V2i( 150, 100 ) ) empty = GafferImage.Empty() empty["format"].setValue( GafferImage.Format( imath.Box2i( imath.V2i( 0 ), imath.V2i( 150, 100 ) ), 1 ) ) deepConstant = GafferImage.DeepMerge() deepConstant["in"][0].setInput( constantNodes[1]["out"] ) deepConstant["in"][1].setInput( empty["out"] ) deepMerge = GafferImage.DeepMerge() deepMerge["in"][0].setInput( representativeImage["out"] ) deepMerge["in"][1].setInput( deepConstant["out"] ) deepState = GafferImage.DeepState() deepState["in"].setInput( deepMerge["out"] ) deepState["pruneOccluded"].setValue( True ) self.assertEqual( GafferImage.ImageAlgo.tiles( constantNodes[1]["out"] ), GafferImage.ImageAlgo.tiles( constantNodes[1]["out"] ) )
def testPracticalTransparencyPrune( self ) : representativeImage = GafferImage.ImageReader() representativeImage["fileName"].setValue( self.representativeImagePath ) empty = GafferImage.Empty() empty["format"].setValue( GafferImage.Format( imath.Box2i( imath.V2i( 0 ), imath.V2i( 150, 100 ) ), 1 ) ) properlyLabelledIn = GafferImage.DeepMerge() properlyLabelledIn["in"][0].setInput( representativeImage["out"] ) properlyLabelledIn["in"][1].setInput( empty["out"] ) # The representative image from Arnold actually contains overlaps one floating point epsilon in width. # Get rid of those, and then we can see the sampleCounts change in a predictable way actuallyTidyIn = GafferImage.DeepState() actuallyTidyIn["in"].setInput( properlyLabelledIn["out"] ) prune = GafferImage.DeepState() prune["in"].setInput( actuallyTidyIn["out"] ) prune["pruneTransparent"].setValue( True ) flatRef = GafferImage.DeepState() flatRef["in"].setInput( actuallyTidyIn["out"] ) flatRef["deepState"].setValue( GafferImage.DeepState.TargetState.Flat ) flatPrune = GafferImage.DeepState() flatPrune["in"].setInput( prune["out"] ) flatPrune["deepState"].setValue( GafferImage.DeepState.TargetState.Flat ) diff = GafferImage.Merge() diff['operation'].setValue( GafferImage.Merge.Operation.Difference ) diff['in'][0].setInput( flatPrune["out"] ) diff['in'][1].setInput( flatRef["out"] ) diffStats = GafferImage.ImageStats() diffStats["in"].setInput( diff["out"] ) diffStats["area"].setValue( diff["out"].dataWindow() ) origCounts = GafferImage.DeepSampleCounts() origCounts["in"].setInput( actuallyTidyIn["out"] ) prunedCounts = GafferImage.DeepSampleCounts() prunedCounts["in"].setInput( prune["out"] ) diffCounts = GafferImage.Merge() diffCounts["operation"].setValue( GafferImage.Merge.Operation.Subtract ) diffCounts["in"][0].setInput( origCounts["out"] ) diffCounts["in"][1].setInput( prunedCounts["out"] ) diffCountsStats = GafferImage.ImageStats() diffCountsStats["in"].setInput( diffCounts["out"] ) diffCountsStats["area"].setValue( diffCounts["out"].dataWindow() ) self.assertEqual( diffCountsStats["max"].getValue()[0], 0 ) # For some reason, our test data from Arnold has a bunch of transparent pixels to start with, # so we've got some stuff to throw out self.assertLess( diffCountsStats["min"].getValue()[0], -20 ) self.assertLess( diffCountsStats["min"].getValue()[0], -0.26 ) # We've got some moderate error introduced by discarding transparent. Why is it so large? # Looks like those transparent pixels are slightly emissive for i in range( 4 ): self.assertLessEqual( diffStats["max"].getValue()[i], [0.00001,0.00001,0.00001,0][i] ) self.assertGreaterEqual( diffStats["max"].getValue()[i], [0.000001,0.000001,0.000001,0][i] ) # By premulting/unpremulting, we zero out samples with no alpha premultiply = GafferImage.Premultiply() premultiply["in"].setInput( actuallyTidyIn["out"] ) unpremultiply = GafferImage.Unpremultiply() unpremultiply["in"].setInput( premultiply["out"] ) flatRef["in"].setInput( unpremultiply["out"] ) prune["in"].setInput( unpremultiply["out"] ) # That gets us a couple extra digits of matching - this is more like what we would expect based # on floating point precision for i in range( 4 ): self.assertLessEqual( diffStats["max"].getValue()[i], [0.0000005,0.0000005,0.0000005,0][i] ) # But now lets hack it to really make some transparent pixels grade = GafferImage.Grade() grade["in"].setInput( actuallyTidyIn["out"] ) grade["channels"].setValue( '[A]' ) grade["multiply"]["a"].setValue( 1.5 ) grade["offset"]["a"].setValue( -0.5 ) premultiply['in'].setInput( grade["out"] ) # Now we can kill lots of samples self.assertEqual( diffCountsStats["max"].getValue()[0], 0 ) self.assertLess( diffCountsStats["min"].getValue()[0], -200 ) self.assertLess( diffCountsStats["min"].getValue()[0], -10 ) # And the flattened results still match closely for i in range( 4 ): self.assertLessEqual( diffStats["max"].getValue()[i], [0.0000005,0.0000005,0.0000005,0.0000002][i] )
def testDeep( self ) : empty = GafferImage.Empty() empty["format"].setValue( GafferImage.Format( imath.Box2i( imath.V2i( 0 ), imath.V2i( 511 ) ), 1 ) ) self.assertEqual( empty["out"]["deep"].getValue(), True )
def testChannelNames( self ) : e = GafferImage.Empty() self.assertEqual( e["out"]["channelNames"].getValue(), IECore.StringVectorData( [] ) )
def testEnableBehaviour( self ) : e = GafferImage.Empty() self.assertTrue( e.enabledPlug().isSame( e["enabled"] ) ) self.assertEqual( e.correspondingInput( e["out"] ), None ) self.assertEqual( e.correspondingInput( e["format"] ), None )
