[nodes] add TracksBuilding node

meshroom/nodes/aliceVision/TracksBuilding.py

@@ -0,0 +1,101 @@
+__version__ = "1.0"
+
+from meshroom.core import desc
+
+
+class TracksBuilding(desc.AVCommandLineNode):
+    commandLine = 'aliceVision_tracksBuilding {allParams}'
+    size = desc.DynamicNodeSize('input')
+
+    category = 'Sparse Reconstruction'
+    documentation = '''
+It fuses all feature matches between image pairs into tracks. Each track represents a candidate point in space, visible from multiple cameras.
+'''
+
+    inputs = [
+        desc.File(
+            name='input',
+            label='SfMData',
+            description='SfMData file.',
+            value='',
+            uid=[0],
+        ),
+        desc.ListAttribute(
+            elementDesc=desc.File(
+                name="featuresFolder",
+                label="Features Folder",
+                description="",
+                value="",
+                uid=[0],
+            ),
+            name="featuresFolders",
+            label="Features Folders",
+            description="Folder(s) containing the extracted features and descriptors."
+        ),
+        desc.ListAttribute(
+            elementDesc=desc.File(
+                name="matchesFolder",
+                label="Matches Folder",
+                description="",
+                value="",
+                uid=[0],
+            ),
+            name="matchesFolders",
+            label="Matches Folders",
+            description="Folder(s) in which computed matches are stored."
+        ),
+        desc.ChoiceParam(
+            name='describerTypes',
+            label='Describer Types',
+            description='Describer types used to describe an image.',
+            value=['dspsift'],
+            values=['sift', 'sift_float', 'sift_upright', 'dspsift', 'akaze', 'akaze_liop', 'akaze_mldb', 'cctag3', 'cctag4', 'sift_ocv', 'akaze_ocv', 'tag16h5'],
+            exclusive=False,
+            uid=[0],
+            joinChar=',',
+        ),
+        desc.IntParam(
+            name='minInputTrackLength',
+            label='Min Input Track Length',
+            description='Minimum track length',
+            value=2,
+            range=(2, 10, 1),
+            uid=[0],
+        ),
+        desc.BoolParam(
+            name='useOnlyMatchesFromInputFolder',
+            label='Use Only Matches From Input Folder',
+            description='Use only matches from the input matchesFolder parameter.\n'
+                        'Matches folders previously added to the SfMData file will be ignored.',
+            value=False,
+            uid=[],
+            advanced=True,
+        ),
+        desc.BoolParam(
+            name='filterTrackForks',
+            label='Filter Track Forks',
+            description='Enable/Disable the track forks removal. A track contains a fork when incoherent matches \n'
+                        'lead to multiple features in the same image for a single track. \n',
+            value=False,
+            uid=[0],
+        ),
+        desc.ChoiceParam(
+            name='verboseLevel',
+            label='Verbose Level',
+            description='Verbosity level (fatal, error, warning, info, debug, trace).',
+            value='info',
+            values=['fatal', 'error', 'warning', 'info', 'debug', 'trace'],
+            exclusive=True,
+            uid=[],
+        )
+    ]
+
+    outputs = [
+        desc.File(
+            name='output',
+            label='Tracks',
+            description='Path to the output tracks file',
+            value=desc.Node.internalFolder + 'tracksFile.json',
+            uid=[],
+        ),
+    ]