New node for semantic image segmentation

meshroom/nodes/aliceVision/FeatureExtraction.py

@@ -1,4 +1,4 @@
-__version__ = "1.2"
+__version__ = "1.3"
 
 from meshroom.core import desc
 
@@ -45,6 +45,22 @@ class FeatureExtraction(desc.AVCommandLineNode):
             value="",
             uid=[0],
         ),
+        desc.ChoiceParam(
+            name="maskExtension",
+            label="Mask Extension",
+            description="File extension for masks.",
+            value="png",
+            values=["png", "exr", "jpg"],
+            exclusive=True,
+            uid=[0],
+        ),
+        desc.BoolParam(
+            name="maskInvert",
+            label="Invert Masks",
+            description="Invert mask values.",
+            value=False,
+            uid=[0],
+        ),
         desc.ChoiceParam(
             name="describerTypes",
             label="Describer Types",

meshroom/nodes/aliceVision/ImageSegmentation.py

@@ -0,0 +1,89 @@
+__version__ = "1.0"
+
+from meshroom.core import desc
+
+
+class ImageSegmentation(desc.AVCommandLineNode):
+    commandLine = 'aliceVision_imageSegmentation {allParams}'
+    size = desc.DynamicNodeSize('input')
+    gpu = desc.Level.NORMAL
+    parallelization = desc.Parallelization(blockSize=50)
+    commandLineRange = '--rangeStart {rangeStart} --rangeSize {rangeBlockSize}'
+
+    category = 'Utils'
+    documentation = '''
+Generate a mask with segmented labels for each pixel.
+'''
+
+    inputs = [
+        desc.File(
+            name="input",
+            label="Input",
+            description="SfMData file input.",
+            value="",
+            uid=[0],
+        ),
+
+        desc.File(
+            name="modelPath",
+            label="Segmentation Model",
+            description="Weights file for the internal model.",
+            value="${ALICEVISION_SEMANTIC_SEGMENTATION_MODEL}",
+            uid=[0]
+        ),
+
+        desc.ListAttribute(
+            elementDesc=desc.ChoiceParam(
+                name="className",
+                label="Class Name",
+                description="Class name to be added to the mask.",
+                value="person",
+                values=[
+                    "__background__",
+                    "aeroplane",
+                    "bicycle", "bird", "boat", "bottle", "bus",
+                    "car", "cat", "chair", "cow",
+                    "diningtable", "dog",
+                    "horse",
+                    "motorbike",
+                    "person", "pottedplant",
+                    "sheep", "sofa",
+                    "train", "tvmonitor"
+                ],
+                exclusive=True,
+                uid=[0]),
+            name="validClasses",
+            label="Classes",
+            description="Classes names which are to be considered."
+        ),
+
+        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="Masks Folder",
+            description="Output path for the masks.",
+            value=desc.Node.internalFolder,
+            uid=[],
+        ),
+        desc.File(
+            name="masks",
+            label="Masks",
+            description="Generated segmentation masks.",
+            semantic="image",
+            value=desc.Node.internalFolder + "<VIEW_ID>.exr",
+            group="",
+            uid=[],
+        ),
+    ]
+