WIP: working on example

Author: 9and3

src/gh/components/DF_CAD_segmentator/code.py

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+#! python3
+
+import System
+import typing
+
+import Rhino
+import Rhino.Geometry as rg
+from ghpythonlib.componentbase import executingcomponent as component
+
+import Grasshopper as gh
+from Grasshopper.Kernel import GH_RuntimeMessageLevel as RML
+
+import diffCheck
+import diffCheck.df_geometries
+from diffCheck.diffcheck_bindings import dfb_segmentation
+
+from diffCheck import df_cvt_bindings
+
+
+class DFCADSegmentator(component):
+    def RunScript(self,
+        i_clouds : typing.List[rg.PointCloud],
+        i_assembly : diffCheck.df_geometries.DFAssembly,
+        i_angle_threshold : float,
+        i_association_threshold : float
+    ) -> rg.PointCloud:
+        """
+        @param i_meshes : the beams (to be converted)
+        @param i_angle_threshold : from 0 to 1, it's the sin value. The closer to 0 the less permissive and viceversa to 1.
+        @param i_association_threshold: from 0 to infinite. By default 0.5. The closer to 0 the less permissive your point 
+        inclusion will be, the higher the value the opposite.
+
+        @return o_clusters : the clusters of the beams
+        """
+        o_clusters = []
+
+        df_clouds = [df_cvt_bindings.cvt_rhcloud_2_dfcloud(cloud) for cloud in i_clouds]
+        # df_meshes = [df_cvt_bindings.cvt_rhmesh_2_dfmesh(mesh) for mesh in i_meshes]
+
+        # # get the point clouds corresponding to the beams
+        # df_asssociated_clusters : List[dfCloud] = dfb_segmentation.DFSegmentation.associate_clusters(
+        #     reference_mesh=df_meshes,
+        #     unassociated_clusters=df_clouds,
+        #     angle_threshold=i_angle_threshold,
+        #     association_threshold=i_association_threshold
+        # )
+
+        print("test")
+
+
+        return o_clusters
+
+if __name__ == "__main__":
+    com = DFCADSegmentator()
+    o_clusters = com.RunScript(
+        i_clouds,
+        i_assembly,
+        i_angle_threshold,
+        i_association_threshold
+        )

src/gh/components/DF_CAD_segmentator/icon.png

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+{
+    "name": "DFNormalSegmentator",
+    "nickname": "DFCNorSeg",
+    "category": "diffCheck",
+    "subcategory": "Segmentation",
+    "description": "Cluster a point cloud based on normals.",
+    "exposure": 4,
+    "instanceGuid": "8f732cef-771c-41b8-acca-562211fd3a80",
+    "ghpython": {
+        "hideOutput": true,
+        "hideInput": true,
+        "isAdvancedMode": true,
+        "marshalOutGuids": true,
+        "iconDisplay": 2,
+        "inputParameters": [
+            {
+                "name": "i_cloud",
+                "nickname": "i_cloud",
+                "description": "The point cloud to reduce the size.",
+                "optional": true,
+                "allowTreeAccess": true,
+                "showTypeHints": true,
+                "scriptParamAccess": "item",
+                "wireDisplay": "default",
+                "sourceCount": 0,
+                "typeHintID": "pointcloud"
+            },
+            {
+                "name": "i_normal_threshold_degree",
+                "nickname": "i_normal_threshold_degree",
+                "description": "The normal threshold in degrees (under that it consider to the same cluster).",
+                "optional": false,
+                "allowTreeAccess": true,
+                "showTypeHints": true,
+                "scriptParamAccess": "item",
+                "wireDisplay": "default",
+                "sourceCount": 0,
+                "typeHintID": "float"
+            },
+            {
+                "name": "i_min_cluster_size",
+                "nickname": "i_min_cluster_size",
+                "description": "The smallest cluster allowed.",
+                "optional": false,
+                "allowTreeAccess": true,
+                "showTypeHints": true,
+                "scriptParamAccess": "item",
+                "wireDisplay": "default",
+                "sourceCount": 0,
+                "typeHintID": "int"
+            },
+            {
+                "name": "i_use_knn_neighborhood",
+                "nickname": "i_use_knn_neighborhood",
+                "description": "If true use knn, otherwise radius search.",
+                "optional": false,
+                "allowTreeAccess": true,
+                "showTypeHints": true,
+                "scriptParamAccess": "item",
+                "wireDisplay": "default",
+                "sourceCount": 0,
+                "typeHintID": "bool"
+            },
+            {
+                "name": "i_knn_neighborhood_size",
+                "nickname": "i_knn_neighborhood_size",
+                "description": "The knn size.",
+                "optional": false,
+                "allowTreeAccess": true,
+                "showTypeHints": true,
+                "scriptParamAccess": "item",
+                "wireDisplay": "default",
+                "sourceCount": 0,
+                "typeHintID": "int"
+            },
+            {
+                "name": "i_radius_neighborhood_size",
+                "nickname": "i_radius_neighborhood_size",
+                "description": "The size of the radius.",
+                "optional": false,
+                "allowTreeAccess": true,
+                "showTypeHints": true,
+                "scriptParamAccess": "item",
+                "wireDisplay": "default",
+                "sourceCount": 0,
+                "typeHintID": "float"
+            }
+        ],
+        "outputParameters": [
+            {
+                "name": "o_clusters",
+                "nickname": "o_clusters",
+                "description": "The segmented clouds.",
+                "optional": false,
+                "sourceCount": 0,
+                "graft": false
+            }
+        ]
+    }
+}