save

curvature_analysis.py

@@ -67,7 +67,7 @@ def get_bins(values, nr_of_bins):
     return bins
 
 
-def generate_curvatures(folder, frame, bins, neighbourhoods=[25], nr_of_labels=6):
+def generate_curvatures(folder, frame, bins, neighbourhoods=[25], nr_of_labels=[6]):
     id = frame.split('_')[0]
     frame_nr = int(frame.split('_')[1].split('.')[0])
 
@@ -91,14 +91,14 @@ def generate_curvatures(folder, frame, bins, neighbourhoods=[25], nr_of_labels=6
     cloud = PyntCloud.from_file(temp_file)
 
     curvatures = []
-    for neighbourhood in neighbourhoods:
+    for neighbourhood, nr_labels in zip(neighbourhoods, nr_of_labels):
         k_neighbors = np.argsort(dist[mask, :][:, mask], axis=-1)[:, :neighbourhood] #cloud.get_neighbors(k=neighbourhood)
         #k_neighbors = k_neighbors_cache[id] # np.argsort(dist[mask, :][:, mask], axis=-1)[:, :neighbourhood] #cloud.get_neighbors(k=neighbourhood)
         ev = cloud.add_scalar_field("eigen_values", k_neighbors=k_neighbors)
         cloud.add_scalar_field("curvature", ev=ev)
         curvature = np.array(cloud.points["curvature(" + str(neighbourhood+1) + ")"])
         
-        bins_local = bins[neighbourhood] if bins is not None else get_bins(curvature, nr_of_labels)
+        bins_local = bins[neighbourhood] if bins is not None else get_bins(curvature, nr_labels)
         labels = np.linspace(0, bins_local.shape[0] - 2, bins_local.shape[0] - 1)
 
         frame_labels = np.zeros((curvature.shape[0]), dtype=np.float32)
@@ -111,7 +111,7 @@ def generate_curvatures(folder, frame, bins, neighbourhoods=[25], nr_of_labels=6
     return curvatures
 
 
-def visualize_curvature_labels(folder, frame, bins, neighbourhoods):
+def visualize_curvature_labels(folder, frame, bins, neighbourhoods, nr_of_labels):
     id = frame.split('_')[0]
     frame_nr = frame.split('_')[1].split('.')[0]
 
@@ -119,7 +119,7 @@ def visualize_curvature_labels(folder, frame, bins, neighbourhoods):
     _, faces = _maskFaces(np.zeros((14475,3)), F, mask)
     verts = np.load(os.path.join(folder, 'mesh_posed', f'{id}_{frame_nr}.npz'))['mesh_posed'][mask,:]
     
-    curvature_labels_all = generate_curvatures(folder, frame, bins, neighbourhoods)
+    curvature_labels_all = generate_curvatures(folder, frame, bins, neighbourhoods, nr_of_labels)
     colors_binned_all = []
 
     for curvature_labels in curvature_labels_all:
@@ -232,4 +232,4 @@ if __name__ == '__main__':
     else:
         dist = np.load('custom_data/dijkstra_skirt.npy')
 
-    visualize_curvature_labels(folder, '02572_1', bins, neighbourhoods=[10, 25, 100])
+    visualize_curvature_labels(folder, '02572_1', bins, neighbourhoods=[25, 25, 25], nr_of_labels=[3,6,12])