option to use global binning

curvature_analysis.py

@@ -67,7 +67,7 @@ def get_bins(values, nr_of_bins):
     return bins
 
 
-def generate_curvatures(folder, frame, 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])
 
@@ -98,20 +98,20 @@ def generate_curvatures(folder, frame, neighbourhoods=[25], nr_of_labels=6):
         cloud.add_scalar_field("curvature", ev=ev)
         curvature = np.array(cloud.points["curvature(" + str(neighbourhood+1) + ")"])
         
-        bins = get_bins(curvature, nr_of_labels)
+        bins_local = bins[neighbourhood] if bins is not None else get_bins(curvature, nr_of_labels)
-        labels = np.linspace(0, bins.shape[0] - 2, bins.shape[0] - 1)
+        labels = np.linspace(0, bins_local.shape[0] - 2, bins_local.shape[0] - 1)
 
         frame_labels = np.zeros((curvature.shape[0]), dtype=np.float32)
-        for j in range(bins.shape[0] - 2):
+        for j in range(bins_local.shape[0] - 2):
-            frame_labels[(curvature >= bins[j]) * (curvature < bins[j+1])] = labels[j]
+            frame_labels[(curvature >= bins_local[j]) * (curvature < bins_local[j+1])] = labels[j]
-        frame_labels[curvature >= bins[-2]] = labels[-1]
+        frame_labels[curvature >= bins_local[-2]] = labels[-1]
 
         curvatures.append(frame_labels)
         
     return curvatures
 
 
-def visualize_curvature_labels(folder, frame, neighbourhoods):
+def visualize_curvature_labels(folder, frame, bins, neighbourhoods):
     id = frame.split('_')[0]
     frame_nr = frame.split('_')[1].split('.')[0]
 
@@ -119,7 +119,7 @@ def visualize_curvature_labels(folder, frame, 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, neighbourhoods)
+    curvature_labels_all = generate_curvatures(folder, frame, bins, neighbourhoods)
     colors_binned_all = []
 
     for curvature_labels in curvature_labels_all:
@@ -166,7 +166,7 @@ def visualize_curvature_labels(folder, frame, neighbourhoods):
                     scene2_aspectmode='manual', scene2_aspectratio=dict(x=1, y=1, z=1),
                     scene3_aspectmode='manual', scene3_aspectratio=dict(x=1, y=1, z=1),
                     scene4_aspectmode='manual', scene4_aspectratio=dict(x=1, y=1, z=1),
-                    scene5_aspectmode='manual', scene5_aspectratio=dict(x=1, y=1, z=1),
+                    # scene5_aspectmode='manual', scene5_aspectratio=dict(x=1, y=1, z=1),
                     )
     helper = dict(xaxis = dict(nticks=4, range=[-1,1],),
                 yaxis = dict(nticks=4, range=[-1,1],),
@@ -175,7 +175,7 @@ def visualize_curvature_labels(folder, frame, neighbourhoods):
                         scene2 = helper,
                         scene3 = helper,
                         scene4 = helper,
-                        scene5 = helper,
+                        # scene5 = helper,
                         )
 
 
@@ -211,6 +211,13 @@ if __name__ == '__main__':
     # k_neighbours(k=25)
 
     folder = '/home/workspace/local-data/valid_skirt'
+    bins = dict()
+    bins[10] = np.load(f'custom_data/train_bins_skirt_10.npy')
+    bins[25] = np.load(f'custom_data/train_bins_skirt.npy')
+    bins[100] = np.load(f'custom_data/train_bins_skirt_100.npy')
+
+    bins = None
+
 
     nr_of_labels = 6
     neighbourhood = 50
@@ -220,4 +227,4 @@ if __name__ == '__main__':
     else:
         dist = np.load('custom_data/dijkstra_skirt.npy')
 
-    visualize_curvature_labels(folder, '02572_1', neighbourhoods=[10, 25, 50, 100])
+    visualize_curvature_labels(folder, '02572_1', bins, neighbourhoods=[10, 25, 100])