Updates

utils/data_utils.py

@@ -3,17 +3,19 @@ import numpy as np
 
 
 class PointcloudScale(object):
+
     def __init__(self, mean=2.0, std=1.0, clip=1.8):
         self.mean, self.std, self.clip = mean, std, clip
 
     def __call__(self, points):
         scaler = points.new(1).normal_(
-            mean=self.mean, std=self.std).clamp_(
-                max(self.mean - self.clip, 0.01), self.mean + self.clip)
+            mean=self.mean, std=self.std
+        ).clamp_(max(self.mean - self.clip, 0.01), self.mean + self.clip)
         return scaler * points
 
 
 class PointcloudRotate(object):
+
     def __init__(self, x_axis=False, z_axis=True):
         assert x_axis or z_axis
         self.x, self.z = x_axis, z_axis
@@ -46,25 +48,30 @@ class PointcloudRotate(object):
 
 
 class PointcloudJitter(object):
+
     def __init__(self, std=0.01, clip=0.03):
         self.std, self.clip = std, clip
 
     def __call__(self, points):
         jittered_data = points.new(*points.size()).normal_(
-            mean=0.0, std=self.std).clamp_(-self.clip, self.clip)
+            mean=0.0, std=self.std
+        ).clamp_(-self.clip, self.clip)
         return points + jittered_data
 
 
 class PointcloudTranslate(object):
+
     def __init__(self, std=1.0, clip=3.0):
         self.std, self.clip = std, clip
 
     def __call__(self, points):
         translation = points.new(3).normal_(
-            mean=0.0, std=self.std).clamp_(-self.clip, self.clip)
+            mean=0.0, std=self.std
+        ).clamp_(-self.clip, self.clip)
         return points + translation
 
 
 class PointcloudToTensor(object):
+
     def __call__(self, points):
         return torch.from_numpy(points).float()