fixed numpy dtype errors

lib/ext_transform.py

@@ -26,7 +26,7 @@ def __call__(self, tensor):
 
 class MaskToTensor(object):
     def __call__(self, img):
-        return torch.from_numpy(np.array(img, dtype=np.int32)).long()
+        return torch.from_numpy(np.array(img, dtype=int)).long()
 
 
 class FreeScale(object):

lib/mesh_util.py

@@ -42,7 +42,7 @@ def eval_func(points):
 
     # Finally we do marching cubes
     try:
-        verts, faces, normals, values = measure.marching_cubes_lewiner(sdf, 0.5)
+        verts, faces, normals, values = measure.marching_cubes(sdf, 0.5)
         # transform verts into world coordinate system
         verts = np.matmul(mat[:3, :3], verts.T) + mat[:3, 3:4]
         verts = verts.T

lib/renderer/glm.py

@@ -2,19 +2,19 @@
 
 
 def vec3(x, y, z):
-    return np.array([x, y, z], dtype=np.float32)
+    return np.array([x, y, z], dtype=float)
 
 
 def radians(v):
     return np.radians(v)
 
 
 def identity():
-    return np.identity(4, dtype=np.float32)
+    return np.identity(4, dtype=float)
 
 
 def empty():
-    return np.zeros([4, 4], dtype=np.float32)
+    return np.zeros([4, 4], dtype=float)
 
 
 def magnitude(v):

lib/sdf.py

@@ -55,8 +55,8 @@ def eval_grid_octree(coords, eval_func,
 
     sdf = np.zeros(resolution)
 
-    dirty = np.ones(resolution, dtype=np.bool)
-    grid_mask = np.zeros(resolution, dtype=np.bool)
+    dirty = np.ones(resolution, dtype=bool)
+    grid_mask = np.zeros(resolution, dtype=bool)
 
     reso = resolution[0] // init_resolution