diff --git a/Wrappers/Python/cil/optimisation/functions/AbsFunction.py b/Wrappers/Python/cil/optimisation/functions/AbsFunction.py
index b922eb36ae..5ae55d1006 100644
--- a/Wrappers/Python/cil/optimisation/functions/AbsFunction.py
+++ b/Wrappers/Python/cil/optimisation/functions/AbsFunction.py
@@ -26,7 +26,7 @@
 
 import numpy as np
 from cil.optimisation.functions import Function
-from cil.framework import DataContainer
+from cil.framework import DataContainer, ImageGeometry
 from typing import Optional
 import warnings
 import logging
@@ -147,10 +147,15 @@ def _take_abs_input(func):
     def _take_abs_decorator(self, x: DataContainer, *args, **kwargs):
         real_dtype, _ = _get_real_complex_dtype(x)
         
-        rgeo = x.geometry.copy()
-        rgeo.dtype = real_dtype
-        r = rgeo.allocate(0)
-        r.fill(np.abs(x.as_array()).astype(real_dtype))
+        try:
+            rgeo = x.geometry.copy()
+            rgeo.dtype = real_dtype
+            r = rgeo.allocate(0)
+            r.fill(np.abs(x.as_array()).astype(real_dtype))
+        except AttributeError as excp:
+            rgeo = ImageGeometry(*x.shape[::-1])
+            r = rgeo.allocate(None, dtype=real_dtype)
+            r.fill(np.abs(x.asarray()))
         fval = func(r, *args, **kwargs)
         return fval
     return _take_abs_decorator
@@ -167,12 +172,17 @@ def _abs_project_decorator(self, x: DataContainer, *args, **kwargs):
         
         real_dtype, complex_dtype = _get_real_complex_dtype(x)
             
-                    
-        rgeo = x.geometry.copy()
-        rgeo.dtype = real_dtype
-        r = rgeo.allocate(None)
-        r.fill(np.abs(x.as_array()).astype(real_dtype))
-        Phi = np.exp((1j*np.angle(x.array)))
+        try:            
+            rgeo = x.geometry.copy()
+            rgeo.dtype = real_dtype
+            r = rgeo.allocate(None)
+            r.fill(np.abs(x.as_array()).astype(real_dtype))
+            Phi = np.exp((1j*np.angle(x.array)))
+        except AttributeError as excp:
+            rgeo = ImageGeometry(*x.shape[::-1])
+            r = rgeo.allocate(None, dtype=real_dtype)
+            r.fill(np.abs(x.asarray()))
+            Phi = np.exp((1j*np.angle(x.asarray())))
         out = kwargs.pop('out', None)
         
         fvals = func(r, *args, **kwargs)
@@ -185,9 +195,14 @@ def _abs_project_decorator(self, x: DataContainer, *args, **kwargs):
             y = r.copy()
             fvals_np = fvals.as_array()
             while np.any(fvals_np < 0):
-                tmp = fvals_np  - 0.5*y.as_array() + 0.5*r.as_array()
-                tmp[tmp < 0] = 0.
-                y += DataContainter(tmp, y.geometry) - fvals
+                tmp = r - y
+                tmp *= 0.5
+                tmp += fvals
+                tmparr = tmp.as_array()
+                tmparr[tmparr < 0] = 0.
+                tmp.fill(tmparr)
+                y += tmp
+                y -= fvals
                 fvals = func(y, *args, **kwargs)
                 cts += 1
                 if cts > 10:
@@ -196,11 +211,12 @@ def _abs_project_decorator(self, x: DataContainer, *args, **kwargs):
                     break
 
         if out is None: 
-            out_geom = x.geometry.copy()
-            out = out_geom.allocate(None)
+            out = x * 0
         if np.isreal(x.as_array()).all():
+            print("Input is real, returning real output")
             out.fill( np.real(fvals_np.astype(complex_dtype)*Phi))
         else:
+            print("Input is complex, returning complex output")
             out.fill( fvals_np.astype(complex_dtype)*Phi)
         return out
     return _abs_project_decorator
@@ -209,7 +225,7 @@ def _abs_project_decorator(self, x: DataContainer, *args, **kwargs):
 def _get_real_complex_dtype(x: DataContainer):
     '''An internal function to find the type of x and set the corresponding real and complex data types '''
     
-    x_dtype = x.as_array().dtype
+    x_dtype = x.dtype
     if np.issubdtype(x_dtype, np.complexfloating):
         complex_dtype = x_dtype
         complex_example = np.array([1 + 1j], dtype=x_dtype)