diff --git a/forwardOnBigImages.py b/forwardOnBigImages.py
index aea5867..1cb92a7 100644
--- a/forwardOnBigImages.py
+++ b/forwardOnBigImages.py
@@ -1,30 +1,28 @@
 import numpy as np
 import networkTraining.cropRoutines as cropRoutines
 import torch
 
 def targetCoords(sourceCoords,validCoords):
   cc=sourceCoords
   vc=validCoords
   tc=[]
   for i in range(len(cc)):
     tc.append(slice(cc[i].start+vc[i].start,cc[i].start+vc[i].stop))
   return tc
 
 def processChunk(inChunk,cropSize,marginSize,startDim,net,outChannels=None):
   nc=cropRoutines.noCrops(inChunk.shape,cropSize,marginSize,startDim)
   size=np.array(inChunk.shape)
   if outChannels:
     size[1]=outChannels
   outChunk=np.zeros(tuple(size))
   net.eval()
   for i in range(nc):
     cc,vc=cropRoutines.cropCoords(i,cropSize,marginSize,inChunk.shape,startDim)
     tc=targetCoords(cc,vc)
     crop=inChunk[tuple(cc)]
     o=net.forward(torch.from_numpy(crop).cuda())
-    print("osize",o.size())
-    print("vc",vc)
-    print("outchunksize",outChunk.shape)
-    print("tc",tc)
+    tc[1]=slice(0,size[1])
+    vc[1]=slice(0,size[1])
     outChunk[tuple(tc)]=o.cpu().data.numpy()[tuple(vc)]
   return outChunk