diff --git a/diffraction/WISH/bragg-detect/cnn/README.md b/diffraction/WISH/bragg-detect/cnn/README.md
index 633af99..313e6a8 100644
--- a/diffraction/WISH/bragg-detect/cnn/README.md
+++ b/diffraction/WISH/bragg-detect/cnn/README.md
@@ -9,7 +9,7 @@ Inorder to use the pretrained Faster RCNN model inside mantid, below steps are r
 * Download the script repository's `scriptrepository\diffraction\WISH` directory as instructed here https://docs.mantidproject.org/nightly/workbench/scriptrepository.html
 * Check whether `<local path>\diffraction\WISH` path is available at `Python Script Directories` tab from `File->Manage User Directories`.
 * Close the workbench
-* From command line, change the directory to the place where the scripts were downloaded ex: `<local path>\diffraction\WISH`
+* From command line, change the directory to the place where the scripts were downloaded ex: `<local path>\diffraction\WISH\bragg-detect\cnn`
 * Within the same conda enviroment, install pytorch dependancies by running `pip install -r requirements.txt`
 * Install NVIDIA CUDA Deep Neural Network library (cuDNN) by running `conda install -c anaconda cudnn`
 * Re-launch workbench from `workbench` command
diff --git a/diffraction/WISH/bragg-detect/cnn/WISHDataSets.py b/diffraction/WISH/bragg-detect/cnn/WISHDataSets.py
index 1ad3048..c0fe447 100644
--- a/diffraction/WISH/bragg-detect/cnn/WISHDataSets.py
+++ b/diffraction/WISH/bragg-detect/cnn/WISHDataSets.py
@@ -3,7 +3,7 @@
 import albumentations as A
 from albumentations.pytorch.transforms import ToTensorV2
 from bragg_utils import make_3d_array
-from mantid.simpleapi import Load, Rebunch, Workspace
+from mantid.simpleapi import Load, Rebunch, Workspace, AnalysisDataService
 
 
 class WISHWorkspaceDataSet(tc.utils.data.Dataset):
@@ -12,11 +12,18 @@ def __init__(self, workspace):
             if workspace.getAxis(0).getUnit().unitID() != "TOF":
                 raise RuntimeError("Unit of the X-axis is expected to be TOF")
             ws = workspace
+            ws_name = ws.getName()
         elif isinstance(workspace, str):
             ws = Load(Filename=workspace, OutputWorkspace=workspace, EnableLogging=False)
+            ws_name = ws
         else:
             raise RuntimeError("Invalid workspace type - must be Workspace object or a name of a workspace to Load")
-        self.rebunched_ws = Rebunch(InputWorkspace=ws, NBunch=3, OutputWorkspace="_cnn_rebunched", StoreInADS=False, EnableLogging=False)
+        
+        rebunched_ws_name = f"__{ws_name}_cnn_rebunched"
+        if AnalysisDataService.doesExist(rebunched_ws_name):
+            self.rebunched_ws = AnalysisDataService[rebunched_ws_name]
+        else:
+            self.rebunched_ws = Rebunch(InputWorkspace=ws, NBunch=3, OutputWorkspace=rebunched_ws_name, EnableLogging=False)
         self.ws_3d = make_3d_array(self.rebunched_ws)
         print(f"Data set for {workspace} is created with shape{self.ws_3d.shape}")
         self.trans = A.Compose([A.pytorch.transforms.ToTensorV2(p=1.0)])