diff --git a/deshape.py b/deshape.py
index 8a9ff82..fa5988d 100644
--- a/deshape.py
+++ b/deshape.py
@@ -1,3 +1,6 @@
+## !!MOVEd to preprocessing.py
+
+
 import os
 import sys
 import time
@@ -18,39 +21,30 @@ if __name__ == '__main__':
 
     uv2mesh = UV2Mesh()
     smpl = SMPL()
+    folder = '/home/workspace/local-data/train_skirt_25'
 
     F = np.load("custom_utils/smpl_faces.npy")
 
     factory = DatasetFactory()
     signature_dynamic = { 'id': (),
                           'pose_shape': (72 + 11,),
-                        #   'uv_posed': (3, 512, 256,),
-                        #   'uv_body_posed': (3, 512, 256,),
-                          # 'mesh_body_posed': (14475, 3,),
-                        #   'mesh_posed_body_no_orient': (14475, 3,),
                           'mesh_posed': (14475, 3,),
                           'mesh_unposed': (14475, 3,),
-                          # 'uv_unposed': (3, 512, 256,),
-                        #   'uv_curvature': (512, 256),
-                        #   'mesh_curvature':  (14475)
                         }
-    signature_static = { #'uv_static': (3, 512, 256,),
-                        #  'mesh_static': (14475, 3,),
+    signature_static = { 
                           'mesh_mask': (14475,),
-                        #  'uv_mask': (512, 256,),
-                        #  'uv_shaped_body': (3, 512, 256,),
                           }
 
-    dataset = factory.get_dataset(folder='/home/workspace/local-data/jumpsuit_20/train',
+    dataset = factory.get_dataset(folder=folder,
                                   batch_size=1,
-                                  signature=signature_dynamic)
-    static_dataset = StaticDataset(folder='/home/workspace/local-data/jumpsuit_20/train',
+                                  signature=signature_dynamic,
+                                  in_memory=False)
+    static_dataset = StaticDataset(folder=folder,
                                    signature=signature_static)
 
 
     uv_res = 256
-
-
+    os.makedirs(os.path.join(folder, id, 'mesh_unposed_no_shape'), exist_ok=True)
 
     for i, batch in enumerate(dataset):
         print(i)
@@ -60,15 +54,15 @@ if __name__ == '__main__':
         mask = np.squeeze(batch['mesh_mask'].numpy()).astype(bool)
         pose, shape = batch['pose_shape'][:, :72].numpy(), batch['pose_shape'][:, 72:].numpy()
         # mesh_posed = np.squeeze(batch['mesh_posed'].numpy())
-        gender = int(shape[0, -1] > 0)
+        gender = int(shape[0, -1] > 0.5)
         print(gender)
 
         shape_offsets = tf.tensordot(shape[:,:10], smpl.shapedirs[gender], axes=[[1], [2]]).numpy()
         
-
         mesh_unposed[mask, :] = mesh_unposed[mask, :] - np.squeeze(shape_offsets)[smpl.to_keep, :][mask, :]
+        np.savez_compressed(os.path.join(folder, id, 'mesh_unposed_no_shape', id + '_' + str(i) + '.npz'), mesh_unposed_no_shape = mesh_unposed)
 
-        np.savez_compressed(os.path.join(folder, id, 'mesh_posed_body_no_orient', id + '_' + str(i) + '.npz'), mesh_posed_body_no_orient = T[i, :, :])
+        # np.savez_compressed(os.path.join(folder, id, 'mesh_posed_body_no_orient', id + '_' + str(i) + '.npz'), mesh_posed_body_no_orient = T[i, :, :])
 
         
         # _, faces = _maskFaces(np.zeros((14475, 3), dtype=np.float32), F, mask)