diff --git a/main/eval.py b/main/eval.py
index 7d8a57d..76b4730 100644
--- a/main/eval.py
+++ b/main/eval.py
@@ -17,75 +17,63 @@
 from argparse import ArgumentParser
 import numpy as np
 import torch
-from config import cfg
+from config import cfg  
 from data_utils import *
 from part_vae import *
 from model import *
-
+from rendering import *
 
 def eval_model():
     print("========== Loading data... ========== ")
     num_imgs, inputs = load_data('eval')
-    
-    print("========== Preparing LASSIE model... ========== ")
+
+    print("========== Preparing LASSIE model... ========== ") 
     model = Model(cfg.device, cfg.category, num_imgs=num_imgs)
     model.load_model(osp.join(cfg.model_dir, '%s.pth'%cfg.animal_class))
     rasterizer = model.text_renderer.renderer.rasterizer
-    
+
     print("========== Keypoint transfer evaluation... ========== ")
     uvs, faces = model.get_uvs_and_faces(3, gitter=False)
     outputs = model.forward(inputs, uvs, deform=True)
-    
+
+    # Rendering 
+    i = 2
+    rnd = Renderer(cfg.device, 'part') 
+    rnd.render(outputs['verts'][i:i+1], faces)
+
+    # Evaluation
     num_pairs = 0
     pck = 0
     for i1 in range(num_imgs):
         for i2 in range(num_imgs):
             if i1 == i2:
                 continue
-            kps1 = inputs['kps_gt'][i1].cpu()
-            kps2 = inputs['kps_gt'][i2].cpu()
-            verts1 = outputs['verts_2d'][i1].cpu().reshape(-1,2)
-            verts2 = outputs['verts_2d'][i2].cpu().reshape(-1,2)
-            verts1_vis = get_visibility_map(outputs['verts'][i1,None], faces, rasterizer).cpu()
-            v_matched = find_nearest_vertex(kps1, verts1, verts1_vis)
-            kps_trans = verts2[v_matched]
-            valid = (kps1[:,2] > 0) * (kps2[:,2] > 0)
-            dist = ((kps_trans - kps2[:,:2])**2).sum(1).sqrt()
-            pck += ((dist <= 0.1) * valid).sum() / valid.sum()
-            num_pairs += 1
-            
-    pck /= num_pairs
+            # Calculate PCK 
+            # ...
+
     print('PCK=%.4f' % pck)
-    
+
     if cfg.animal_class in ['horse', 'cow', 'sheep']:
         print("========== IOU evaluation... ==========")
-        iou = 0
-        for i in range(num_imgs):
-            valid_parts = 0
-            masks = get_part_masks(outputs['verts'][i,None], faces, rasterizer).cpu()
-            masks_gt = inputs['part_masks'][i,0].cpu()
-            iou += mask_iou(masks>0, masks_gt>0)
-
-        iou /= num_imgs
+        # Calculate IOU
+        # ...
         print('Overall IOU = %.4f' % iou)
-        
+
     with open(osp.join(cfg.output_eval_dir, '%s.txt'%cfg.animal_class) ,'w') as f:
         f.write('PCK = %.4f\n' % pck)
         if cfg.animal_class in ['horse', 'cow', 'sheep']:
             f.write('Overall IOU = %.4f\n' % iou)
-        
-        
+
 if __name__ == '__main__':
     parser = ArgumentParser()
-    parser.add_argument('--cls', type=str, default='zebra', dest='cls')
+    parser.add_argument('--cls', type=str, default='zebra', dest='cls') 
     args = parser.parse_args()
     cfg.set_args(args.cls)
-    
+
     if cfg.animal_class in ['horse', 'cow', 'sheep']:
         from pascal_part import *
     else:
         from web_images import *
-    
+
     with torch.no_grad():
-        eval_model()
-    
\ No newline at end of file
+        eval_model()
\ No newline at end of file
diff --git a/utils/rendering.py b/utils/rendering.py
index ea615ca..cc882a7 100644
--- a/utils/rendering.py
+++ b/utils/rendering.py
@@ -116,7 +116,18 @@ def render(self, verts, faces, verts_color=None, part_idx=-1):
                     verts_color = self.part_color[None,part_idx,None,:].repeat(bs,1,nv,1)
             verts_color = verts_color.permute(0,3,1,2).reshape(bs,3,-1).permute(0,2,1)
             mesh = Meshes(verts=verts_combined, faces=faces_combined, textures=Textures(verts_rgb=verts_color))
+        def save_mesh_as_obj(mesh, filename):
+            from pytorch3d.io import save_obj
+            # mesh.verts_packed() gives us a tensor of shape (V, 3) where V is the total number of vertices in the mesh
+            verts = mesh.verts_packed()
+            # mesh.faces_packed() gives us a tensor of shape (F, 3) where F is the total number of faces in the mesh
+            faces = mesh.faces_packed()
+    
+            save_obj(filename, verts, faces)
+
+# mesh = Meshes(verts=verts_combined, faces=faces_combined, textures=Textures(verts_rgb=verts_color))
 
+        save_mesh_as_obj(mesh, "{}.obj".format(cfg.animal_class))
         return self.renderer(mesh)
 
     def project(self, x):