small refactor

mogen/smpl/render_mesh.py

@@ -162,19 +162,20 @@ def render(motions):
 
 def render_from_smpl(thetas, yfov, move_x, move_y, move_z, x_rot, y_rot, z_rot, draw_platform=True, depth_only=False, normals=False, smpl_model_path=None, shape_parameters=None):
     if shape_parameters is not None:
-        betas_single = torch.tensor([shape_parameters], dtype=torch.float32)
+        betas_tensor = torch.tensor([shape_parameters], dtype=torch.float32)
         batch_size = thetas.shape[3]  
-        betas_batch = betas_single.repeat(batch_size, 1)  # Replicates the single sample across the batch
+        betas_batch = betas_tensor.repeat(batch_size, 1)  # Replicates the single sample across the batch
         betas_batch = betas_batch.to(device=get_torch_device())
     else:
         betas_batch = None
-    rot2xyz = Rotation2xyz(device=get_torch_device(), smpl_model_path=smpl_model_path)
+        
+    rot2xyz = Rotation2xyz(device=get_torch_device(), smpl_model_path=smpl_model_path, betas=betas_batch)
     faces = rot2xyz.smpl_model.faces
 
     vertices = rot2xyz(thetas.clone().to(get_torch_device()).detach(), mask=None,
                                     pose_rep='rot6d', translation=True, glob=True,
                                     jointstype='vertices',
-                                    vertstrans=True, betas=betas_batch)
+                                    vertstrans=True)
 
     frames = vertices.shape[3] # shape: 1, nb_frames, 3, nb_joints
     print (vertices.shape)

mogen/smpl/rotation2xyz.py

@@ -8,14 +8,15 @@ JOINTSTYPES = ["a2m", "a2mpl", "smpl", "vibe", "vertices"]
 
 
 class Rotation2xyz:
-    def __init__(self, device, dataset='amass', smpl_model_path=None):
+    def __init__(self, device, dataset='amass', smpl_model_path=None, betas=None):
         self.device = device
         self.dataset = dataset
         self.smpl_model = SMPL(smpl_model_path).eval().to(device)
+        self.betas = betas
 
     def __call__(self, x, mask, pose_rep, translation, glob,
                  jointstype, vertstrans, beta=0,
-                 glob_rot=None, get_rotations_back=False, betas=None, **kwargs):
+                 glob_rot=None, get_rotations_back=False, **kwargs):
         if pose_rep == "xyz":
             return x
 
@@ -57,12 +58,12 @@ class Rotation2xyz:
             global_orient = rotations[:, 0]
             rotations = rotations[:, 1:]
 
-        if betas is None:
-            betas = torch.zeros([rotations.shape[0], self.smpl_model.num_betas],
+        if self.betas is None:
+            self.betas = torch.zeros([rotations.shape[0], self.smpl_model.num_betas],
                                 dtype=rotations.dtype, device=rotations.device)
-            betas[:, 1] = beta
+            self.betas[:, 1] = beta
             # import ipdb; ipdb.set_trace()
-        out = self.smpl_model(body_pose=rotations, global_orient=global_orient, betas=betas)
+        out = self.smpl_model(body_pose=rotations, global_orient=global_orient, betas=self.betas)
 
         # get the desirable joints
         joints = out[jointstype]