Init.

demo.py

@@ -0,0 +1,38 @@
+import torch
+
+from smpl.pytorch.smpl_layer import SMPL_Layer
+from display_utils import display_model
+
+
+if __name__ == '__main__':
+    cuda = False
+    batch_size = 1
+
+    # Create the SMPL layer
+    smpl_layer = SMPL_Layer(
+        center_idx=0,
+        gender='neutral',
+        model_root='smpl/native/models')
+
+    # Generate random pose and shape parameters
+    pose_params = torch.rand(batch_size, 72) * 0.2
+    shape_params = torch.rand(batch_size, 10) * 0.03
+
+    # GPU mode
+    if cuda:
+        pose_params = pose_params.cuda()
+        shape_params = shape_params.cuda()
+        smpl_layer.cuda()
+
+    # Forward from the SMPL layer
+    verts, Jtr = smpl_layer(pose_params, th_betas=shape_params)
+
+    # Draw output vertices and joints
+    display_model(
+        {'verts': verts.cpu().detach(),
+         'joints': Jtr.cpu().detach()},
+        model_faces=smpl_layer.th_faces,
+        with_joints=True,
+        kintree_table=smpl_layer.kintree_table,
+        savepath='image.png',
+        show=True)