use persistent data for ckpt

app.py

@@ -132,7 +132,7 @@ def infer_sample(opt, var, graph):
     return var.mesh_pred[0]
     
 def infer(input_image_path, input_mask_path):
-    opt_cmd = options.parse_arguments(["--yaml=options/shape.yaml", "--datadir=examples", "--eval.vox_res=128", "--ckpt=weights/shape.ckpt"])
+    opt_cmd = options.parse_arguments(["--yaml=options/shape.yaml", "--datadir=examples", "--eval.vox_res=128", "--ckpt=/data/shape.ckpt"])
     opt = options.set(opt_cmd=opt_cmd, safe_check=False)
     opt.device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
 
@@ -148,7 +148,7 @@ def infer(input_image_path, input_mask_path):
         print("Downloading checkpoint...")
         subprocess.run(
             shlex.split(
-                "wget -q -O weights/shape.ckpt https://www.dropbox.com/scl/fi/hv3w9z59dqytievwviko4/shape.ckpt?rlkey=a2gut89kavrldmnt8b3df92oi&dl=0"
+                "wget -q -O /data/shape.ckpt https://www.dropbox.com/scl/fi/hv3w9z59dqytievwviko4/shape.ckpt?rlkey=a2gut89kavrldmnt8b3df92oi&dl=0"
             )
         )