Update app.py

app.py

@@ -26,19 +26,15 @@ from eval_wrapper.eval import EvalWrapper, eval_scene
 device = 'cuda' if torch.cuda.is_available() else 'cpu'
 
 outdir = "/tmp/rayst3r"
-
+print("Loading MoGe model")
 moge_model = MoGeModel.from_pretrained("Ruicheng/moge-vitl").to(device)
 dino_model = torch.hub.load('facebookresearch/dinov2', "dinov2_vitl14_reg")
 dino_model.eval()
 dino_model.to(device)
 
-print("Loading RaySt3R model")
-rayst3r_checkpoint = hf_hub_download("bartduis/rayst3r", "rayst3r.pth")
-rayst3r_model = EvalWrapper(rayst3r_checkpoint,device='cpu')
-rayst3r_model = rayst3r_model.to(device)
-print("Loaded all models")
 
-print("Loading MoGe model")
+
+
 # Load the model from huggingface hub (or load from local).
 
 
@@ -111,7 +107,14 @@ def prep_for_rayst3r(img,depth_dict,mask):
 def rayst3r_to_glb(img,depth_dict,mask,max_total_points=10e6,rotated=False):
     prep_for_rayst3r(img,depth_dict,mask)
     print('Doneneee')
+    
+    print("Loading RaySt3R model")
+    rayst3r_checkpoint = hf_hub_download("bartduis/rayst3r", "rayst3r.pth")
+    rayst3r_model = EvalWrapper(rayst3r_checkpoint,device='cpu')
+    rayst3r_model = rayst3r_model.to(device)
+    print("Loaded rayst3r_model")
     print(rayst3r_model)
+    
     rayst3r_points = eval_scene(rayst3r_model,os.path.join(outdir, "input"),do_filter_all_masks=True,dino_model=dino_model, device = device).cpu()
 
     # subsample points