Use DPT_Large model

app.py

@@ -5,25 +5,13 @@ import numpy as np
 from PIL import Image
 import time
 
-midas = torch.hub.load("intel-isl/MiDaS", "MiDaS")
-
-use_large_model = True
-
-if use_large_model:
-    midas = torch.hub.load("intel-isl/MiDaS", "MiDaS")
-else:
-    midas = torch.hub.load("intel-isl/MiDaS", "MiDaS_small")
+midas = torch.hub.load("intel-isl/MiDaS", "DPT_Large")
 
 device = "cpu"
 midas.to(device)
 
 midas_transforms = torch.hub.load("intel-isl/MiDaS", "transforms")
-
-if use_large_model:
-    transform = midas_transforms.default_transform
-else:
-    transform = midas_transforms.small_transform
-
+transform = midas_transforms.dpt_transform
 
 def depth(img):
   original_image = img