Upload app.py

app.py

@@ -57,7 +57,8 @@ def create_depth_demo(model, device):
         image = torch.nn.functional.interpolate(image, (440,480), mode='bilinear', align_corners=True)
         image = F.pad(image, (0, 0, 40, 0))
         with torch.no_grad():
-            pred = model(image)['pred_d']
+            pred = model(image)#['pred_d']
+            print('!!!', pred.keys())
 
         pred = pred[:,:,40:,:]
         pred = torch.nn.functional.interpolate(pred, shape[2:], mode='bilinear', align_corners=True)
@@ -88,6 +89,7 @@ def create_refseg_demo(model, tokenizer, device):
         image_t = transforms.Normalize(mean=[0.5, 0.5, 0.5], std=[0.5, 0.5, 0.5])(image_t)
         shape = image_t.shape
         image_t = torch.nn.functional.interpolate(image_t, (512,512), mode='bilinear', align_corners=True)
+        print('!!!', text)
         input_ids = tokenizer(text=text, truncation=True, max_length=40, return_length=True,
             return_overflowing_tokens=False, padding="max_length", return_tensors="pt")['input_ids'].to(device)