Update app.py

app.py

@@ -33,7 +33,7 @@ def run_theia(image):
     image = torchvision.transforms.Resize(size=(224, 224))(image)
     images = [image]
     
-    theia_decode_results, gt_decode_results = decode_everything(
+    theia_decode_results, gt_results = decode_everything(
         theia_model=theia_model,
         feature_means=feature_means,
         feature_vars=feature_vars,
@@ -51,9 +51,9 @@ def run_theia(image):
     theia_decode_dino = (255.0 * theia_decode_results[0]).astype(np.uint8)[:, width // 4 : 2 * width // 4, :]
     theia_decode_sam = (255.0 * theia_decode_results[0]).astype(np.uint8)[:, 2 * width // 4 : 3 * width // 4, :]
     theia_decode_depth = (255.0 * theia_decode_results[0]).astype(np.uint8)[:, 3 * width // 4 :, :]
-    gt_dino = (255.0 * theia_decode_results[0]).astype(np.uint8)[:, width // 4 : 2 * width // 4, :]
-    gt_sam = (255.0 * theia_decode_results[0]).astype(np.uint8)[:, 2 * width // 4 : 3 * width // 4, :]
-    gt_depth = (255.0 * theia_decode_results[0]).astype(np.uint8)[:, 3 * width // 4 :, :]
+    gt_dino = (255.0 * gt_results[0]).astype(np.uint8)[:, width // 4 : 2 * width // 4, :]
+    gt_sam = (255.0 * gt_results[0]).astype(np.uint8)[:, 2 * width // 4 : 3 * width // 4, :]
+    gt_depth = (255.0 * gt_results[0]).astype(np.uint8)[:, 3 * width // 4 :, :]
 
     theia_output = [(theia_decode_dino, "DINOv2"), (theia_decode_sam, "SAM"), (theia_decode_depth, "Depth-Anything")]
     gt_output = [(gt_dino, "DINOv2"), (gt_sam, "SAM"), (gt_depth, "Depth-Anything")]