update

app.py

@@ -78,23 +78,30 @@ placeholder_image = Image.new("RGBA", (512, 512), (0, 0, 0, 0))
 
 @spaces.GPU
 def process_selected_models(uploaded_image, selected_models):
-    results = []
+    selected_results = []
+    placeholder_results = []
+
     for model_name in model_name_mapping:
+        label = model_name_mapping[model_name]
+
         if uploaded_image is None:
-            results.append(gr.update(value=placeholder_image, label=f"{model_name_mapping[model_name]} (No input)"))
+            result = gr.update(value=placeholder_image, label=f"{label} (No input)")
         elif model_name in selected_models:
             try:
                 model, data_params = model_dict[model_name]
                 pixel_values = pil_to_tensor(uploaded_image, **data_params).unsqueeze(0).to(device)
                 output = model(pixel_values)[0]
                 reconstructed_image = tensor_to_pil(output[0].cpu(), **data_params)
-                results.append(gr.update(value=reconstructed_image, label=model_name_mapping[model_name]))
+                result = gr.update(value=reconstructed_image, label=label)
             except Exception as e:
                 print(f"Error in model {model_name}: {e}")
-                results.append(gr.update(value=placeholder_image, label=f"{model_name_mapping[model_name]} (Error)"))
+                result = gr.update(value=placeholder_image, label=f"{label} (Error)")
+            selected_results.append(result)
         else:
-            results.append(gr.update(value=placeholder_image, label=f"{model_name_mapping[model_name]} (Not selected)"))
-    return results
+            result = gr.update(value=placeholder_image, label=f"{label} (Not selected)")
+            placeholder_results.append(result)
+
+    return selected_results + placeholder_results
 
 with gr.Blocks() as demo:
     gr.Markdown("## VTBench")
@@ -140,15 +147,15 @@ with gr.Blocks() as demo:
     run_button = gr.Button("Start Processing")
 
     image_outputs = []
-    model_items = list(model_name_mapping.items())
-
+    model_names_ordered = list(model_name_mapping.keys())
     n_columns = 5
-    output_rows = [model_items[i:i+n_columns] for i in range(0, len(model_items), n_columns)]
+    output_rows = [model_names_ordered[i:i+n_columns] for i in range(0, len(model_names_ordered), n_columns)]
 
     with gr.Column():
         for row in output_rows:
             with gr.Row():
-                for model_name, display_name in row:
+                for model_name in row:
+                    display_name = model_name_mapping[model_name]
                     out_img = gr.Image(
                         label=f"{display_name} (Not run)",
                         value=placeholder_image,

src/model_processing.py

@@ -279,8 +279,8 @@ def get_model(model_path, model_name):
         data_params = {
             "target_image_size": (384, 384),
             "lock_ratio": True,
-            "center_crop": False,
-            "padding": True,
+            "center_crop": True,
+            "padding": False,
         }
 
     elif "var" in model_name.lower():
@@ -307,8 +307,8 @@ def get_model(model_path, model_name):
                 (512, 512) if "512" in model_name.lower() else (256, 256)
             ),
             "lock_ratio": True,
-            "center_crop": False,
-            "padding": True,
+            "center_crop": True,
+            "padding": False,
             "standardize": False,
         }
 
@@ -349,8 +349,8 @@ def get_model(model_path, model_name):
         data_params = {
             "target_image_size": (1024, 1024),
             "lock_ratio": True,
-            "center_crop": False,
-            "padding": True,
+            "center_crop": True,
+            "padding": False,
             "standardize": False,
         }
 
@@ -367,8 +367,8 @@ def get_model(model_path, model_name):
         data_params = {
             "target_image_size": (1024, 1024),
             "lock_ratio": True,
-            "center_crop": False,
-            "padding": True,
+            "center_crop": True,
+            "padding": False,
             "standardize": True,
         }
 
@@ -385,8 +385,8 @@ def get_model(model_path, model_name):
         data_params = {
             "target_image_size": (1024, 1024),
             "lock_ratio": True,
-            "center_crop": False,
-            "padding": True,
+            "center_crop": True,
+            "padding": False,
             "standardize": True,
         }
 
@@ -396,8 +396,8 @@ def get_model(model_path, model_name):
         data_params = {
             "target_image_size": (1024, 1024),
             "lock_ratio": True,
-            "center_crop": False,
-            "padding": True,
+            "center_crop": True,
+            "padding": False,
             "standardize": False,
         }
         model = GPTImage(data_params)