minor tweaks

app.py

@@ -13,9 +13,9 @@ device = 'cuda' if torch.cuda.is_available() else 'cpu'
 
 
 MODELS = {
-    "BISENET-BASE": loadModel('bisenet', device, 'weight_Base.pth'),
+    # "BISENET-BASE": loadModel('bisenet', device, 'weight_Base.pth'),
     "BISENET-BEST": loadModel('bisenet', device, 'weight_Best.pth'),
-    "BISENETV2-BASE": loadModel('bisenetv2', device, 'weight_Base.pth'),
+    # "BISENETV2-BASE": loadModel('bisenetv2', device, 'weight_Base.pth'),
     "BISENETV2-BEST": loadModel('bisenetv2', device, 'weight_Best.pth')
 }
 
@@ -70,7 +70,10 @@ with gr.Blocks(title="Semantic Segmentation Predictors") as demo:
         with gr.Column():
             image_input = gr.Image(type="pil", label="Upload image")
             model_selector = gr.Radio(
-                choices=["BiSeNet-Base", "BiSeNet-Best", "BiSeNetV2-Base", "BiSeNetV2-Best"],
+                choices=[   #"BiSeNet-Base", 
+                            "BiSeNet-Best", 
+                            # "BiSeNetV2-Base", 
+                            "BiSeNetV2-Best"],
                 value="BiSeNet-Base",
                 label="Select the real time segmentation model"
                 )