update

app.py

@@ -24,7 +24,7 @@ with open("classes.txt") as f:
 
 
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-model = torchvision.models.resnet101(weights="DEFAULT")
+model = torchvision.models.resnet50(weights="DEFAULT")
 model.eval()
 model.to(device)
 
@@ -100,13 +100,14 @@ with gr.Blocks(title="Grad-CAM") as demo:
     gr.Markdown(
         """
 # Grad-CAM
+Unofficial re-implementation of Grad-CAM (https://arxiv.org/abs/1610.02391).<br>
 Upload an image and select a prediction to show the Grad-CAM heatmap.
 """
     )
 
     with gr.Row():
         with gr.Column():
-            layer = gr.Dropdown(layer_choices, label="ResNet-101", value="layer4")
+            layer = gr.Dropdown(layer_choices, label="ResNet-50", value="layer4")
             image = gr.Image(label="input", type="numpy")
             label = gr.Label(num_top_classes=10, label="top-10 predictions")
             exmpl = gr.Examples(["cat_dog.png"], image)