Update app.py

app.py

@@ -41,6 +41,7 @@ def inference(input_img, transparancy = 0.5, target_layer_number = -1):
     input_img = transform(input_img)
     input_img = input_img.unsqueeze(0)
     outputs = model(input_img)
+    print(outputs)
     softmax =  torch.nn.Softmax(dim=0)
     o = softmax(outputs.flattern())
     confidences = {classes[i]:float(o[i] for i in range(10))}
@@ -61,7 +62,7 @@ demo = gr.Inference(
         gr.Slider(0,1,value=0.5,label="Overall opacity of the overelay"),
         gr.Slider(-2,-1, value =-2, step=1, label= "Which layer for Gradcam")
     ],
-    outputd = [
+    outputs = [
         "text",
         gr.IMage(width= 256, height=256,label="Output"),
         gr.Label(num_top_classes=3)