updated app.py

app.py

@@ -40,7 +40,7 @@ def predict(Image):
 
     with torch.no_grad():
         grade = torch.softmax(model(img.float()), dim=1)[0]
-    category = ["None", "Mild", "Moderate", "Severe", "Proliferative"]
+    category = ["Normal", "Mild", "Moderate", "Severe", "Proliferative"]
     output_dict = {}
     for cat, value in zip(category, grade):
         output_dict[cat] = value.item()
@@ -50,7 +50,7 @@ def predict(Image):
 
 
 image = gr.Image(type="pil")#shape=(224, 224), image_mode="RGB")
-label = gr.Label(label="Grade")
+label = gr.Label(label="Level")
 
 demo = gr.Interface(
     fn=predict,