Update app.py

app.py

@@ -9,26 +9,9 @@ def predict(img):
     img = PILImage.create(img)
     pred,pred_idx,probs = learn.predict(img)
     prediction = str(pred)
-
-    explanations = {
-        "Cancer_negative": "The image does not show signs of cancer.",
-        "Cancer_positive": "The image shows signs of cancer.",
-        "implant_cancer_positive": "The image shows signs of implant-related cancer.",
-        "implant_cancer_negative": "The image does not show signs of implant-related cancer."
-    }
-
-    # Get the explanation for the predicted class
-    explanation = explanations[prediction]
     
-    return prediction, explanation
-
+    return prediction
 
-# Create the Gradio interface
-inputs = gr.inputs.Image(label="Upload a breast X-ray image")
-outputs = [
-    gr.outputs.Textbox(label="Prediction"),
-    gr.outputs.Textbox(label="Explanation")
-] 
 
 title = "Breast cancer detection with AI(Deep Transfer Learning)"
 description = "<p style='text-align: center'><b>As a radiologist or oncologist, it is crucial to know what is wrong with a breast x-ray image.<b><br><b>Upload the breast X-ray image to know what is wrong with a patients breast with or without inplant<b><p>"