Update app.py

app.py

@@ -8,7 +8,23 @@ labels = learn.dls.vocab
 def predict(img):
     img = PILImage.create(img)
     pred,pred_idx,probs = learn.predict(img)
-    return {labels[i]: float(probs[i]) for i in range(len(labels))}
+     prediction = str(pred)
+    
+    # Provide explanation based on the prediction
+    if pred == "cancer_positive":
+        explanation = "The model predicts that the image shows signs of cancer."
+    else:
+        explanation = "The model predicts that the image does not show signs of cancer."
+    
+    return prediction, explanation
+
+# Create the Gradio interface
+inputs = gr.inputs.Image(label="Upload an 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>"