Update app.py

app.py

@@ -40,7 +40,7 @@ def predictor(audio_filename):
     mfcc19 = v[18]
     mfcc20 = v[19]
 
-    features = np.array([chroma_stft,rmse,spec_cent,spec_bw,rolloff,zcr,mfcc1,mfcc2,mfcc3,mfcc4,mfcc5,mfcc6,mfcc7,mfcc8,mfcc9,mfcc10,mfcc11,mfcc12,mfcc13,mfcc14,mfcc15,mfcc16,mfcc17,mfcc18,mfcc19,mfcc20])
+    features = np.array([[chroma_stft,rmse,spec_cent,spec_bw,rolloff,zcr,mfcc1,mfcc2,mfcc3,mfcc4,mfcc5,mfcc6,mfcc7,mfcc8,mfcc9,mfcc10,mfcc11,mfcc12,mfcc13,mfcc14,mfcc15,mfcc16,mfcc17,mfcc18,mfcc19,mfcc20]])
 
     prediction = model.predict(StandardScaler().fit_transform(features))
     
@@ -52,6 +52,6 @@ def predictor(audio_filename):
 
 
 app = gr.Interface(predictor,
-gr.Audio(source="upload",label="Please Upload Audio file here:"),
-gr.Textbox(label="Result"),title="SMART UTI DETECTOR",description="UTI Prediction Model",examples=[["normal 1_rn.wav"]])
+inputs=gr.inputs.Audio(source="upload",label="Please Upload Audio file here:"),
+outputs=gr.outputs.Textbox(label="Result"),title="SMART UTI DETECTOR",description="UTI Prediction Model",examples=[["normal 1_rn.wav"]])
 app.launch()