Update app.py

app.py

@@ -165,9 +165,35 @@ def return_prediction(mic, file):
     else:
         return "You must either provide a mic recording or a file"
     
+    '''
+        '1' => 0
+        '3' => 1
+        '5' => 2
+        '4' => 3
+        '2' => 4
+    '''
+
     score = score.item()
     score = str(round(100 * score, 2)) + "%"
-    return text_lab, score
+    neu = round(100 * out_prob[0, 0].item(), 2)
+    joy = round(100 * out_prob[0, 1].item(), 2)
+    aff = round(100 * out_prob[0, 2].item(), 2)
+    ang = round(100 * out_prob[0, 3].item(), 2)
+    sad = round(100 * out_prob[0, 4].item(), 2)
+    result_dict = {
+        "Neutral: ": neu,
+        "Joy: ": joy,
+        "Affection: ": aff,
+        "Anger: ": ang,
+        "Sadness: ": sad,
+    }
+    # order the dict in reverse order by value
+    result_dict = dict(sorted(result_dict.items(), key=lambda item: item[1], reverse=True))
+    keys = list(result_dict.keys())
+    values = list(result_dict.values())
+    result_string = keys[0] + "\t" + str(values[0]) + "%" + "\n" + keys[1] + "\t" + str(values[1]) + "%" + "\n" + keys[2] + "\t" + str(values[2]) + "%" + "\n" + keys[3] + "\t" + str(values[3]) + "%" + "\n" + keys[4] + "\t" + str(values[4]) + "%"
+    # return text_lab, score
+    return result_string
     
 
 classifier = foreign_class(source="Porjaz/wavlm-base-emo-fi", pymodule_file="custom_interface.py", classname="CustomEncoderWav2vec2Classifier")
@@ -184,4 +210,4 @@ gradio_app = gr.Interface(
 
 
 if __name__ == "__main__":
-    gradio_app.launch(share=True, ssl_verify=False)
+    gradio_app.launch(share=True, ssl_verify=False)