Update app.py

app.py

@@ -9,20 +9,20 @@ import gradio as gr
 from model import MFCC_CNN
 
 EMOTIONS = {
-    'neutral_Male': 9,
-    'happy_Male': 7,
-    'sad_Male': 11,
-    'angry_Male': 1,
-    'fear_Male': 5,
-    'disgust_Male': 3,
-    'surprise_Male': 13,
-    'neutral_Female': 8,
-    'happy_Female': 6,
-    'sad_Female': 10,
-    'angry_Female': 0,
-    'fear_Female': 4,
-    'disgust_Female': 2,
-    'surprise_Female': 12
+    9 : 'neutral_Male',
+    7: 'happy_Male',
+    11: 'sad_Male',
+    1: 'angry_Male',
+    5: 'fear_Male',
+    3: 'disgust_Male',
+    13 : 'surprise_Male',
+    8 : 'neutral_Female',
+    6 : 'happy_Female',
+    10 : 'sad_Female',
+    0 : 'angry_Female',
+    4 : 'fear_Female',
+    2 : 'disgust_Female',
+    12 : 'surprise_Female'
     }
 
 # LOAD AUDIO
@@ -35,7 +35,7 @@ WIN_LENGTH = 2048
 WINDOW = 'hann'
 HOP_LENGTH = 512
 
-PATH = './chekpoint/models-epoch=97-val_loss=2.09.ckpt'
+PATH = 'C:\python_tmp\gradio_test\chekpoint\models-epoch=97-val_loss=2.09.ckpt'
 ckpt = torch.load(PATH)
 
 pretrained_model = MFCC_CNN(14)
@@ -54,7 +54,7 @@ def processAudio(audio_file):
     feature_set = []
 
     mfcc = lr.feature.mfcc(y=signal,
-                                    r=sr,
+                                    sr=sr,
                                     n_mfcc=N_MFCC,
                                     win_length=WIN_LENGTH,
                                     window=WINDOW,
@@ -71,7 +71,7 @@ def processAudio(audio_file):
     
 demo = gr.Interface(
     fn=processAudio,
-    inputs=gr.Audio(),
+    inputs=gr.Audio(type='filepath'),
     outputs=gr.Label(),
     examples=[
         [os.path.join(os.path.dirname(__file__), "files/03-01-01-01-02-02-01.wav")],
@@ -81,4 +81,4 @@ demo = gr.Interface(
     )
 
 if __name__ == '__main__':
-    demo.launch()
+    demo.launch()