Update app.py

app.py

@@ -29,6 +29,7 @@ def process_video_audio(video_path):
     
     face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')
 
+
     if len(wav[0]) > 261540:
         print(wav.shape)
         train_audio_wave[0, :] = wav[0][:261540]
@@ -69,7 +70,7 @@ def process_video_audio(video_path):
 def predict_emotion(video_path):
     last_frame, audio_path, train_visual, train_audio_wave, train_audio_cnn = process_video_audio(video_path)
     
-    model = load_model("model_vui_ve2392.keras")
+    model = load_model("model_vui_ve1024.keras")
     
     predictions = model.predict({
         "input_visual": train_visual,
@@ -81,7 +82,7 @@ def predict_emotion(video_path):
     return last_frame, audio_path, predicted_label
 
 def predict_emotion_gradio(video_path):
-    emotion_dict = {0: 'neutral', 1: 'calm', 2: 'happy', 3: 'sad', 4: 'angry', 5: 'fearful', 6: 'disgust', 7: 'surprised'}
+    emotion_dict = {0: 'neutral', 1: 'calm', 2: 'happy', 3: 'sad', 4: 'angry', 5: 'fearful'}
     last_frame, audio_path, predicted_label = predict_emotion(video_path)
     predicted_emotion = emotion_dict[predicted_label]
     return last_frame, audio_path, predicted_emotion