Update app.py

app.py

@@ -3,14 +3,10 @@ from transformers import pipeline
 from gtts import gTTS 
 from PIL import Image
 import time
-#from playsound import playsound
-#from pydub import AudioSegment
-#from preferredsoundplayer import soundplay
 
-#@st.cache()
 @st.cache(allow_output_mutation=True)
 def load_model():
-    """Retrieves the trained model"""
+	"""Retrieves the trained model"""
     model = pipeline('image-to-text')
     return model
 
@@ -40,29 +36,8 @@ def main():
 		st.write(generated_text)
 		generated_audio = gTTS(generated_text)
 		generated_audio.save('demo.mp3')
-
 		audio_file = open(‘demo.mp3’, ‘rb’)
 		audio_bytes = audio_file.read()
 		st.audio(audio_bytes, format=‘audio/ogg’,start_time=0)
-
-		#html_string = """
-        #<audio controls autoplay>
-        #  <source src="demo.mp3" type="audio/mp3">
-        #</audio>
-        #"""
-		#sound = st.empty()
-		#sound.markdown(html_string, unsafe_allow_html=True)  # will display a st.audio with the sound you specified in the "src" of the html_string and autoplay it
-		#time.sleep(2)  # wait for 2 seconds to finish the playing of the audio
-		#sound.empty()  # optionally delete the element afterwards
-
-		#sound = AudioSegment.from_mp3("demo.mp3")
-		#sound.export("demo.wav", format="wav")
-		#soundplay("demo.mp3")
-		#playsound('demo.mp3')
-		#audio_file = open('demo.wav', 'rb')
-		#audio_bytes = audio_file.read()
-		#st.audio(audio_bytes, format='audio/wav')
-
-
 if __name__ == '__main__' : 
 	main()