Update app.py

app.py

@@ -1,37 +1,18 @@
 import gradio as gr
-from transformers import pipeline
-from PIL import Image
-import requests
-from io import BytesIO
-python -m pip install 
+from easytts import EasyTTS
 
+# Initialize the EasyTTS model
+tts_model = EasyTTS()
 
-# Load the emotion detection model from Hugging Face's Transformers library
-emotion_model = pipeline("image-classification", model="EleutherAI/emotion-english", device=0)
+def text_to_speech(text_input):
+    # Use EasyTTS to convert text to speech
+    audio_data = tts_model.synthesize(text_input)
+    
+    # Display and play the audio
+    gr.output.Audio(audio_data).play()
 
-# Define the function to make predictions on user-uploaded images
-def predict_emotion(image):
-    # Open the uploaded image
-    img = Image.open(BytesIO(image.encode("utf-8")))
+# Create a Gradio interface
+iface = gr.Interface(fn=text_to_speech, inputs="text", outputs=None)
 
-    # Make prediction using the emotion detection model
-    result = emotion_model(img)
-
-    # Extract the emotion label with the highest confidence
-    emotion = result[0]['label']
-
-    return f"Predicted emotion: {emotion}"
-
-# Define the Gradio interface
-iface = gr.Interface(
-    fn=predict_emotion,
-    inputs=gr.Image(),
-    outputs="text",
-    live=True,
-    interpretation="default",
-    title="Face Expression Predictor",
-    description="Upload an image and get the predicted face expression."
-)
-
-# Launch the Gradio app
+# Launch the interface
 iface.launch()