Update app.py

app.py

@@ -1,77 +1,52 @@
 import streamlit as st
 from transformers import pipeline
-import soundfile as sf
-import os
-
-# Cache models to avoid reloading on every interaction
-@st.cache_resource
-def load_models():
-    return {
-        "image_to_text": pipeline("image-to-text", model="Salesforce/blip-image-captioning-base"),
-        "story_gen": pipeline("text-generation", model="distilbert/distilgpt2"),
-        "text_to_speech": pipeline("text-to-speech", model="facebook/mms-tts-eng")
-    }
 
 # function part
-def img2text(url, processor):
-    text = processor(url)[0]["generated_text"]
+# img2text
+def img2text(url):
+    image_to_text_model = pipeline("image-to-text", model="Salesforce/blip-image-captioning-base")
+    text = image_to_text_model(url)[0]["generated_text"]
     return text
 
-def text2story(text, generator, max_length=150):
-    prompt = f"Create a story based on: {text}"
-    story = generator(
-        prompt,
-        max_length=max_length,
-        temperature=0.7,
-        do_sample=True
-    )[0]['generated_text']
-    return story[:1000]  # Safety truncation
+# text2story
+def text2story(text):
+    story_generator = pipeline("text-generation", model="distilgpt2")  # Corrected pipeline initialization
+    story_text = story_generator(text, max_length=150, num_return_sequences=1)  # Pass parameters here
+    return story_text[0]["generated_text"]  # Extract generated text
+
+# text2audio
+def text2audio(story_text):
+    tts_model = pipeline("text-to-speech", model="facebook/mms-tts-eng")  # Initialize pipeline
+    audio_data = tts_model(story_text)  # Generate audio
+    return audio_data  # Return generated audio
+     
+
+#main part
+
+st.set_page_config(page_title="Your Image to Audio Story",
+                   page_icon="🦜")
+st.header("Turn Your Image to Audio Story")
+uploaded_file = st.file_uploader("Select an Image...")
+
+if uploaded_file is not None:
+    print(uploaded_file)
+    bytes_data = uploaded_file.getvalue()
+    with open(uploaded_file.name, "wb") as file:
+        file.write(bytes_data)
+
+    st.image(uploaded_file, caption="Uploaded Image",
+             use_column_width=True)
 
-def text2audio(text, synthesizer):
-    audio = synthesizer(text)
-    return audio
+    #Stage 1: Image to Text
+    st.text('Processing img2text...')
+    scenario = img2text(uploaded_file.name)
+    st.write(scenario)
 
-# main part
-def main():
-    st.set_page_config(page_title="Your Image to Audio Story", page_icon="🦜")
-    st.header("Turn Your Image to Audio Story")
-    
-    # Load models once
-    models = load_models()
-    
-    uploaded_file = st.file_uploader("Select an Image...", type=["jpg", "jpeg", "png"])
-    
-    if uploaded_file is not None:
-        # Save uploaded file temporarily
-        temp_path = f"temp_{uploaded_file.name}"
-        with open(temp_path, "wb") as f:
-            f.write(uploaded_file.getvalue())
-            
-        st.image(uploaded_file, caption="Uploaded Image", use_column_width=True)
-        
-        # Stage 1: Image to Text
-        with st.spinner('Generating caption...'):
-            scenario = img2text(temp_path, models["image_to_text"])
-            st.subheader("Image Caption")
-            st.write(scenario)
-        
-        # Stage 2: Text to Story
-        with st.spinner('Creating story...'):
-            story = text2story(scenario, models["story_gen"])
-            st.subheader("Generated Story")
-            st.write(story)
-        
-        # Stage 3: Story to Audio
-        with st.spinner('Generating audio...'):
-            audio = text2audio(story, models["text_to_speech"])
-            sf.write("temp_audio.wav", audio["audio"], samplerate=audio["sampling_rate"])
-            
-            st.subheader("Audio Story")
-            st.audio("temp_audio.wav")
-            
-        # Clean up temp files
-        os.remove(temp_path)
-        os.remove("temp_audio.wav")
+    #Stage 2: Text to Story
+    st.text('Generating a story...')
+    story = text2story(scenario)
+    st.write(story)
 
-if __name__ == "__main__":
-    main()
+    #Stage 3: Story to Audio data
+    st.text('Generating audio data...')
+    audio_data =text2audio(story)