Create app.py

app.py

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+import streamlit as st
+from transformers import pipeline
+from PIL import Image
+
+# Creates a brief description for the pictures
+def generate_caption(image):
+    with st.spinner("Analysing the Pictures for Key Message..."):
+        # Loads the BLIP model to examine and describe the picture
+        image_to_text = pipeline("image-to-text", model="Salesforce/blip-image-captioning-large")
+        caption = image_to_text(image)[0]["generated_text"]
+    return caption
+
+# Builds a story from the picture’s description
+def generate_story(caption):
+    with st.spinner("Enhancing the Story for better Details..."):
+        # Uses the text generation model to create a story based on the description
+        pipe = pipeline("text-generation", model="TheBloke/phi-2-GGUF")
+        story = pipe(caption)[0]['generated_text']
+    return story
+
+# Turns the story into audio
+def generate_audio(story):
+    with st.spinner("Turning story into News audio..."):
+        # Uses a speech model to turn description into audio
+        pipe = pipeline("text-to-speech", model="hexgrad/Kokoro-82M")
+        audio = pipe(story)
+    return audio
+
+# Streamlit UI: Makes a simple interface to generate the audio
+
+# Displays the title
+st.title("Tool for the Reporter - Turning the News Photo into Audio")
+
+# Describes the app for users
+st.write("Please upload the News Photo within 200MB")
+
+# Allows picture uploads
+uploaded_file = st.file_uploader("Upload the Photo below", type=["png", "jpg", "jpeg"])
+
+if uploaded_file is not None:
+    # Shows the uploaded picture
+    image = Image.open(uploaded_file)
+    st.image(image, caption="Your Picture!", use_container_width=True)
+    
+    # Gets the picture’s description
+    image_caption = generate_caption(image)
+    st.subheader("Phot Description:")
+    st.write(image_caption)
+
+    # Generate the News descriptions
+    story_telling = generate_story(image_caption)
+    st.subheader("The News:")
+    st.write(story_telling)
+
+    # Generates audio
+    audio = generate_audio(story_telling)
+    if st.button("Hear the News"):
+        st.audio(audio['audio'], 
+                 format="audio/wav", 
+                 start_time=0, 
+                 sample_rate=audio['sampling_rate'])