updated

app.py

@@ -1,4 +1,47 @@
 import streamlit as st
+from transformers import pipeline
+from PIL import Image
 
-x = st.slider('Select a value')
-st.write(x, 'squared is', x * x)
+
+
+
+st.header("Character Captions")
+st.write("Have a character caption any image you upload!")
+character = st.selectbox("Choose a character", ["rapper", "monkey", "shrek", "unintelligible"])
+
+uploaded_img = st.file_uploader("Upload an image")
+
+if uploaded_img is not None:
+
+    image = Image.open(uploaded_img)
+    st.image(image)
+
+    image_captioner = pipeline("image-to-text", model="Salesforce/blip-image-captioning-large")
+
+    response = image_captioner(image)
+    caption = response[0]['generated_text']
+    st.write("Caption:", caption)
+
+    character_prompts = {
+        "rapper": f"Describe this scene like you're a rapper singing: {caption}.",
+        "monkey": f"Describe this scene like you're a monkey going bananas: {caption}.",
+        "shrek": f"Describe this scene like you're Shrek: {caption}.",
+        "unintelligible": f"Describe this scene in a way that makes no sense: {caption}."
+    }
+
+    prompt = character_prompts[character]
+    st.write(prompt)
+
+
+
+
+# pipe = pipeline("text-generation", model="meta-llama/Meta-Llama-Guard-2-8B")
+
+# # Pass the caption to another model
+
+# personality = "rapper"
+# prompt = personality_prompts[personality]
+
+# styled_caption = text_generator(prompt, max_length=100, num_return_sequences=1)
+
+# print(styled_caption[0]["generated_text"])