final commit

app.py

@@ -0,0 +1,65 @@
+import streamlit as st
+import requests
+import io
+import base64
+from PIL import Image
+import os
+
+hf_api_key = os.getenv("HUGGINGFACE_TOKEN")
+
+headers = {"Authorization": f"Bearer {hf_api_key}"}
+ANALYSIS_API_URL = "https://api-inference.huggingface.co/models/dandelin/vilt-b32-finetuned-vqa"
+GENERATION_API_URL = "https://api-inference.huggingface.co/models/thejagstudio/3d-animation-style-sdxl"
+
+def query_analysis(image_bytes, question):
+    payload = {
+        "inputs": {
+            "question": question,
+            "image": base64.b64encode(image_bytes).decode('utf-8')
+        }
+    }
+    response = requests.post(ANALYSIS_API_URL, headers=headers, json=payload)
+    if response.status_code == 200 and response.json():
+        return response.json()[0].get('answer', 'unspecified')
+    return 'unspecified'
+
+def query_generation(prompt, image_bytes):
+    payload = {
+        "inputs": prompt,
+        "image": base64.b64encode(image_bytes).decode('utf-8')
+    }
+    response = requests.post(GENERATION_API_URL, headers=headers, json=payload)
+    return response.content
+
+st.title("Image Insight & Generation Studio👻")
+
+uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
+
+if uploaded_file is not None:
+    st.image(uploaded_file, caption="Uploaded Image", use_column_width=True)
+    
+    image_bytes = uploaded_file.read()
+
+    user_prompt = st.text_input("Enter additional description for image generation:")
+
+    if st.button("Generate Image"):
+        gender = query_analysis(image_bytes, "What is the gender of the person in the image?")
+        clothing = query_analysis(image_bytes, "What is the person wearing and which color?")
+        hair_color = query_analysis(image_bytes, "What is the hair color of the person?")
+        facial_expression = query_analysis(image_bytes, "What is the facial expression of the person?")
+        
+        if gender.lower() == "female":
+            prompt = f"create one school-going girl with {hair_color}, wearing {clothing}, showing a {facial_expression}. {user_prompt}"
+        elif gender.lower() == "male":
+            prompt = f"create one school-going boy with {hair_color}, wearing {clothing}, showing a {facial_expression}. {user_prompt}"
+        else:
+            prompt = f"create one school-going child with {hair_color}, wearing {clothing}, showing a {facial_expression}. {user_prompt}"
+        
+        generated_image_data = query_generation(prompt, image_bytes)
+        generated_image = Image.open(io.BytesIO(generated_image_data))
+        
+        st.image(generated_image, caption="Generated Image", use_column_width=True)
+
+        buffered = io.BytesIO()
+        generated_image.save(buffered, format="PNG")
+        st.download_button(label="Download Generated Image", data=buffered.getvalue(), file_name="generated_image.png", mime="image/png")