Update app.py

app.py

@@ -7,10 +7,10 @@ from gtts import gTTS
 from scenedetect import open_video, SceneManager, ContentDetector
 from transformers import BlipProcessor, BlipForConditionalGeneration
 from openai import OpenAI
+import base64
 # Load AI models
 caption_processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
-caption_model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base").to("cpu")
-caption_model = torch.quantization.quantize_dynamic(caption_model, {torch.nn.Linear}, dtype=torch.qint8)
+caption_model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base")
 client = OpenAI(
   api_key="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"
 )
@@ -19,16 +19,28 @@ client = OpenAI(
 # Streamlit App UI
 st.title("🎥 AI-Powered Video Summarization")
 # Define custom CSS
-st.markdown(
-    """
-    <style>
-    body {
-        background-color: #f6bf46;  /* Light Blue */
-    }
-    </style>
-    """,
-    unsafe_allow_html=True
-)
+
+
+def set_background(image_file):
+    with open(image_file, "rb") as image:
+        encoded_string = base64.b64encode(image.read()).decode()
+
+    st.markdown(
+        f"""
+        <style>
+        .stApp {{
+            background-image: url("data:image/jpg;base64,{encoded_string}");
+            background-size: cover;
+            background-position: center;
+            background-repeat: no-repeat;
+        }}
+        </style>
+        """,
+        unsafe_allow_html=True
+    )
+
+# Set background
+set_background("yellow-wallpaper.jpg")
     
 
 uploaded_file = st.file_uploader("📤 Upload a Video File", type=["mp4"])