Update app.py

app.py

@@ -11,8 +11,9 @@ from transformers import (
     AutoImageProcessor,
     AutoModelForObjectDetection
 )
-import os
 import tempfile
+import streamlit as st
+from huggingface_hub import hf_hub_download
 
 # -------------------- Configuration -------------------- #
 DEVICE = torch.device("cuda" if torch.cuda.is_available() else "cpu")
@@ -259,19 +260,10 @@ def analyze_video(video_path):
     print(f"\n🎯 Final Score: {score}")  # Debugging line
     return score  # ✅ Ensure this score is returned properly
 
-
-
 # -------------------- Execution -------------------- #
-import streamlit as st
-import tempfile
+# Streamlit Interface
 
-def local_css(file_name):
-    with open(file_name) as f:
-        st.markdown(f"<style>{f.read()}</style>", unsafe_allow_html=True)
-local_css("style.css")  # Ensure you have a separate style.css file
-
-# Sidebar for Navigation
-# Navigation
+# Side Navigation
 st.sidebar.title("Navigation")
 page = st.sidebar.radio("", ["Home", "Analyze Video", "About"])
 
@@ -307,7 +299,7 @@ if page == "Home":
 
 
 elif page == "Analyze Video":
-    uploaded_file = st.file_uploader("Upload a Video", type=["mp4", "mov"], label_visibility="hidden")
+    uploaded_file = st.file_uploader("Upload a Video", type=["mp4", "mov"])
 
     if uploaded_file is not None:
         # Save uploaded file to a temporary location
@@ -317,14 +309,14 @@ elif page == "Analyze Video":
 
         st.video(temp_video_path)
 
-        if st.button("Analyze Video", key="analyze_video_button"):
+        if st.button("Analyze Video", label_visibility="collapsed"):
             with st.spinner("Analyzing..."):
                 try:
                     score = analyze_video(temp_video_path)  # ✅ Ensure function exists
                     
-                    # Debugging Line
                     st.write(f"Analysis Score: {score}")  
                     float(score)
+                    
                     # Display result based on score
                     if score >= 3.5 :
                         st.markdown(f"""