Update app.py

app.py

@@ -24,12 +24,16 @@ st.markdown(
     }
     .stTabs > div > button {
         background-color: #e0e0e0;
-        color: #1a1a1a;
+        color: #333333;  /* Darker tab text */
         font-weight: bold;
     }
     .stTabs > div > button:hover {
         background-color: #d0d0d0;
-        color: #1a1a1a;
+        color: #333333;
+    }
+    .stTabs > div > button[aria-selected="true"] {
+        background-color: #ffffff;
+        color: #333333;
     }
     .stButton > button {
         background-color: #e0e0e0;
@@ -40,13 +44,22 @@ st.markdown(
         background-color: #d0d0d0;
         color: #1a1a1a;
     }
+    /* Fix container height to prevent scrolling */
+    .main .block-container {
+        max-height: 100vh;
+        overflow-y: auto;
+    }
+    .stImage > img {
+        max-height: 50vh;  /* Limit image height */
+        object-fit: contain;
+    }
     </style>
     """,
     unsafe_allow_html=True
 )
 
 # Load Model
-model_path = 'https://huggingface.co/spaces/ankitkupadhyay/fire_and_smoke/resolve/main/best.pt'
+model_path = 'https://huggingface.co/spaces/tstone87/ccr-colorado/resolve/main/best.pt'
 try:
     model = YOLO(model_path)
 except Exception as ex:
@@ -58,10 +71,12 @@ if 'monitoring' not in st.session_state:
     st.session_state.monitoring = False
 if 'current_webcam_url' not in st.session_state:
     st.session_state.current_webcam_url = None
+if 'yt_monitoring' not in st.session_state:
+    st.session_state.yt_monitoring = False
 
 # Header
 st.title("AI Fire Watch")
-st.markdown("Monitor fire and smoke in real-time with AI precision.")
+st.markdown("Monitor fire and smoke in real-time with AI vision models.")
 
 # Tabs
 tabs = st.tabs(["Upload", "Webcam", "YouTube"])
@@ -75,19 +90,20 @@ with tabs[0]:
         uploaded_file = st.file_uploader("", type=["jpg", "jpeg", "png", "mp4"], label_visibility="collapsed")
         confidence = st.slider("Detection Threshold", 0.25, 1.0, 0.4, key="upload_conf")
     with col2:
+        frame_placeholder = st.empty()  # Pre-create placeholder
+        status_placeholder = st.empty()
         if uploaded_file:
             file_type = uploaded_file.type.split('/')[0]
             if file_type == 'image':
                 image = PIL.Image.open(uploaded_file)
                 results = model.predict(image, conf=confidence)
                 detected_image = results[0].plot()[:, :, ::-1]
-                st.image(detected_image, use_column_width=True)
-                st.write(f"Objects detected: {len(results[0].boxes)}")
+                frame_placeholder.image(detected_image, use_column_width=True)
+                status_placeholder.write(f"Objects detected: {len(results[0].boxes)}")
             elif file_type == 'video':
                 tfile = tempfile.NamedTemporaryFile(delete=False)
                 tfile.write(uploaded_file.read())
                 cap = cv2.VideoCapture(tfile.name)
-                frame_placeholder = st.empty()
                 while cap.isOpened():
                     ret, frame = cap.read()
                     if not ret:
@@ -95,6 +111,7 @@ with tabs[0]:
                     results = model.predict(frame, conf=confidence)
                     detected_frame = results[0].plot()[:, :, ::-1]
                     frame_placeholder.image(detected_frame, use_column_width=True)
+                    status_placeholder.write(f"Objects detected: {len(results[0].boxes)}")
                     time.sleep(0.05)
                 cap.release()
 
@@ -118,11 +135,11 @@ with tabs[1]:
             st.session_state.current_webcam_url = None
 
     with col2:
+        frame_placeholder = st.empty()
+        status_placeholder = st.empty()
+        timer_placeholder = st.empty()
+        
         if st.session_state.monitoring and st.session_state.current_webcam_url:
-            frame_placeholder = st.empty()
-            status_placeholder = st.empty()
-            timer_placeholder = st.empty()
-            
             # Try video stream first
             cap = cv2.VideoCapture(webcam_url)
             is_video_stream = cap.isOpened()
@@ -136,7 +153,6 @@ with tabs[1]:
                             status_placeholder.error("Video stream interrupted.")
                             break
                     else:
-                        # Fallback to image-based webcam
                         response = requests.get(webcam_url, timeout=5)
                         if response.status_code != 200:
                             status_placeholder.error(f"Fetch failed: HTTP {response.status_code}")
@@ -159,7 +175,7 @@ with tabs[1]:
                     if not is_video_stream:
                         time.sleep(remaining)
                     else:
-                        time.sleep(0.1)  # Faster update for video streams
+                        time.sleep(0.1)
                     
                 except Exception as e:
                     status_placeholder.error(f"Error: {e}")
@@ -180,18 +196,16 @@ with tabs[2]:
         start_yt = st.button("Start Analysis", key="yt_start")
         stop_yt = st.button("Stop Analysis", key="yt_stop")
 
-        if 'yt_monitoring' not in st.session_state:
-            st.session_state.yt_monitoring = False
-        
         if start_yt:
             st.session_state.yt_monitoring = True
         if stop_yt:
             st.session_state.yt_monitoring = False
 
     with col2:
+        frame_placeholder = st.empty()
+        status_placeholder = st.empty()
+        
         if st.session_state.yt_monitoring and youtube_url and youtube_url != "https://www.youtube.com/watch?v=<id>":
-            status_placeholder = st.empty()
-            frame_placeholder = st.empty()
             try:
                 status_placeholder.write("Initializing stream...")
                 streams = streamlink.streams(youtube_url)
@@ -213,7 +227,7 @@ with tabs[2]:
                             detected_frame = results[0].plot()[:, :, ::-1]
                             frame_placeholder.image(detected_frame, use_column_width=True)
                             status_placeholder.write(f"Objects detected: {len(results[0].boxes)}")
-                            time.sleep(0.1)  # Control frame rate
+                            time.sleep(0.1)
                         cap.release()
             except Exception as e:
                 status_placeholder.error(f"Error: {e}")