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Update app.py
Browse files
app.py
CHANGED
@@ -5,40 +5,71 @@ import cv2
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import random
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import time
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from gtts import gTTS
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import
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import tempfile
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import threading
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from datetime import datetime, timedelta
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# Initialize pygame mixer for audio alerts
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pygame.mixer.quit()
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pygame.mixer.init()
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# Load YOLOv8 model
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yolo = YOLO("yolov8n.pt")
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# Streamlit app layout
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st.set_page_config(page_title="Assistive Vision App", layout="wide")
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st.
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# Placeholder for video
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# User controls
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alert_categories = {"person", "cat", "dog", "knife", "fire", "gun"}
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last_alert_time = {}
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alert_cooldown = timedelta(seconds=10) #
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# Create a directory for temporary audio files
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audio_temp_dir = "audio_temp_files"
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if not os.path.exists(audio_temp_dir):
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os.makedirs(audio_temp_dir)
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def play_audio_alert(label, position):
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"""Generate and play an audio alert."""
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@@ -54,23 +85,14 @@ def play_audio_alert(label, position):
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tts.save(temp_audio_path)
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try:
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def cleanup_audio():
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while pygame.mixer.music.get_busy():
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time.sleep(0.1)
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pygame.mixer.music.stop()
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if os.path.exists(temp_audio_path):
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os.remove(temp_audio_path)
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threading.Thread(target=cleanup_audio, daemon=True).start()
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except Exception as e:
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print(f"Audio playback error: {e}")
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results = yolo(frame)
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result = results[0]
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@@ -79,48 +101,55 @@ def process_frame(frame, enable_audio):
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x1, y1, x2, y2 = map(int, box.xyxy[0])
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label = result.names[int(box.cls[0])]
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if enable_audio and label not in alert_categories:
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continue
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# Determine object position
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frame_center_x = frame.shape[1] // 2
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position = "left" if
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detected_objects[label] = position
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# Draw bounding box and label on the frame
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cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 255, 0), 2)
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cv2.putText(
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return detected_objects, frame
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if start_detection:
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st.success("
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try:
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video_capture = cv2.VideoCapture(0)
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if not video_capture.isOpened():
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st.error("
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else:
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while not stop_detection:
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ret, frame = video_capture.read()
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if not ret:
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st.error("
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break
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detected_objects, processed_frame = process_frame(frame,
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# Convert frame to RGB for Streamlit display
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frame_rgb = cv2.cvtColor(processed_frame, cv2.COLOR_BGR2RGB)
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if enable_audio:
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current_time = datetime.now()
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for label, position in detected_objects.items():
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if
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play_audio_alert(label, position)
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last_alert_time[label] = current_time
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@@ -129,9 +158,9 @@ if start_detection:
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except Exception as e:
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st.error(f"An error occurred: {e}")
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finally:
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video_capture.
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elif stop_detection:
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st.warning("
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import random
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import time
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from gtts import gTTS
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from playsound import playsound
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from datetime import datetime, timedelta
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# Load YOLOv8 model
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yolo = YOLO("yolov8n.pt")
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# Streamlit app layout
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st.set_page_config(page_title="Assistive Vision App", layout="wide")
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st.markdown(
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"""
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<style>
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body {
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background-color: #f7f9fc;
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font-family: "Arial", sans-serif;
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}
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.stButton>button {
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background-color: #1a73e8;
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color: white;
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justify-content: center;
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align-items: center;
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border-radius: 10px;
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padding: 10px;
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margin: 5px;
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}
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.stCheckbox {
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margin-top: 20px;
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}
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</style>
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""",
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unsafe_allow_html=True,
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)
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# Display welcome image
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welcome_image_path = "bismillah.png"
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if os.path.exists(welcome_image_path):
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st.image(welcome_image_path, use_container_width=True, caption="Bismillah hir Rehman Ar Raheem")
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else:
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st.warning("Welcome image not found! Please add 'bismillah.png' in the script directory.")
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st.title("Object Detection & Assistive Vision App for Visually Impaired People")
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st.write("This application provides real-time object recognition and optional audio alerts.")
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# Directory to store temp audio files
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audio_temp_dir = "audio_temp_files"
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if not os.path.exists(audio_temp_dir):
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os.makedirs(audio_temp_dir)
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# Placeholder for video frames
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stframe = st.empty()
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# User controls
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col1, col2 = st.columns(2)
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with col1:
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start_detection = st.button("Start Detection")
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with col2:
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stop_detection = st.button("Stop Detection")
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audio_activation = st.checkbox("Enable Audio Alerts", value=False)
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# Categories for audio alerts
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alert_categories = {"person", "cat", "dog", "knife", "fire", "gun"}
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# Dictionary to store the last alert timestamp for each object
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last_alert_time = {}
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alert_cooldown = timedelta(seconds=10) # 10-second cooldown for alerts
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def play_audio_alert(label, position):
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"""Generate and play an audio alert."""
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tts.save(temp_audio_path)
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try:
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playsound(temp_audio_path)
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os.remove(temp_audio_path) # Clean up after playing
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except Exception as e:
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print(f"Audio playback error: {e}")
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def process_frame(frame, audio_mode):
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"""Process a single video frame for object detection."""
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results = yolo(frame)
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result = results[0]
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x1, y1, x2, y2 = map(int, box.xyxy[0])
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label = result.names[int(box.cls[0])]
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if audio_mode and label not in alert_categories:
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continue
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frame_center_x = frame.shape[1] // 2
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obj_center_x = (x1 + x2) // 2
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position = "left" if obj_center_x < frame_center_x else "right"
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detected_objects[label] = position
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cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 255, 0), 2)
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cv2.putText(
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frame,
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f"{label}",
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(x1, y1 - 10),
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cv2.FONT_HERSHEY_SIMPLEX,
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0.5,
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(0, 255, 0),
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2,
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)
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return detected_objects, frame
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# Main logic
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if start_detection:
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st.success("Object detection started.")
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try:
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video_capture = cv2.VideoCapture(0)
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if not video_capture.isOpened():
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st.error("Could not access the webcam. Please check your camera settings.")
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else:
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while not stop_detection:
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ret, frame = video_capture.read()
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if not ret:
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st.error("Failed to capture video. Please check your camera.")
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break
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detected_objects, processed_frame = process_frame(frame, audio_activation)
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frame_rgb = cv2.cvtColor(processed_frame, cv2.COLOR_BGR2RGB)
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stframe.image(frame_rgb, channels="RGB", use_column_width=True)
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if audio_activation:
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current_time = datetime.now()
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for label, position in detected_objects.items():
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if (
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label not in last_alert_time
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or current_time - last_alert_time[label] > alert_cooldown
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):
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play_audio_alert(label, position)
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last_alert_time[label] = current_time
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except Exception as e:
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st.error(f"An error occurred: {e}")
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finally:
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if 'video_capture' in locals() and video_capture.isOpened():
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video_capture.release()
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cv2.destroyAllWindows()
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elif stop_detection:
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st.warning("Object detection stopped.")
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