Update app.py

app.py

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+import os
+import streamlit as st
+from ultralytics import YOLO
+import cv2
+import random
+import time
+from gtts import gTTS
+import pygame
+import threading
+from datetime import datetime, timedelta
+
+# Initialize pygame mixer
+pygame.mixer.quit()  # Ensure the mixer is fully stopped
+pygame.mixer.init()
+
+# Load YOLOv8 model
+yolo = YOLO("yolov8n.pt")
+
+# Streamlit app layout
+st.set_page_config(page_title="Assistive Vision App", layout="centered")
+st.title("Assistive Vision App for Visual Impairments")
+st.write("This application provides real-time object recognition and optional audio alerts.")
+
+# Directory to store temp audio files
+audio_temp_dir = "audio_temp_files"
+if not os.path.exists(audio_temp_dir):
+    os.makedirs(audio_temp_dir)
+
+# Placeholder for video frames
+stframe = st.empty()
+
+# User controls
+start_detection = st.button("Start Detection")
+stop_detection = st.button("Stop Detection")
+audio_activation = st.checkbox("Enable Audio Alerts", value=False)
+
+# Categories for audio alerts (hazardous objects or living things)
+alert_categories = {"person", "cat", "dog", "knife", "fire", "gun"}
+
+# Dictionary to store the last alert timestamp for each object
+last_alert_time = {}
+alert_cooldown = timedelta(seconds=10)  # 10-second cooldown for alerts
+
+
+def play_audio_alert(label, position):
+    """Generate and play an audio alert."""
+    phrases = [
+        f"Be careful, there's a {label} on your {position}.",
+        f"Watch out! {label} detected on your {position}.",
+        f"Alert! A {label} is on your {position}.",
+    ]
+    caution_note = random.choice(phrases)
+
+    # Generate a unique audio filename using timestamp
+    temp_file_path = os.path.join(audio_temp_dir, f"temp_{datetime.now().strftime('%Y%m%d_%H%M%S_%f')}.mp3")
+
+    # Generate audio
+    tts = gTTS(caution_note)
+    tts.save(temp_file_path)
+
+    try:
+        # Load and play the audio using pygame
+        pygame.mixer.music.load(temp_file_path)
+        pygame.mixer.music.play()
+
+        # Create a new thread to handle file cleanup after playback
+        def cleanup_audio_file():
+            while pygame.mixer.music.get_busy():  # Wait until audio finishes playing
+                time.sleep(0.1)
+
+            # After music finishes, stop the music and try to remove the file
+            pygame.mixer.music.stop()  # Explicitly stop the music before cleanup
+
+            try:
+                # Try to remove the file after playback is finished
+                os.remove(temp_file_path)
+            except OSError as e:
+                print(f"Error deleting file {temp_file_path}: {e}")
+
+        # Start the cleanup thread
+        threading.Thread(target=cleanup_audio_file, daemon=True).start()
+
+    except Exception as e:
+        print(f"Error playing audio alert: {e}")
+
+
+def process_frame(frame, audio_mode):
+    """Process a single video frame for object detection."""
+    results = yolo(frame)
+    result = results[0]
+
+    detected_objects = {}  # Dictionary to store object labels and their positions
+    for box in result.boxes:
+        x1, y1, x2, y2 = map(int, box.xyxy[0])
+        label = result.names[int(box.cls[0])]
+
+        # Apply filtering logic for audio mode
+        if audio_mode and label not in alert_categories:
+            continue
+
+        # Determine position
+        frame_center_x = frame.shape[1] // 2
+        obj_center_x = (x1 + x2) // 2
+        position = "left" if obj_center_x < frame_center_x else "right"
+
+        # Update detected objects with label and position
+        detected_objects[label] = position
+
+        # Draw bounding boxes
+        cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 255, 0), 2)
+        cv2.putText(
+            frame,
+            f"{label}",
+            (x1, y1 - 10),
+            cv2.FONT_HERSHEY_SIMPLEX,
+            0.5,
+            (0, 255, 0),
+            2,
+        )
+
+    return detected_objects, frame
+
+
+# Main logic
+if start_detection:
+    st.success("Object detection started.")
+    try:
+        video_capture = cv2.VideoCapture(0)
+        if not video_capture.isOpened():
+            st.error("Could not access the webcam. Please check your camera settings.")
+        else:
+            while not stop_detection:
+                ret, frame = video_capture.read()
+                if not ret:
+                    st.error("Failed to capture video. Please check your camera.")
+                    break
+
+                # Process the frame based on whether audio alerts are enabled
+                detected_objects, processed_frame = process_frame(frame, audio_activation)
+
+                # Convert BGR to RGB for Streamlit
+                frame_rgb = cv2.cvtColor(processed_frame, cv2.COLOR_BGR2RGB)
+                stframe.image(frame_rgb, channels="RGB", use_container_width=True)
+
+                # Generate audio alerts for detected objects
+                if audio_activation:
+                    current_time = datetime.now()
+                    for label, position in detected_objects.items():
+                        # Check if enough time has passed since the last alert for this object
+                        if (
+                            label not in last_alert_time
+                            or current_time - last_alert_time[label] > alert_cooldown
+                        ):
+                            play_audio_alert(label, position)
+                            last_alert_time[label] = current_time  # Update the last alert time
+
+                time.sleep(0.1)  # Small delay for smoother updates
+
+    except Exception as e:
+        st.error(f"An error occurred: {e}")
+    finally:
+        if 'video_capture' in locals() and video_capture.isOpened():
+            video_capture.release()
+            cv2.destroyAllWindows()
+            pygame.mixer.quit()
+
+elif stop_detection:
+    st.warning("Object detection stopped.")