practisebook's picture
Update app.py
13219fe verified
import os
import streamlit as st
from ultralytics import YOLO
import cv2
import random
import time
from gtts import gTTS
from playsound import playsound
from datetime import datetime, timedelta
# Load YOLOv8 model
yolo = YOLO("yolov8n.pt")
# Streamlit app layout
st.set_page_config(page_title="Assistive Vision App", layout="wide")
st.markdown(
"""
<style>
body {
background-color: #f7f9fc;
font-family: "Arial", sans-serif;
}
.stButton>button {
background-color: #1a73e8;
color: white;
justify-content: center;
align-items: center;
border-radius: 10px;
padding: 10px;
margin: 5px;
}
.stCheckbox {
margin-top: 20px;
}
</style>
""",
unsafe_allow_html=True,
)
# Display welcome image
welcome_image_path = "bismillah.png"
if os.path.exists(welcome_image_path):
st.image(welcome_image_path, use_container_width=True, caption="Bismillah hir Rehman Ar Raheem")
else:
st.warning("Welcome image not found! Please add 'bismillah.png' in the script directory.")
st.title("Object Detection & Assistive Vision App for Visually Impaired People")
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
col1, col2 = st.columns(2)
with col1:
start_detection = st.button("Start Detection")
with col2:
stop_detection = st.button("Stop Detection")
audio_activation = st.checkbox("Enable Audio Alerts", value=False)
# Categories for audio alerts
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}.",
]
alert_text = random.choice(phrases)
temp_audio_path = os.path.join(audio_temp_dir, f"alert_{datetime.now().strftime('%Y%m%d_%H%M%S_%f')}.mp3")
tts = gTTS(alert_text)
tts.save(temp_audio_path)
try:
playsound(temp_audio_path)
os.remove(temp_audio_path) # Clean up after playing
except Exception as e:
print(f"Audio playback error: {e}")
def process_frame(frame, audio_mode):
"""Process a single video frame for object detection."""
results = yolo(frame)
result = results[0]
detected_objects = {}
for box in result.boxes:
x1, y1, x2, y2 = map(int, box.xyxy[0])
label = result.names[int(box.cls[0])]
if audio_mode and label not in alert_categories:
continue
frame_center_x = frame.shape[1] // 2
obj_center_x = (x1 + x2) // 2
position = "left" if obj_center_x < frame_center_x else "right"
detected_objects[label] = position
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:
detected_objects, processed_frame = process_frame(frame, audio_activation)
frame_rgb = cv2.cvtColor(processed_frame, cv2.COLOR_BGR2RGB)
stframe.image(frame_rgb, channels="RGB", use_column_width=True)
if audio_activation:
current_time = datetime.now()
for label, position in detected_objects.items():
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
time.sleep(0.1)
except Exception as e:
st.error(f"An error occurred: {e}")
finally:
if 'cap' in locals() and cap.isOpened():
cap.release()
cv2.destroyAllWindows()
elif stop_detection:
st.warning("Object detection stopped.")