app.py

'''import cv2
import numpy as np
import torch
import streamlit as st
from ultralytics import YOLO
from camera_input_live import camera_input_live

# Load YOLO fire detection model
model_path = "last.pt"
if not torch.cuda.is_available():
    device = "cpu"
else:
    device = "cuda"

model = YOLO(model_path)
model.to(device)

# Streamlit app title
st.title("Live Fire Detection with Camera")
st.subheader("Hold the camera towards potential fire sources to detect in real-time.")

# Capture live camera input
image = camera_input_live()

if image is not None:
    # Convert the image to OpenCV format
    bytes_data = image.getvalue()
    cv2_img = cv2.imdecode(np.frombuffer(bytes_data, np.uint8), cv2.IMREAD_COLOR)

    # Perform fire detection
    results = model(cv2_img)

    # Draw bounding boxes for detected fires
    for result in results:
        boxes = result.boxes
        for box in boxes:
            b = box.xyxy[0].cpu().numpy().astype(int)
            c = int(box.cls[0])
            label = f'Fire {box.conf[0]:.2f}'
            cv2.rectangle(cv2_img, (b[0], b[1]), (b[2], b[3]), (0, 0, 255), 3)
            cv2.putText(cv2_img, label, (b[0], b[1] - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.9, (0, 0, 255), 2)

    # Display the annotated image
    st.image(cv2_img, channels="BGR", caption="Detected Fire", use_container_width=True)
'''
import cv2
import numpy as np
import torch
import streamlit as st
import pygame
from ultralytics import YOLO
from camera_input_live import camera_input_live

# Initialize Pygame mixer for audio alarm
pygame.mixer.init()
alarm_sound = "alarm.mp3"  # Ensure you have an alarm.mp3 file in your directory

# Load YOLO fire detection model
model_path = "last.pt"
device = "cuda" if torch.cuda.is_available() else "cpu"

model = YOLO(model_path)
model.to(device)

# Streamlit app title
st.title("Live Fire Detection with Camera")
st.subheader("Hold the camera towards potential fire sources to detect in real-time.")

# Capture live camera input
image = camera_input_live()
fire_detected = False  # Track fire detection state

if image is not None:
    # Convert the image to OpenCV format
    bytes_data = image.getvalue()
    cv2_img = cv2.imdecode(np.frombuffer(bytes_data, np.uint8), cv2.IMREAD_COLOR)

    # Perform fire detection
    results = model(cv2_img)

    fire_present = False  # Temporary flag for fire detection in this frame
    
    # Draw bounding boxes for detected fires
    for result in results:
        boxes = result.boxes
        for box in boxes:
            b = box.xyxy[0].cpu().numpy().astype(int)
            label = f'Fire {box.conf[0]:.2f}'
            cv2.rectangle(cv2_img, (b[0], b[1]), (b[2], b[3]), (0, 0, 255), 3)
            cv2.putText(cv2_img, label, (b[0], b[1] - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.9, (0, 0, 255), 2)
            fire_present = True  # Fire detected
    
    # Display the annotated image
    st.image(cv2_img, channels="BGR", caption="Detected Fire", use_container_width=True)
    
    # Display logs
    if fire_present:
        st.error("🔥 Fire Detected! 🔥")
        if not fire_detected:  # Play alarm if not already playing
            pygame.mixer.music.load(alarm_sound)
            pygame.mixer.music.play(-1)  # Loop indefinitely
        fire_detected = True  # Update fire status
    else:
        st.success("✅ No Fire Detected")
        if fire_detected:
            pygame.mixer.music.stop()  # Stop alarm
        fire_detected = False