import cv2
import numpy as np
import torch
import streamlit as st
import streamlit.components.v1 as components
from ultralytics import YOLO
from camera_input_live import camera_input_live

# 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 Alarm 🔥")
st.subheader("Hold the camera towards potential fire sources to detect in real-time.")

# Load alarm sound (must be a direct MP3 URL)
alarm_url = "https://docs.google.com/uc?export=download&id=16IzsnQDmWkfYSeb_AjOTx79NEgkOpz88"


# JavaScript to auto-play alarm when fire is detected
js_code = f"""
<script>
    var alarm = new Audio("{alarm_url}");
    alarm.loop = true;

    function playAlarm() {{
        alarm.play().catch(error => {{
            console.log("Autoplay failed. User interaction required.");
        }});
    }}

    function stopAlarm() {{
        alarm.pause();
        alarm.currentTime = 0;
    }}
</script>
"""

# Inject JavaScript
components.html(js_code, height=0)

# 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)

    fire_present = False  # Flag for fire detection
    
    # Check if fire is detected
    for result in results:
        if len(result.boxes) > 0:
            fire_present = True
            break  # No need to check further

    # Display logs & trigger alarm
    if fire_present:
        st.error("🔥 Fire Detected! 🔥")
        components.html("<script>playAlarm();</script>", height=0)
    else:
        st.success("✅ No Fire Detected")
        components.html("<script>stopAlarm();</script>", height=0)