app.py

import time
import os
import yaml
import logging
import numpy as np
import gradio as gr
import soundfile as sf
from dotenv import load_dotenv
from threading import Lock
from queue import Queue
import threading

from src.detection.factory import get_detector

# ───────────────────────────── logging
logging.basicConfig(
    level=logging.INFO,
    format="%(asctime)s │ %(message)s",
    datefmt="%H:%M:%S",
)

# ───────────────────────────── config / detector
load_dotenv()
with open("config.yaml") as f:
    CFG = yaml.safe_load(f)

detector = get_detector(CFG)

# ───────────────────────────── alert sound manager
class AlertManager:
    def __init__(self, wav_path, cooldown_seconds=5):
        self.cooldown_seconds = cooldown_seconds
        self.last_alert_time = 0
        self.lock = Lock()
        self.alert_queue = Queue(maxsize=1)
        
        # Load alert sound
        try:
            self.sample_rate, self.audio_data = sf.read(wav_path, dtype="float32")
            
            # Ensure stereo format for Gradio
            if self.audio_data.ndim == 1:
                self.audio_data = np.column_stack([self.audio_data, self.audio_data])
            
            # Normalize to [-1, 1] range
            max_val = np.abs(self.audio_data).max()
            if max_val > 0:
                self.audio_data = self.audio_data / max_val
            
            logging.info(f"Loaded alert sound: {wav_path} "
                        f"({len(self.audio_data)/self.sample_rate:.2f}s, "
                        f"shape: {self.audio_data.shape})")
            self.is_loaded = True
        except Exception as e:
            logging.error(f"Failed to load alert sound: {e}")
            self.is_loaded = False
            self.sample_rate = 44100
            self.audio_data = None
    
    def should_alert(self, drowsiness_level, lighting):
        """Check if we should trigger an alert"""
        if not self.is_loaded:
            return False
        
        with self.lock:
            current_time = time.monotonic()
            if (drowsiness_level != "Awake" 
                and lighting != "Low" 
                and (current_time - self.last_alert_time) > self.cooldown_seconds):
                self.last_alert_time = current_time
                return True
        return False
    
    def get_alert_audio(self):
        """Get the alert audio data"""
        if self.is_loaded:
            return (int(self.sample_rate), self.audio_data.copy())
        return None

# Initialize alert manager
alert_manager = AlertManager(
    wav_path=CFG["alerting"].get("alert_sound_path"),
    cooldown_seconds=CFG["alerting"].get("alert_cooldown_seconds", 5)
)

# ───────────────────────────── frame processing
def process_live_frame(frame):
    """Process frame for drowsiness detection"""
    if frame is None:
        return (
            np.zeros((480, 640, 3), dtype=np.uint8),
            "Status: Inactive",
            None
        )
    
    t0 = time.perf_counter()
    
    try:
        # Process frame through detector
        processed, indic = detector.process_frame(frame)
    except Exception as e:
        logging.error(f"Error processing frame: {e}")
        processed = np.zeros_like(frame)
        indic = {
            "drowsiness_level": "Error",
            "lighting": "Unknown",
            "details": {"Score": 0.0}
        }
    
    # Extract detection results
    level = indic.get("drowsiness_level", "Awake")
    lighting = indic.get("lighting", "Good")
    score = indic.get("details", {}).get("Score", 0.0)
    
    # Log performance
    dt_ms = (time.perf_counter() - t0) * 1000.0
    logging.info(f"{dt_ms:6.1f} ms │ {lighting:<4} │ {level:<14} │ score={score:.2f}")
    
    # Create status text
    status_txt = f"Lighting: {lighting}\n"
    if lighting == "Low":
        status_txt += "Detection paused – low light."
    else:
        status_txt += f"Status: {level}\nScore: {score:.2f}"
    
    # Check if we should trigger alert
    audio_out = None
    if alert_manager.should_alert(level, lighting):
        audio_out = alert_manager.get_alert_audio()
        if audio_out:
            logging.info("🔊 Alert triggered!")
    
    return processed, status_txt, audio_out

# ───────────────────────────── UI with error handling
def create_ui():
    with gr.Blocks(title="Drive Paddy – Drowsiness Detection") as app:
        gr.Markdown("# 🚗 **Drive Paddy** – Real-time Drowsiness Detection")
        gr.Markdown("Webcam-based drowsiness detection with audio alerts.")
        
        with gr.Row():
            with gr.Column(scale=2):
                cam = gr.Image(
                    sources=["webcam"],
                    streaming=True,
                    label="Live Camera Feed"
                )
            
            with gr.Column(scale=1):
                out_img = gr.Image(label="Processed Feed")
                out_text = gr.Textbox(
                    label="Live Status",
                    lines=4,
                    interactive=False
                )
                out_audio = gr.Audio(
                    label="Alert Sound",
                    autoplay=True,
                    type="numpy",
                    visible=True,
                )
        
        # Add system info
        with gr.Row():
            gr.Markdown(f"""
            **System Info:**
            - Alert cooldown: {CFG['alerting'].get('alert_cooldown_seconds', 5)}s
            - Alert sound loaded: {'✓' if alert_manager.is_loaded else '✗'}
            """)
        
        # Connect the streaming
        cam.stream(
            fn=process_live_frame,
            inputs=[cam],
            outputs=[out_img, out_text, out_audio]
        )
    
    return app

# ───────────────────────────── main
if __name__ == "__main__":
    logging.info("Initializing Drive Paddy...")
    
    # Create and launch app
    app = create_ui()
    
    logging.info("Launching Gradio app...")
    app.launch(
        debug=True,
        share=False,  # Set to True if you want a public link
        server_name="0.0.0.0",  # Allow external connections
        server_port=7860
    )