import cv2
import gradio as gr
import os
import datetime
import pandas as pd
from PIL import Image
from pathlib import Path
import torch

# 🔧 Setup
os.makedirs("logs", exist_ok=True)

# 🧠 Load YOLOv5 Model
model = torch.hub.load('ultralytics/yolov5', 'yolov5s', trust_repo=True)

# 📍 Fake GPS Location
def get_fake_gps_location():
    return "28.6139° N, 77.2090° E"  # Delhi (demo)

# 🔊 Simulated Voice Alert (just returns text)
def voice_alert(text):
    print(f"[VOICE ALERT] {text}")
    return f"🔊 Voice: {text}"

# 🎯 Detection Function
def detect_luggage(image_path, status_label):
    image = Image.open(image_path)
    results = model(image)
    annotated_image = results.render()[0]
    annotated_pil = Image.fromarray(annotated_image)

    # 🗺️ Fake GPS
    gps = get_fake_gps_location()

    # 🔊 Voice Message
    alert_text = f"Luggage {status_label} at {gps}"
    voice = voice_alert(alert_text)

    # 📝 Logging
    time_now = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
    log_path = "luggage_log.csv"
    entry = {"timestamp": time_now, "status": status_label, "gps": gps}
    df = pd.DataFrame([entry])
    if not os.path.exists(log_path):
        df.to_csv(log_path, index=False)
    else:
        df.to_csv(log_path, mode='a', header=False, index=False)

    # 💾 Save Image
    img_name = f"{status_label}_{datetime.datetime.now().strftime('%Y%m%d_%H%M%S')}.jpg"
    annotated_pil.save(f"logs/{img_name}")

    return annotated_pil, f"{voice} | 📍 Location: {gps}"

# 🤖 Demo Function
def run_demo(status_label):
    test_image_path = "assets/test_luggage.jpg"
    return detect_luggage(test_image_path, status_label)

# 🎨 Gradio UI
demo = gr.Interface(
    fn=run_demo,
    inputs=gr.Radio(["Loaded", "Dispatched"], label="Select Luggage Status", value="Loaded"),
    outputs=[
        gr.Image(label="Detected Luggage"),
        gr.Text(label="Detection Report")
    ],
    title="🎒 Luggage Tracking with Voice + GPS",
    description="YOLO-based luggage detection with simulated GPS & voice alerts. Ready for Hugging Face!"
)

if __name__ == "__main__":
    demo.launch()