import gradio as gr
import cv2
import time
import os
from services.video_service import get_random_video_frame
from services.thermal_service import detect_thermal_anomalies
from services.overlay_service import overlay_boxes
from services.metrics_service import update_metrics

paused = False
frame_rate = 1.0  # seconds

def monitor_feed():
    global paused
    if paused:
        frame = get_random_video_frame()  # Still fetch to keep system active
    else:
        frame = get_random_video_frame()
        detected_boxes = detect_thermal_anomalies(frame)
        frame = overlay_boxes(frame, detected_boxes)
        metrics = update_metrics(detected_boxes)
        return frame[:, :, ::-1], metrics  # BGR → RGB

    return frame[:, :, ::-1], {"Detections": 0}

with gr.Blocks() as app:
    gr.Markdown("# 🌡️ Solar Surveillance Thermal Monitoring")

    with gr.Row():
        with gr.Column(scale=3):
            video_output = gr.Image(label="Live Video Feed", elem_id="video-feed")
        with gr.Column(scale=1):
            metrics_output = gr.Label(label="Detection Metrics")

    with gr.Row():
        pause_btn = gr.Button("⏸️ Pause")
        resume_btn = gr.Button("▶️ Resume")
        frame_slider = gr.Slider(0.5, 5.0, step=0.1, value=1.0, label="Frame Interval (seconds)")

    def toggle_pause():
        global paused
        paused = True

    def toggle_resume():
        global paused
        paused = False

    def set_frame_rate(val):
        global frame_rate
        frame_rate = val

    pause_btn.click(toggle_pause)
    resume_btn.click(toggle_resume)
    frame_slider.change(set_frame_rate, inputs=[frame_slider])

    def streaming_loop():
        while True:
            frame, metrics = monitor_feed()
            yield frame, metrics
            time.sleep(frame_rate)

    app.load(streaming_loop, outputs=[video_output, metrics_output])

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