import gradio as gr
from ultralytics import YOLO
import cv2
from PIL import Image
import numpy as np

# Load YOLOv8 model
MODEL_PATH = "Best_Model1.pt"
model = YOLO(MODEL_PATH)

def detect_flash(image: Image.Image):
    # Convert PIL image to OpenCV format
    image_cv = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)

    # Run detection
    results = model(image_cv)
    detections = results[0].boxes.data.tolist()
    num_detections = len(detections)

    message = ""
    if num_detections > 0:
        message += f"Flash(es) Detected: {num_detections}\n"
        for i, det in enumerate(detections):
            x1, y1, x2, y2, conf, cls = det
            message += f"  Flash {i+1}: Confidence={conf:.2f}, Position=[{int(x1)},{int(y1)},{int(x2)},{int(y2)}]\n"
    else:
        message = "No Flash Detected."

    # Plot result
    res_plotted = results[0].plot()
    res_rgb = cv2.cvtColor(res_plotted, cv2.COLOR_BGR2RGB)
    output_image = Image.fromarray(res_rgb)

    return output_image, message

def clear_all():
    return None, None, ""

# Gradio interface
with gr.Blocks() as demo:
    gr.Markdown("Flash Detection with YOLOv8")
    gr.Markdown("Upload an image to detect flash.")

    with gr.Row():
        img_input = gr.Image(type="pil", label="Upload Image")
        output_img = gr.Image(type="pil", label="Detected Image")

    output_text = gr.Textbox(label="Detection Info", lines=6)

    with gr.Row():
        detect_btn = gr.Button("Detect Flash")
        clear_btn = gr.Button("Clear")

    detect_btn.click(fn=detect_flash, inputs=img_input, outputs=[output_img, output_text])
    clear_btn.click(fn=clear_all, inputs=[], outputs=[img_input, output_img, output_text])

demo.launch()