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


def blur_score_from_pil(pil_img: Image.Image) -> float:
    # Convert PIL -> OpenCV grayscale
    img = np.array(pil_img.convert("RGB"))
    gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
    return float(cv2.Laplacian(gray, cv2.CV_64F).var())


def check_blur(image: Image.Image, blur_threshold: float = 100.0):
    if image is None:
        return None, "No image provided."

    score = blur_score_from_pil(image)

    if score < blur_threshold:
        return score, "🚫 Blurry image detected. Please re-upload a clearer image."
    else:
        return score, "✅ Image looks clear. Proceeding to next step."


demo = gr.Interface(
    fn=check_blur,
    inputs=[
        gr.Image(type="pil", label="Upload Image"),
        gr.Slider(0, 500, value=100, step=1, label="Blur Threshold (Laplacian Variance)"),
    ],
    outputs=[
        gr.Number(label="Blur Score (Laplacian Variance)"),
        gr.Textbox(label="Result"),
    ],
    title="Image Blur Checker",
    description="Checks image blur using variance of the Laplacian. Lower score = blurrier image.",
)

demo.launch(server_name="0.0.0.0", server_port=7860, show_error=True)