import os

import cv2
import gradio as gr
import numpy as np
from imgutils.data import load_image


def variance_of_laplacian(np_image):
    """
    Inspired by https://pyimagesearch.com/2015/09/07/blur-detection-with-opencv/
    """
    return cv2.Laplacian(np_image, cv2.CV_64F).var()


def laplacian_score(image):
    v = np.array(load_image(image, force_background='white', mode='L'))
    return variance_of_laplacian(v)


def _fn(image, threshold: float):
    v = laplacian_score(image)
    text = 'Is Blur' if v < threshold else 'Not Blur'
    return v, text


if __name__ == '__main__':
    with gr.Blocks() as demo:
        with gr.Row():
            with gr.Column():
                gr_input_image = gr.Image(type='pil', label='Original Image')
                gr_threshold = gr.Slider(70, maximum=500, value=100, label='Threshold')
                gr_submit = gr.Button(value='Submit', variant='primary')

            with gr.Column():
                gr_score = gr.Text(label='Laplacian Score', value='')
                gr_pred = gr.Text(label='Prediction', value='')

            gr_submit.click(
                _fn,
                inputs=[gr_input_image, gr_threshold],
                outputs=[gr_score, gr_pred],
            )

    demo.queue(os.cpu_count()).launch()