#!/usr/bin/env python
# coding: utf-8

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import stackview

import pyclesperanto_prototype as cle
from skimage.data import cells3d
import matplotlib.pyplot as plt
from napari_segment_blobs_and_things_with_membranes import seeded_watershed
import numpy as np


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# load image
image = cells3d()
membrane2d = cle.asarray(image[30,0])
membrane2d = membrane2d * 255 / membrane2d.max()
membrane2d


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def segment_image(image, 
                  blur_sigma:float = 2,
                  threshold:float = 11,
                  smooth_outline_radius:int=5, 
                  image_brightness:float=1.5, 
                  show_image:bool=True, 
                  show_border:bool=True):
    
    labels = seeded_watershed(membrane2d, 
            cle.label(
                cle.gaussian_blur(
                    membrane2d, 
                    sigma_x=blur_sigma, 
                    sigma_y=blur_sigma) 
                < threshold
            )
         )
    
    processed = \
      cle.detect_label_edges(
        cle.extend_labeling_via_voronoi(
            cle.opening_labels(labels, radius=smooth_outline_radius)
        )
      ) * 255
    
    if show_image and show_border:
        return stackview.merge_rgb(image * image_brightness, processed, image * image_brightness)
    elif show_image:
        return image * image_brightness
    elif show_border:
        return processed
    else:
        return np.zeros(processed.shape)
    
stackview.interact(segment_image, membrane2d, continuous_update=True)


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