import cv2
import numpy as np

def particle_canny(image, sigma=230):

    #v = np.median(image[image > 0])
    lower = sigma
    upper = 255
    edged = cv2.Canny(image, lower, upper)

    return edged

def auto_canny(image, sigma=0.66):
    # compute the median of the single channel pixel intensities
    v = np.median(image)

    # apply automatic Canny edge detection using the computed median
    lower = int(max(0, (1.0 - sigma) * v))
    upper = int(min(255, (1.0 + sigma) * v))
    edged = cv2.Canny(image, lower, upper)

    # return the edged image
    return edged

def img_fill(im_in):  # n = binary image threshold

    # Copy the thresholded image.
    im_floodfill = im_in.copy()

    # Mask used to flood filling.
    # Notice the size needs to be 2 pixels than the image.
    h, w = im_in.shape[:2]
    mask = np.zeros((h + 2, w + 2), np.uint8)

    # Floodfill from point (0, 0)
    cv2.floodFill(im_floodfill, mask, (0, 0), 255)

    # Invert floodfilled image
    im_floodfill_inv = cv2.bitwise_not(im_floodfill)

    # Combine the two images to get the foreground.
    fill_image = im_in | im_floodfill_inv

    return fill_image