cómo eliminar el fondo de una imagen mediante el procesamiento de imágenes en el ejemplo de código de Python

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Ejemplo: eliminar bg de la imagen usando pthon

import cv2
import numpy as np

#== Parameters =======================================================================
BLUR =21
CANNY_THRESH_1 =10
CANNY_THRESH_2 =200
MASK_DILATE_ITER =10
MASK_ERODE_ITER =10
MASK_COLOR =(0.0,0.0,1.0)# In BGR format#== Processing =======================================================================#-- Read image -----------------------------------------------------------------------
img = cv2.imread('C:/Temp/person.jpg')
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)#-- Edge detection -------------------------------------------------------------------
edges = cv2.Canny(gray, CANNY_THRESH_1, CANNY_THRESH_2)
edges = cv2.dilate(edges,None)
edges = cv2.erode(edges,None)#-- Find contours in edges, sort by area ---------------------------------------------
contour_info =[]
_, contours, _ = cv2.findContours(edges, cv2.RETR_LIST, cv2.CHAIN_APPROX_NONE)# Previously, for a previous version of cv2, this line was: #  contours, _ = cv2.findContours(edges, cv2.RETR_LIST, cv2.CHAIN_APPROX_NONE)# Thanks to notes from commenters, I've updated the code but left this notefor c in contours:
    contour_info.append((
        c,
        cv2.isContourConvex(c),
        cv2.contourArea(c),))
contour_info =sorted(contour_info, key=lambda c: c[2], reverse=True)
max_contour = contour_info[0]#-- Create empty mask, draw filled polygon on it corresponding to largest contour ----# Mask is black, polygon is white
mask = np.zeros(edges.shape)
cv2.fillConvexPoly(mask, max_contour[0],(255))#-- Smooth mask, then blur it --------------------------------------------------------
mask = cv2.dilate(mask,None, iterations=MASK_DILATE_ITER)
mask = cv2.erode(mask,None, iterations=MASK_ERODE_ITER)
mask = cv2.GaussianBlur(mask,(BLUR, BLUR),0)
mask_stack = np.dstack([mask]*3)# Create 3-channel alpha mask#-- Blend masked img into MASK_COLOR background --------------------------------------
mask_stack  = mask_stack.astype('float32')/255.0# Use float matrices, 
img         = img.astype('float32')/255.0#  for easy blending

masked =(mask_stack * img)+((1-mask_stack)* MASK_COLOR)# Blend
masked =(masked *255).astype('uint8')# Convert back to 8-bit 

cv2.imshow('img', masked)# Display
cv2.waitKey()#cv2.imwrite('C:/Temp/person-masked.jpg', masked)           # Save

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