image_process.py

import cv2
import numpy as np

def image_masking(filepath):

    BLUR = 21
    CANNY_THRESH_1 = 10
    CANNY_THRESH_2 = 200
    MASK_DILATE_ITER = 10
    MASK_ERODE_ITER = 10
    MASK_COLOR = (0.0, 0.0, 0.0) #BGR format

    img = cv2.imread(filepath)
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

    edges = cv2.Canny(gray, CANNY_THRESH_1, CANNY_THRESH_2)
    edges = cv2.dilate(edges, None)
    edges = cv2.erode(edges, None)

    contour_info = []
    _, contours, __ = cv2.findContours(edges, cv2.RETR_LIST, cv2.CHAIN_APPROX_NONE)

    for c in contours:
        contour_info.append((c, cv2.isContentConvex(c), cv2.contourArea(c), ))

    contour_info = sorted(contour_info, keys=lambda c: c[2], reverse=True)

    max_contour = contour_info[0]
    mask = np.zeroes(edges.shape)
    cv2.fillConvexPoly(mask, max_contour[0], (255))

    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)
    mask_stack = mask_stack.astype('float32') / 255.0
    img = img.astype('float32') / 255.0

    masked = (mask_stack * img) + ((1 - mask_stack) * MASK_COLOR)
    masked = (masked * 255).astype('uint8')

    fileName, fileExtension = filepath.split('.')
    fileName += '-masked.'
    filepath = fileName + fileExtension
    print(filepath)

    cv2.imwrite(filepath, masked)

if __name__ == '__main__':
    filepath = input('Enter Image File Name: \n')
    image_masking(filepath)