Last active
November 13, 2019 00:52
-
-
Save kidapu/395326bec6c5a1e9c2a91ab1ae747691 to your computer and use it in GitHub Desktop.
floodfill image
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
import numpy as np | |
import matplotlib.pyplot as plt | |
import cv2 | |
import glob | |
pathes = glob.glob('./datas/input/*.jpg') | |
for path in pathes: | |
print(path) | |
im_in = cv2.imread(path, cv2.IMREAD_GRAYSCALE) | |
im = cv2.imread(path) | |
th, im_th = cv2.threshold(im_in, 245, 255, cv2.THRESH_BINARY_INV) | |
im_floodfill = im_th.copy() | |
h, w = im_th.shape[:2] | |
mask = np.zeros((h+2, w+2), np.uint8) | |
cv2.floodFill(im_floodfill, mask, (0,0), 255) | |
im_floodfill_inv = cv2.bitwise_not(im_floodfill) | |
im_mask = im_th | im_floodfill_inv | |
b_channel, g_channel, r_channel = cv2.split(im) | |
img_BGRA = cv2.merge((b_channel, g_channel, r_channel, im_mask)) | |
new_image = Image.fromarray(cv2.cvtColor(img_BGRA,cv2.COLOR_BGRA2RGBA)) | |
bbox = new_image.split()[-1].getbbox() | |
new_image = new_image.crop(bbox) | |
outpath = path.replace("input","output") | |
new_image.save(outpath+".png") | |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment