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December 4, 2023 18:54
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Convert all labelme generated json into mask image in every subdirectory
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# Author : frakw | |
# Date : 2023-12-04 | |
# Description : Convert all labelme generated json into mask image in every subdirectory | |
# Usage : python labelme_gen_mask_img.py | |
import json | |
import numpy as np | |
import cv2 | |
import os | |
import fnmatch | |
from pathlib import Path | |
root_dir = './' | |
def gen_mask_img(json_filename): | |
# read json file | |
with open(json_filename, "r") as f: | |
data = f.read() | |
# convert str to json objs | |
data = json.loads(data) | |
# get the points | |
points = data["shapes"][0]["points"] | |
points = np.array(points, dtype=np.int32) # tips: points location must be int32 | |
target_dirname = os.path.dirname(json_filename) | |
original_img_filename = target_dirname + '/' + data["imagePath"] | |
# read image to get shape | |
image = cv2.imread(original_img_filename) | |
# create a blank image | |
mask = np.zeros_like(image, dtype=np.uint8) | |
# fill the contour with 255 | |
cv2.fillPoly(mask, [points], (255, 255, 255)) | |
json_filename_noex = Path(json_filename).stem | |
mask_img_filename = target_dirname + '/' + json_filename_noex + "_mask.png" | |
# save the mask | |
cv2.imwrite(mask_img_filename, mask) | |
def main(): | |
for dirname, dirnames, filenames in os.walk(root_dir): | |
for filename in filenames: | |
if fnmatch.fnmatch(filename,"*.json") == True: | |
relative_filename = os.path.join(dirname,filename) | |
relative_filename = relative_filename.replace("\\","/") | |
print("generate mask img for " + relative_filename) | |
gen_mask_img(relative_filename) | |
else: | |
pass | |
if __name__ == '__main__': | |
main() |
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numpy==1.26.2 | |
opencv-python==4.8.1.78 |
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