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#!/usr/bin/env python3
import os
import argparse
import skimage.io
import skimage.external.tifffile
from multiprocess import Pool
from functools import partial
from tqdm import tqdm
import cv2
try:
__import__("frame_field_learning.local_utils")
except ImportError:
print("ERROR: The frame_field_learning package is not installed! "
"Execute script setup.sh to install local dependencies such as frame_field_learning in develop mode.")
exit()
from lydorn_utils import print_utils
def get_args():
argparser = argparse.ArgumentParser(description=__doc__)
argparser.add_argument(
'--filepath',
required=True,
type=str,
nargs='*',
help='Path(s) to tiff seg RGB images to convert to single channel segmentation map (only keep the first channel).')
argparser.add_argument(
'--out_dirpath',
type=str,
help='Path to the output directory for the converted images.')
args = argparser.parse_args()
return args
def convert_one(filepath, out_dirpath):
image = skimage.io.imread(filepath)
gray_image = image[:, :, 0]
basename = os.path.basename(filepath)
name = basename.split(".")[0]
out_filepath = os.path.join(out_dirpath, name + ".png")
os.makedirs(os.path.dirname(out_filepath), exist_ok=True)
cv2.imwrite(out_filepath, gray_image, [cv2.IMWRITE_PNG_COMPRESSION, 9])
def main():
args = get_args()
print_utils.print_info(f"INFO: converting {len(args.filepath)} seg images.")
pool = Pool()
list(tqdm(pool.imap(partial(convert_one, out_dirpath=args.out_dirpath), args.filepath), desc="RGB to Gray", total=len(args.filepath)))
if __name__ == '__main__':
main()
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