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#!/usr/bin/env python3
import glob
import os
import PIL.Image as Image
import cv2
import numpy as np
import tqdm
import shutil
from saicinpainting.evaluation.utils import load_yaml
def generate_masks_for_img(infile, outmask_pattern, mask_size=200, step=0.5):
inimg = Image.open(infile)
width, height = inimg.size
step_abs = int(mask_size * step)
mask = np.zeros((height, width), dtype='uint8')
mask_i = 0
for start_vertical in range(0, height - step_abs, step_abs):
for start_horizontal in range(0, width - step_abs, step_abs):
mask[start_vertical:start_vertical + mask_size, start_horizontal:start_horizontal + mask_size] = 255
cv2.imwrite(outmask_pattern.format(mask_i), mask)
mask[start_vertical:start_vertical + mask_size, start_horizontal:start_horizontal + mask_size] = 0
mask_i += 1
def main(args):
if not args.indir.endswith('/'):
args.indir += '/'
if not args.outdir.endswith('/'):
args.outdir += '/'
config = load_yaml(args.config)
in_files = list(glob.glob(os.path.join(args.indir, '**', f'*{config.img_ext}'), recursive=True))
for infile in tqdm.tqdm(in_files):
outimg = args.outdir + infile[len(args.indir):]
outmask_pattern = outimg[:-len(config.img_ext)] + '_mask{:04d}.png'
os.makedirs(os.path.dirname(outimg), exist_ok=True)
shutil.copy2(infile, outimg)
generate_masks_for_img(infile, outmask_pattern, **config.gen_kwargs)
if __name__ == '__main__':
import argparse
aparser = argparse.ArgumentParser()
aparser.add_argument('config', type=str, help='Path to config for dataset generation')
aparser.add_argument('indir', type=str, help='Path to folder with images')
aparser.add_argument('outdir', type=str, help='Path to folder to store aligned images and masks to')
main(aparser.parse_args())
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