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import os
import argparse
import glob
import operator
from multiprocessing import Pool, cpu_count
from shutil import rmtree
from PIL import Image
parser = argparse.ArgumentParser()
parser.add_argument('--overlap', default=2, type=int)
parser.add_argument('--scale', default=4, type=int)
parser.add_argument('dir', metavar='dir', help='Directory to process')
args = parser.parse_args()
def split_crop_dir(fn):
crop, x, y, w, h = os.path.basename(fn).split("_")
return int(x), int(y), int(w), int(h)
def merge_files(file, crop_dir_list, ww, hh, overlap, merge_dir):
fn = os.path.basename(file)
print(fn)
canvas = Image.new('RGB', (ww, hh,))
for crop_dir_tuple in crop_dir_list:
x, y, w, h = crop_dir_tuple
crop_dir = "crop_{}_{}_{}_{}".format(x, y, w, h)
image = Image.open("{}/{}/{}".format(args.dir, crop_dir, fn))
crop = image.crop((overlap, overlap, image.size[0] - overlap * 2, image.size[1] - overlap * 2))
canvas.paste(crop, (x * args.scale, y * args.scale,))
canvas.save("{}/{}".format(merge_dir, fn))
def merge_dir():
overlap = args.overlap * args.scale
crop_dirs = glob.glob("{}/crop_*".format(args.dir))
merge_dir = "{}/merged".format(args.dir)
os.makedirs(merge_dir, exist_ok=True)
ww = 0
hh = 0
masks = {}
crop_dir_list = []
widths = []
heights = []
for crop_dir in crop_dirs:
x, y, w, h = split_crop_dir(crop_dir)
if x == 0:
hh = max(y + h - args.overlap * 2, hh)
if y == 0:
ww = max(x + w - args.overlap * 2, ww)
crop_dir_list.append((x, y, w, h,))
crop_dir_list = sorted(crop_dir_list, key=operator.itemgetter(0, 1))
ww *= args.scale
hh *= args.scale
print("{}x{}".format(ww, hh))
files = sorted(glob.glob("{}/*.png".format(crop_dirs[0])))
dataset = []
for file in files:
dataset.append((file, crop_dir_list, ww, hh, overlap, merge_dir,))
chunksize = 3
with Pool(processes=cpu_count()) as pool:
pool.starmap(merge_files, dataset, chunksize)
if __name__ == "__main__":
merge_dir()
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