File size: 1,385 Bytes
5f3481c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 | from PIL import Image
from tqdm import tqdm
import numpy as np
import argparse
import glob
import pdb
import os
parser = argparse.ArgumentParser(description="resize image using bicubic upsampling")
parser.add_argument("--in_dir", default='/mnt/session_space/home/lingzzha/EgoHOS/data/train/lama_512_pad', type=str)
parser.add_argument("--out_dir", default='/mnt/session_space/home/lingzzha/EgoHOS/data/train/lama_512', type=str)
parser.add_argument("--ict_tf", default=False, type=bool)
parser.add_argument("--medfe_tf", default=False, type=bool)
parser.add_argument("--pad_info_dir", default='/mnt/session_space/home/lingzzha/EgoHOS/data/train/image_512_pad_info', type=str)
parser.add_argument("--size", default=512, type=int)
args = parser.parse_args()
os.makedirs(args.out_dir, exist_ok=True)
for img_file in tqdm(glob.glob(args.in_dir + '/*')):
fname = img_file.split('/')[-1].split('.')[0]
img = np.array(Image.open(img_file))
cut_info = np.load(os.path.join(args.pad_info_dir, fname+'.npy'))
if args.ict_tf or args.medfe_tf:
cut_info = cut_info/2
# pdb.set_trace()
if cut_info[0,0] == 0:
img_cut = img[args.size - int(cut_info[0,1]):,:,:]
else:
img_cut = img[:,:int(cut_info[0,1]),:]
img_cut = Image.fromarray(img_cut.astype('uint8'))
img_cut.save(os.path.join(args.out_dir, fname+'.jpg'))
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