| 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 |
| |
| |
| 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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