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d239e33 | 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 | from PIL import Image
import numpy as np
from skimage.io import imsave
import glob
import pdb
import os
import torchvision
import torch
from torchvision.models.feature_extraction import create_feature_extractor
from torchvision import transforms
from tqdm import tqdm
from shutil import copyfile
feat_extractor = torchvision.models.vgg16(pretrained=True).features.cuda()
# pdb.set_trace()
tsfm = transforms.Compose([
transforms.ToTensor(),
transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
])
lama_dir = '/mnt/session_space/home/lingzzha/EgoHOS/data/train/lama_512'
lama_feat_dir = '/mnt/session_space/home/lingzzha/EgoHOS/data/train/lama_512_feature'
os.makedirs(lama_feat_dir, exist_ok = True)
for file in tqdm(glob.glob(lama_dir + '/*')):
fname = os.path.basename(file).split('.')[0]
clean_back = tsfm(Image.open(file).convert('RGB').resize((480, 360))).cuda()
clean_back_feat = feat_extractor(clean_back.unsqueeze(0)).reshape(-1)
clean_back_feat_np = clean_back_feat.cpu().data.numpy()
np.save(os.path.join(lama_feat_dir, fname + '.npy'), clean_back_feat_np)
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