Spaces:
Paused
Paused
File size: 2,028 Bytes
f9e4a6c |
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 41 42 43 44 45 46 |
"""This script is the data preparation script for Deep3DFaceRecon_pytorch
"""
import os
import numpy as np
import argparse
from util.detect_lm68 import detect_68p,load_lm_graph
from util.skin_mask import get_skin_mask
from util.generate_list import check_list, write_list
import warnings
warnings.filterwarnings("ignore")
parser = argparse.ArgumentParser()
parser.add_argument('--data_root', type=str, default='datasets', help='root directory for training data')
parser.add_argument('--img_folder', nargs="+", required=True, help='folders of training images')
parser.add_argument('--mode', type=str, default='train', help='train or val')
opt = parser.parse_args()
os.environ['CUDA_VISIBLE_DEVICES'] = '0'
def data_prepare(folder_list,mode):
lm_sess,input_op,output_op = load_lm_graph('./checkpoints/lm_model/68lm_detector.pb') # load a tensorflow version 68-landmark detector
for img_folder in folder_list:
detect_68p(img_folder,lm_sess,input_op,output_op) # detect landmarks for images
get_skin_mask(img_folder) # generate skin attention mask for images
# create files that record path to all training data
msks_list = []
for img_folder in folder_list:
path = os.path.join(img_folder, 'mask')
msks_list += ['/'.join([img_folder, 'mask', i]) for i in sorted(os.listdir(path)) if 'jpg' in i or
'png' in i or 'jpeg' in i or 'PNG' in i]
imgs_list = [i.replace('mask/', '') for i in msks_list]
lms_list = [i.replace('mask', 'landmarks') for i in msks_list]
lms_list = ['.'.join(i.split('.')[:-1]) + '.txt' for i in lms_list]
lms_list_final, imgs_list_final, msks_list_final = check_list(lms_list, imgs_list, msks_list) # check if the path is valid
write_list(lms_list_final, imgs_list_final, msks_list_final, mode=mode) # save files
if __name__ == '__main__':
print('Datasets:',opt.img_folder)
data_prepare([os.path.join(opt.data_root,folder) for folder in opt.img_folder],opt.mode)
|