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step7_final_mapper_data_preparation.py
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step7_final_mapper_data_preparation.py
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import os.path
import argparse
import numpy as np
import glob
import random
def parse_args():
"""Parses arguments."""
parser = argparse.ArgumentParser(
description='Edit image synthesis with given semantic boundary.')
parser.add_argument('--test_data_dir', type=str, default='./data/test_data/final',
help='Directory to load validation data.')
parser.add_argument('--dataset_name', type=str, required=True,
help='D0 dataset name. (required)')
parser.add_argument('--noise_dataset_name', type=str, required=True,
help='Dnoise dataset name')
parser.add_argument('--mapper_name', type=str, default='final_mapper',
help='mapper name')
return parser.parse_args()
def run():
args = parse_args()
dataset_path = './training_runs/dataset'
male_training_path = './training_runs/male_training'
female_training_path = './training_runs/female_training'
output_dir = f'./training_runs/{args.mapper_name}/data'
print(f'============= Male mapper training list will be saved to {output_dir} =============')
wp_data_dir = os.path.join(dataset_path, args.dataset_name)
wp_male_res_dir = os.path.join(male_training_path, args.dataset_name)
wp_female_res_dir = os.path.join(female_training_path, args.dataset_name)
wp_add_noise_data_dir = os.path.join(dataset_path, args.noise_dataset_name)
wp_add_noise_male_res_dir = os.path.join(male_training_path, args.noise_dataset_name)
wp_add_noise_female_res_dir = os.path.join(female_training_path, args.noise_dataset_name)
os.makedirs(output_dir)
train_data = open(os.path.join(output_dir, 'train.txt'), 'w')
val_data = open(os.path.join(output_dir, 'val.txt'), 'w')
test_data = open(os.path.join(output_dir, 'test.txt'), 'w')
latent_data = []
data_list = []
count = 0
# wp
male_mask_dir = os.path.join(wp_male_res_dir, 'mask')
male_res_code_dir = os.path.join(wp_male_res_dir, 'res_wp_codes')
female_mask_dir = os.path.join(wp_female_res_dir, 'mask')
female_res_code_dir = os.path.join(wp_female_res_dir, 'res_wp_codes')
wp = np.load(os.path.join(wp_data_dir, 'wp.npy'))
for code_path in glob.glob(os.path.join(male_res_code_dir, '*.npy')):
name = os.path.basename(code_path)[:6]
mask_path = os.path.join(male_mask_dir, f'{name}.png')
origin_code = np.reshape(wp[int(name), :, :], (1, 18, 512))
latent_data.append(origin_code)
line = str(count) + ' ' + code_path + ' ' + mask_path + '\n'
data_list.append(line)
count += 1
for code_path in glob.glob(os.path.join(female_res_code_dir, '*.npy')):
name = os.path.basename(code_path)[:6]
mask_path = os.path.join(female_mask_dir, f'{name}.png')
origin_code = np.reshape(wp[int(name), :, :], (1, 18, 512))
latent_data.append(origin_code)
line = str(count) + ' ' + code_path + ' ' + mask_path + '\n'
data_list.append(line)
count += 1
male_mask_dir = os.path.join(wp_add_noise_male_res_dir, 'mask')
male_res_code_dir = os.path.join(wp_add_noise_male_res_dir, 'res_wp_codes')
female_mask_dir = os.path.join(wp_add_noise_female_res_dir, 'mask')
female_res_code_dir = os.path.join(wp_add_noise_female_res_dir, 'res_wp_codes')
wp = np.load(os.path.join(wp_add_noise_data_dir, 'wp.npy'))
for code_path in glob.glob(os.path.join(male_res_code_dir, '*.npy')):
name = os.path.basename(code_path)[:6]
mask_path = os.path.join(male_mask_dir, f'{name}.png')
origin_code = np.reshape(wp[int(name), :, :], (1, 18, 512))
latent_data.append(origin_code)
line = str(count) + ' ' + code_path + ' ' + mask_path + '\n'
data_list.append(line)
count += 1
for code_path in glob.glob(os.path.join(female_res_code_dir, '*.npy')):
name = os.path.basename(code_path)[:6]
mask_path = os.path.join(female_mask_dir, f'{name}.png')
origin_code = np.reshape(wp[int(name), :, :], (1, 18, 512))
latent_data.append(origin_code)
line = str(count) + ' ' + code_path + ' ' + mask_path + '\n'
data_list.append(line)
count += 1
latent_data = np.concatenate(latent_data, axis=0)
np.save(os.path.join(output_dir, 'original_wp.npy'), latent_data)
random.shuffle(data_list)
for line in data_list:
if random.randint(0, 500) % 299 == 0:
val_data.write(line)
else:
train_data.write(line)
# test data test_data_dir
test_code_dir = os.path.join(args.test_data_dir, 'code')
test_mask_dir = os.path.join(args.test_data_dir, 'mask')
test_img_dir = os.path.join(args.test_data_dir, 'origin')
for codepath in glob.glob(os.path.join(test_code_dir, '*.npy')):
name = os.path.basename(codepath)[:-4]
origin_image_path = os.path.join(test_img_dir, f'{name}.png')
mask = os.path.join(test_mask_dir, f'{name}.png')
if (not os.path.exists(mask)) or (not os.path.exists(origin_image_path)):
continue
line = origin_image_path + ' ' + codepath + ' ' + mask + '\n'
test_data.write(line)
if __name__ == '__main__':
run()