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| import os | |
| from utils.util import check_path_is_img | |
| from utils.data_utils import Transforms, check_create_shuffled_order, check_equal_length | |
| from utils.augmentation import NumpyToTensor | |
| def add_numpy_paired_data(data, transforms, config, paired_data_order): | |
| A_paths = [] | |
| B_paths = [] | |
| if config['dataset']['paired_' + config['common']['phase'] + '_filelist'] != '': | |
| paired_data_file = open(config['dataset']['paired_' + config['common']['phase'] + '_filelist'], 'r') | |
| Lines = paired_data_file.readlines() | |
| paired_data_order = check_create_shuffled_order(Lines, paired_data_order) | |
| check_equal_length(Lines, paired_data_order, data) | |
| for i in paired_data_order: | |
| line = Lines[i] | |
| if not config['dataset']['use_absolute_datafile']: | |
| file1 = os.path.join(config['dataset']['dataroot'], line.split(" ")[0]).strip() | |
| file2 = os.path.join(config['dataset']['dataroot'], line.split(" ")[1]).strip() | |
| else: | |
| file1 = line.split(" ")[0].strip() | |
| file2 = line.split(" ")[1].strip() | |
| if os.path.exists(file1) and os.path.exists(file2): | |
| A_paths.append(file1) | |
| B_paths.append(file2) | |
| paired_data_file.close() | |
| elif config['dataset']['paired_' + config['common']['phase'] + 'A_folder'] != '' and \ | |
| config['dataset']['paired_' + config['common']['phase'] + 'B_folder'] != '': | |
| dir_A = config['dataset']['paired_' + config['common']['phase'] + 'A_folder'] | |
| dir_B = config['dataset']['paired_' + config['common']['phase'] + 'B_folder'] | |
| filenames = os.listdir(dir_A) | |
| paired_data_order = check_create_shuffled_order(filenames, paired_data_order) | |
| check_equal_length(filenames, paired_data_order, data) | |
| for i in paired_data_order: | |
| filename = filenames[i] | |
| if not check_path_is_img(filename): | |
| continue | |
| A_path = os.path.join(dir_A, filename) | |
| B_path = os.path.join(dir_B, filename) | |
| if os.path.exists(A_path) and os.path.exists(B_path): | |
| A_paths.append(A_path) | |
| B_paths.append(B_path) | |
| else: | |
| dir_A = os.path.join(config['dataset']['dataroot'], config['common']['phase'] + 'numpypairedA') | |
| dir_B = os.path.join(config['dataset']['dataroot'], config['common']['phase'] + 'numpypairedB') | |
| if os.path.exists(dir_A) and os.path.exists(dir_B): | |
| filenames = os.listdir(dir_A) | |
| paired_data_order = check_create_shuffled_order(filenames, paired_data_order) | |
| check_equal_length(filenames, paired_data_order, data) | |
| for i in paired_data_order: | |
| filename = filenames[i] | |
| if not check_path_is_img(filename): | |
| continue | |
| A_path = os.path.join(dir_A, filename) | |
| B_path = os.path.join(dir_B, filename) | |
| if os.path.exists(A_path) and os.path.exists(B_path): | |
| A_paths.append(A_path) | |
| B_paths.append(B_path) | |
| btoA = config['dataset']['direction'] == 'BtoA' | |
| # get the number of channels of input image | |
| input_nc = config['model']['output_nc'] if btoA else config['model']['input_nc'] | |
| output_nc = config['model']['input_nc'] if btoA else config['model']['output_nc'] | |
| transform = Transforms(config, input_grayscale_flag=(input_nc == 1), output_grayscale_flag=(output_nc == 1)) | |
| transform.transform_list.append(NumpyToTensor()) | |
| transform = transform.compose_transforms() | |
| data['paired_A_path'] = A_paths | |
| data['paired_B_path'] = B_paths | |
| transforms['paired'] = transform | |
| return paired_data_order | |
| def apply_numpy_paired_transforms(index, data, transforms, return_dict): | |
| if len(data['paired_A_path']) > 0: | |
| return_dict['paired_A'], return_dict['paired_B'] = transforms['paired'] \ | |
| (data['paired_A_path'][index], data['paired_B_path'][index]) | |
| return_dict['paired_A_path'] = data['paired_A_path'][index] | |
| return_dict['paired_B_path'] = data['paired_B_path'][index] | |