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| import os | |
| import glob | |
| import json | |
| from pathlib import Path | |
| from collections import OrderedDict | |
| pretrained_models_dict = {'E2VID': "0000_000012", 'FireNet': "0000_000020", | |
| 'E2VID+': "0000_000000", 'FireNet+': "0000_000002", | |
| 'ET-Net': "0000_000030", 'SSL_E2VID': "0000_000040", | |
| 'SPADE_E2VID': "0000_000050"} | |
| full_ref_metrics = ['mse', 'ssim', 'lpips'] | |
| no_ref_metrics = ['brisque', 'niqe', 'maniqa'] | |
| def read_json(fname): | |
| fname = Path(fname) | |
| with fname.open('rt') as handle: | |
| return json.load(handle, object_hook=OrderedDict) | |
| def get_filenames(base_path, filename_pattern): | |
| file_names = [] | |
| glob_pattern = os.path.join(base_path, filename_pattern) | |
| file_paths = glob.glob(glob_pattern) | |
| for file_path in file_paths: | |
| file_name = Path(file_path).stem | |
| file_names.append(file_name) | |
| return file_names | |
| def get_dataset_config_names(data_configs_path): | |
| data_configs_filename_pattern = "*.json" | |
| return get_filenames(data_configs_path, data_configs_filename_pattern) | |
| def get_sequence_names(data_configs_path, dataset_name): | |
| sequences = [] | |
| dataset_file_name = os.path.join(data_configs_path, dataset_name + ".json") | |
| dataset_config = read_json(dataset_file_name) | |
| for sequence in dataset_config['sequences']: | |
| sequences.append(sequence) | |
| return sequences | |