| """ |
| Copyright (c) 2022 Samsung Electronics Co., Ltd. |
| |
| Author: |
| Abhijith Punnappurath (abhijith.p@samsung.com) |
| |
| Licensed under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License, (the "License"); |
| you may not use this file except in compliance with the License. |
| You may obtain a copy of the License at https://creativecommons.org/licenses/by-nc/4.0 |
| Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an |
| "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| See the License for the specific language governing permissions and limitations under the License. |
| For conditions of distribution and use, see the accompanying LICENSE.md file. |
| |
| """ |
|
|
| from shutil import copyfile, rmtree |
| import os |
| from glob import glob |
| import argparse |
| import cv2 |
| import pickle |
|
|
| from pipeline.pipeline_utils import get_metadata, get_visible_raw_image |
| from utils.gen_utils import check_dir |
|
|
|
|
| def parse_args(): |
| parser = argparse.ArgumentParser() |
| parser.add_argument('--base_path', default='dataset/night_real', type=str, |
| help='base address') |
| parser.add_argument('--which_fold', default=0, type=int, help='which fold for testing [0,1,2]') |
| parser.add_argument('--kfold_indices', default='utils/k_fold_indices_saved.p', type=str, help='load saved k-fold indices') |
| parser.add_argument('--with_noise', default=0, type=int, help='for noisy case, mix iso 1600 and 3200 equally') |
| args = parser.parse_args() |
|
|
| print(args) |
|
|
| return args |
|
|
|
|
| def split_func(args, folder_path, k_fold_indices): |
|
|
| train_index = k_fold_indices['train_index_all'][args.which_fold] |
| val_index = k_fold_indices['val_index_all'][args.which_fold] |
| test_index = k_fold_indices['test_index_all'][args.which_fold] |
|
|
| if folder_path == 'iso_1600': |
| index = {'train': train_index[0::2], 'val': val_index[0::2]} |
| elif folder_path == 'iso_3200': |
| index = {'train': train_index[1::2], 'val': val_index[1::2]} |
| else: |
| index = {'train': train_index, 'val': val_index} |
|
|
| input_dir = args.base_path |
|
|
| print('train') |
| print(index['train']) |
| print('...') |
|
|
| print('val') |
| print(index['val']) |
| print('...') |
|
|
| print('test') |
| print(test_index) |
| print('...') |
| print(args.which_fold, len(index['train']), len(index['val']), len(test_index)) |
|
|
| |
| check_dir('data') |
| for fol in ['train', 'val', 'test']: check_dir(os.path.join('data', fol)) |
| for fol in ['train', 'val']: |
| for subfol in ['clean_raw', 'noisy_raw', 'clean', 'metadata_raw']: check_dir(os.path.join('data', fol, subfol)) |
| for fol in ['test']: |
| for subfol in ['clean_raw', 'clean', 'dng']: check_dir(os.path.join('data', fol, subfol)) |
| check_dir(os.path.join('data', 'test', 'dng', folder_path)) |
|
|
| allfiles = [os.path.basename(x) for x in sorted(glob(os.path.join(input_dir, 'clean', '*.png')))] |
|
|
| for fol in ['train', 'val']: |
| for ind in index[fol]: |
| for subfol in ['clean_raw', 'clean']: |
| source = os.path.join(input_dir, subfol, allfiles[ind]) |
| destination = os.path.join('data', fol, subfol, allfiles[ind]) |
| copyfile(source, destination) |
|
|
| for subfol in ['noisy_raw']: |
| rawimg = get_visible_raw_image(os.path.join(input_dir, 'dng', folder_path, allfiles[ind][:-4] + '.dng')) |
| destination = os.path.join('data', fol, subfol, allfiles[ind]) |
| cv2.imwrite(destination, rawimg) |
|
|
| for subfol in ['metadata_raw']: |
| metadata = get_metadata(os.path.join(input_dir, 'dng', folder_path, allfiles[ind][:-4] + '.dng')) |
| pickle.dump(metadata, open(os.path.join('data', fol, subfol, allfiles[ind][:-4] + '.p'), "wb")) |
|
|
| for fol in ['test']: |
| for ind in test_index: |
| if folder_path == 'iso_50' or folder_path == 'iso_1600': |
| for subfol in ['clean_raw', 'clean']: |
| source = os.path.join(input_dir, subfol, allfiles[ind]) |
| destination = os.path.join('data', fol, subfol, allfiles[ind]) |
| copyfile(source, destination) |
|
|
| for subfol in ['dng']: |
| source = os.path.join(input_dir, subfol, folder_path, allfiles[ind][:-4]+'.dng') |
| destination = os.path.join('data', fol, subfol, folder_path, allfiles[ind][:-4]+'.dng') |
| copyfile(source, destination) |
|
|
|
|
| if __name__ == "__main__": |
| args = parse_args() |
| k_fold_indices = pickle.load(open(args.kfold_indices, "rb")) |
|
|
| if os.path.isdir('data'): rmtree('data') |
|
|
| if args.with_noise: |
| split_func(args, 'iso_1600', k_fold_indices) |
| split_func(args, 'iso_3200', k_fold_indices) |
| else: |
| split_func(args, 'iso_50', k_fold_indices) |
|
|
| print('Done!') |
|
|
