Python torch.utils.data.LQ_dataset() Examples

The following are 5 code examples of torch.utils.data.LQ_dataset(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module torch.utils.data , or try the search function .
Example #1
Source File: __init__.py    From BasicSR with Apache License 2.0 6 votes vote down vote up 
def create_dataset(dataset_opt):
    mode = dataset_opt['mode']
    if mode == 'LQ':
        from data.LQ_dataset import LQDataset as D
    elif mode == 'LQGT':
        from data.LQGT_dataset import LQGTDataset as D
    # elif mode == 'LQGTseg_bg':
    #     from data.LQGT_seg_bg_dataset import LQGTSeg_BG_Dataset as D
    else:
        raise NotImplementedError('Dataset [{:s}] is not recognized.'.format(mode))
    dataset = D(dataset_opt)

    logger = logging.getLogger('base')
    logger.info('Dataset [{:s} - {:s}] is created.'.format(dataset.__class__.__name__,
                                                           dataset_opt['name']))
    return dataset
Example #2
Source File: __init__.py    From real-world-sr with MIT License 6 votes vote down vote up 
def create_dataset(dataset_opt):
    mode = dataset_opt['mode']
    if mode == 'LQ':
        from data.LQ_dataset import LQDataset as D
    elif mode == 'LQGT':
        from data.LQGT_dataset import LQGTDataset as D
    # elif mode == 'LQGTseg_bg':
    #     from data.LQGT_seg_bg_dataset import LQGTSeg_BG_Dataset as D
    else:
        raise NotImplementedError('Dataset [{:s}] is not recognized.'.format(mode))
    dataset = D(dataset_opt)

    logger = logging.getLogger('base')
    logger.info('Dataset [{:s} - {:s}] is created.'.format(dataset.__class__.__name__,
                                                           dataset_opt['name']))
    return dataset
Example #3
Source File: __init__.py    From IKC with Apache License 2.0 6 votes vote down vote up 
def create_dataset(dataset_opt):
    mode = dataset_opt['mode']
    if mode == 'LQ': #Predictor
        from data.LQ_dataset import LQDataset as D
        dataset = D(dataset_opt)
    elif mode == 'LQGTker': #SFTMD
        from data.LQGTker_dataset import LQGTKerDataset as D
        dataset = D(dataset_opt)
    elif mode == 'SRker': #Corrector
        from data.SRker_dataset import SRkerDataset as D
        dataset = D(dataset_opt)
    # elif mode == 'LQGTseg_bg':
    #     from data.LQGT_seg_bg_dataset import LQGTSeg_BG_Dataset as D
    else:
        raise NotImplementedError('Dataset [{:s}] is not recognized.'.format(mode))

    logger = logging.getLogger('base')
    logger.info('Dataset [{:s} - {:s}] is created.'.format(dataset.__class__.__name__,
                                                           dataset_opt['name']))
    return dataset
Example #4
Source File: __init__.py    From EDVR with Apache License 2.0 6 votes vote down vote up 
def create_dataset(dataset_opt):
    mode = dataset_opt['mode']
    # datasets for image restoration
    if mode == 'LQ':
        from data.LQ_dataset import LQDataset as D
    elif mode == 'LQGT':
        from data.LQGT_dataset import LQGTDataset as D
    # datasets for video restoration
    elif mode == 'REDS':
        from data.REDS_dataset import REDSDataset as D
    elif mode == 'Vimeo90K':
        from data.Vimeo90K_dataset import Vimeo90KDataset as D
    elif mode == 'video_test':
        from data.video_test_dataset import VideoTestDataset as D
    else:
        raise NotImplementedError('Dataset [{:s}] is not recognized.'.format(mode))
    dataset = D(dataset_opt)

    logger = logging.getLogger('base')
    logger.info('Dataset [{:s} - {:s}] is created.'.format(dataset.__class__.__name__,
                                                           dataset_opt['name']))
    return dataset
Example #5
Source File: __init__.py    From mmsr with Apache License 2.0 6 votes vote down vote up 
def create_dataset(dataset_opt):
    mode = dataset_opt['mode']
    # datasets for image restoration
    if mode == 'LQ':
        from data.LQ_dataset import LQDataset as D
    elif mode == 'LQGT':
        from data.LQGT_dataset import LQGTDataset as D
    # datasets for video restoration
    elif mode == 'REDS':
        from data.REDS_dataset import REDSDataset as D
    elif mode == 'Vimeo90K':
        from data.Vimeo90K_dataset import Vimeo90KDataset as D
    elif mode == 'video_test':
        from data.video_test_dataset import VideoTestDataset as D
    else:
        raise NotImplementedError('Dataset [{:s}] is not recognized.'.format(mode))
    dataset = D(dataset_opt)

    logger = logging.getLogger('base')
    logger.info('Dataset [{:s} - {:s}] is created.'.format(dataset.__class__.__name__,
                                                           dataset_opt['name']))
    return dataset