import logging logger = logging.getLogger('base') def create_model(opt): model = opt['model'] # image restoration if model == 'sr': # PSNR-oriented super resolution from .SR_model import SRModel as M elif model == 'srgan' or model == 'corruptgan': # GAN-based super resolution(SRGAN / ESRGAN), or corruption use same logic from .SRGAN_model import SRGANModel as M # video restoration elif model == 'video_base': from .Video_base_model import VideoBaseModel as M else: raise NotImplementedError('Model [{:s}] not recognized.'.format(model)) m = M(opt) logger.info('Model [{:s}] is created.'.format(m.__class__.__name__)) return m