svjack/Kolors-Controlnet_and_IPA

1import random2import time3from os import path as osp4from torch.utils import data as data5from torchvision.transforms.functional import normalize6 7from basicsr.data.transforms import augment8from basicsr.utils import FileClient, get_root_logger, imfrombytes, img2tensor9from basicsr.utils.registry import DATASET_REGISTRY10 11 12@DATASET_REGISTRY.register()13class FFHQDataset(data.Dataset):14    """FFHQ dataset for StyleGAN.15 16    Args:17        opt (dict): Config for train datasets. It contains the following keys:18            dataroot_gt (str): Data root path for gt.19            io_backend (dict): IO backend type and other kwarg.20            mean (list | tuple): Image mean.21            std (list | tuple): Image std.22            use_hflip (bool): Whether to horizontally flip.23 24    """25 26    def __init__(self, opt):27        super(FFHQDataset, self).__init__()28        self.opt = opt29        # file client (io backend)30        self.file_client = None31        self.io_backend_opt = opt['io_backend']32 33        self.gt_folder = opt['dataroot_gt']34        self.mean = opt['mean']35        self.std = opt['std']36 37        if self.io_backend_opt['type'] == 'lmdb':38            self.io_backend_opt['db_paths'] = self.gt_folder39            if not self.gt_folder.endswith('.lmdb'):40                raise ValueError("'dataroot_gt' should end with '.lmdb', but received {self.gt_folder}")41            with open(osp.join(self.gt_folder, 'meta_info.txt')) as fin:42                self.paths = [line.split('.')[0] for line in fin]43        else:44            # FFHQ has 70000 images in total45            self.paths = [osp.join(self.gt_folder, f'{v:08d}.png') for v in range(70000)]46 47    def __getitem__(self, index):48        if self.file_client is None:49            self.file_client = FileClient(self.io_backend_opt.pop('type'), **self.io_backend_opt)50 51        # load gt image52        gt_path = self.paths[index]53        # avoid errors caused by high latency in reading files54        retry = 355        while retry > 0:56            try:57                img_bytes = self.file_client.get(gt_path)58            except Exception as e:59                logger = get_root_logger()60                logger.warning(f'File client error: {e}, remaining retry times: {retry - 1}')61                # change another file to read62                index = random.randint(0, self.__len__())63                gt_path = self.paths[index]64                time.sleep(1)  # sleep 1s for occasional server congestion65            else:66                break67            finally:68                retry -= 169        img_gt = imfrombytes(img_bytes, float32=True)70 71        # random horizontal flip72        img_gt = augment(img_gt, hflip=self.opt['use_hflip'], rotation=False)73        # BGR to RGB, HWC to CHW, numpy to tensor74        img_gt = img2tensor(img_gt, bgr2rgb=True, float32=True)75        # normalize76        normalize(img_gt, self.mean, self.std, inplace=True)77        return {'gt': img_gt, 'gt_path': gt_path}78 79    def __len__(self):80        return len(self.paths)81