(self, model: BasicVSRPlusPlusGan, device: torch.device, fp16: bool)

(self, file_path: str, video_meta_data: VideoMetadata)

(self, scene: Scene, size, pad_mode, id)

(self, model: Yolo11SegmentationModel, video_metadata: VideoMetadata, frame_detection_queue: PipelineQueue, mo

(self, device, video_file, max_clip_length, mosaic_restoration_model_name, mosaic_detection_m

(self, model, device)

(self)

(self)

(self)

(self, initial: FrameRestorerOptions | None = None)

(self)

(self, video_file)

(self, frame_restorer)

(self, **kwargs)

(self)

(self, **kwargs)

(self, **kwargs)

(self, **kwargs)

(self, watched_widget: Gtk.Widget, overlay_widgets: list[Gtk.Widget])

(self, frame_restorer_provider: FrameRestorerProvider, buffer_queue_min_thresh_time, buffer_queue_max_thresh_t

(self, **kwargs)

(self, **kwargs)

(self, style_manager: Adw.StyleManager)

(self, preset: EncodingPreset, config: Config, create_new: bool, **kwargs)

(self, **kwargs)

(self, **kwargs)

(self, **kwargs)

(self, video_metadata: VideoMetadata)

(self, **kwargs)

(self, **kwargs)

(self, **kwargs)

(self)

(self)

(self, original_file: Gio.File, restored_file: Gio.File, **kwargs)

(self, *args, **kwargs)

(self, model_path: str, device, imgsz=640, fp16=False, **kwargs)

(self, **kwargs)

(self, **opt)

(self, in_channels, out_channels, kernel_size,

(self, interval: dict = {}, on_train=False, on_val=True,

(self, interval: int = 1000, vis_kwargs_list: Tuple[List[dict], dict] = None

( self, kernel_size: Tuple[int, int] = (71, 71), sigma: Tuple[float, float] = (10.0, 1

(self, loss_weight: float = 1.)

(self, loss_weight: float = 0.1)

(self, save_dir: str, exp_name: Optional[str] = None, label

(self, in_channels, mid_channels=64, skip_connection=True)

(self, generator, pixel_loss, train_cfg=None,

(self, gt_key: str = 'gt_img', pred_key: str = 'pred_img',

(self, generator, discriminator=None, gan_loss=None,

(self, module_keys, interp_mode='lerp', interp_cfg=None,

(self, mid_channels=64, num_blocks=7, max_residue_magnitude

(self, *args, **kwargs)

(self, in_channels, out_channels=64, num_blocks=30)

(self, in_channels, out_channels, kernel_size, stride, padding, activation)

(self)

(self, mid_channels: int = 64, res_scale: float = 1.0)

(self, in_channels: int, out_channels: int, scale_factor: int, upsample_kernel: int)

(self, metrics: Union[dict, BaseMetric, Sequence])

(self, loss_weight: float = 1.0, reduction: str = 'mean', s

(self, loss_weight: float = 1.0, reduction: str = 'mean', s

(self, loss_weight: float = 1.0)

(self, loss_weight: float = 1.0, toY: bool = False)

(self, generator: dict, pixel_loss: dict, train_cfg: Option

(self, mean: Union[Sequence[Union[float, int]], float, int] = 127.5, std: Un

(self, gt_key: str = 'gt_img', pred_key: str = 'pred_img',

(self, optim_wrapper_cfg: dict, paramwise_cfg=None)

(self, runner, dataloader: DATALOADER_TYPE, evaluator: EVAL

(self, runner, dataloader, evaluator, fp16=False)

(self, sample_kwargs: dict, runner: Optional[Runner] = None)

(self, sample_kwargs: dict, runner: Runner)

(self, sample_kwargs: dict, runner: Runner)

(self, sample_kwargs: dict, runner: Runner)

(self, gt_key: str = 'gt_img', pred_key: str = 'pred_img',

(self, fn_key: str, img_keys: Sequence[str], pixel_range={}

(self, layer_weights: dict, layer_weights_style: Optional[dict] = None,

(self, loss_weight: float = 1.0, use_attention: bool = True,

(self, fake_nums: int, real_nums: int = 0, fake_key: Option

(self, batch_size, max_length, sample_model, dataset, need_cond, sample_kwargs)

(self, nc=80, anchors=(), ch=(), inplace=True, num_offsets=0)

(self, c1, c2, k=1, s=1, p=None, g=1, act=True)

(self, c1, c2, k=1, s=1, act=True)

(self, c, num_heads)

(self, c1, c2, num_heads, num_layers)

(self, c1, c2, shortcut=True, g=1, e=0.5)

(self, c1, c2, n=1, shortcut=True, g=1, e=0.5)

(self, c1, c2, n=1, shortcut=True, g=1, e=0.5)

(self, c1, c2, k=(5, 9, 13), n=1, shortcut=True, g=1, e=0.5)

(self, c1, c2, n=1, shortcut=True, g=1, e=0.5)

(self, c1, c2, k=(5, 9, 13))

(self, c1, c2, k=5)

(self, c1, c2, k=1, s=1, p=None, g=1, act=True)

(self, c1, c2, k=1, s=1, g=1, act=True)

(self, c1, c2, k=3, s=1)

(self, gain=2)

(self, gain=2)

(self, dimension=1)

(self, model)

(self, imgs, pred, files, times=None, names=None, shape=None)

(self, c1, c2, k=3, s=1, g=1, e=1.0, shortcut=False)

(self, c1, c2, k=(1, 3), s=1, equal_ch=True)