(sigma_min: float, sigma_max: float)
return torch.empty(1).uniform_(sigma_min, sigma_max).item()
Choose sigma for random gaussian blurring.

        Args:
            sigma_min (float): Minimum standard deviation that can be chosen for blurring kernel.
            sigma_max (float): Maximum standard deviation that can be chosen for blurring kernel.

        Returns:
            float: Standard deviation to be passed to calculate kernel for gaussian blurring.
Choose sigma for random gaussian blurring.
Choose sigma for random gaussian blurring .
def get_params(sigma_min: float, sigma_max: float) -> float:
        """Choose sigma for random gaussian blurring.

        Args:
            sigma_min (float): Minimum standard deviation that can be chosen for blurring kernel.
            sigma_max (float): Maximum standard deviation that can be chosen for blurring kernel.

        Returns:
            float: Standard deviation to be passed to calculate kernel for gaussian blurring.
        """
        return torch.empty(1).uniform_(sigma_min, sigma_max).item()
def get_params ( sigma_min : float , sigma_max : float ) -> float : return torch . empty ( 1 ) . uniform_ ( sigma_min , sigma_max ) . item ( )