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# http://www.apache.org/licenses/LICENSE-2.0
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from typing import Any, Tuple, List
import sys
matx = sys.modules['matx']
from .. import ASYNC, NormalizeOp
from ._base import BaseInterfaceClass, BatchBaseClass
[docs]class Normalize(BaseInterfaceClass):
[docs] def __init__(self,
mean: List[float],
std: List[float],
global_scale: float = 1.0,
device_id: int = -2,
sync: int = ASYNC) -> None:
super().__init__(device_id=device_id, sync=sync)
self._mean: List[float] = mean
self._std: List[float] = std
self._global_scale: float = global_scale
[docs] def __call__(self, device: Any, device_str: str, sync: int) -> Any:
return NormalizeImpl(device, device_str, self._mean, self._std, self._global_scale, sync)
class NormalizeImpl(BatchBaseClass):
def __init__(self,
device: Any,
device_str: str,
mean: List[float],
std: List[float],
global_scale: float = 1.0,
sync: int = ASYNC) -> None:
super().__init__()
self.global_scale: float = global_scale
self.mean: List[float] = [i / global_scale for i in mean]
self.std: List[float] = [i / global_scale for i in std]
self.device_str: str = device_str
self.op: NormalizeOp = NormalizeOp(device, self.mean, self.std)
self.sync: int = sync
self.name: str = "Normalize"
def _process(self, imgs: List[matx.NDArray]) -> List[matx.NDArray]:
return self.op(imgs, sync=self.sync)
def __repr__(self) -> str:
return self.name + '(mean={0}, std={1}, device={2}, sync={3})'.format(
self.mean, self.std, self.device_str, self.sync)