Source code for rastervision.core.data.raster_transformer.raster_transformer
from typing import TYPE_CHECKING
from abc import (ABC, abstractmethod)
if TYPE_CHECKING:
import numpy as np
[docs]class RasterTransformer(ABC):
"""Transforms raw chips to be input to a neural network."""
[docs] @abstractmethod
def transform(self, chip: 'np.ndarray',
channel_order=None) -> 'np.ndarray':
"""Transform a chip of a raster source.
Args:
chip: ndarray of shape [height, width, channels] This is assumed to already
have the channel_order applied to it if channel_order is set. In other
words, channels should be equal to len(channel_order).
channel_order: list of indices of channels that were extracted from the
raw imagery.
Returns:
(np.ndarray): Array of shape (..., H, W, C)
"""
pass