mindspore.dataset.vision.py_transforms.LinearTransformation

class mindspore.dataset.vision.py_transforms.LinearTransformation(transformation_matrix, mean_vector)[source]

Transform the input numpy.ndarray image with a given square transformation matrix and a mean vector. It will first flatten the input image and subtract the mean vector from it, then compute the dot product with the transformation matrix, finally reshape it back to its original shape.

Parameters

transformation_matrix (numpy.ndarray) – A square transformation matrix in shape of (D, D), where \(D = C \times H \times W\).
mean_vector (numpy.ndarray) – A mean vector in shape of (D,), where \(D = C \times H \times W\).

Examples

>>> from mindspore.dataset.transforms.py_transforms import Compose
>>> import numpy as np
>>> height, width = 32, 32
>>> dim = 3 * height * width
>>> transformation_matrix = np.ones([dim, dim])
>>> mean_vector = np.zeros(dim)
>>> transforms_list = Compose([py_vision.Decode(),
...                            py_vision.Resize((height,width)),
...                            py_vision.ToTensor(),
...                            py_vision.LinearTransformation(transformation_matrix, mean_vector)])
>>> # apply the transform to dataset through map function
>>> image_folder_dataset = image_folder_dataset.map(operations=transforms_list,
...                                                 input_columns="image")