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 \(D = C \times H \times W\).
- Raises
- Supported Platforms:
CPU
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")