tf.keras.preprocessing.image.random_channel

TensorFlow 1 version

View source on GitHub

Performs a random spatial shear of a Numpy image tensor.

View aliases

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.keras.preprocessing.image.random_shear

tf.keras.preprocessing.image.random_shear(
    x, intensity, row_axis=1, col_axis=2, channel_axis=0,
    fill_mode='nearest', cval=0.0, interpolation_order=1
)

Arguments
`x`	Input tensor. Must be 3D.
`intensity`	Transformation intensity in degrees.
`row_axis`	Index of axis for rows in the input tensor.
`col_axis`	Index of axis for columns in the input tensor.
`channel_axis`	Index of axis for channels in the input tensor.
`fill_mode`	Points outside the boundaries of the input are filled according to the given mode (one of `{'constant', 'nearest', 'reflect', 'wrap'}`).
`cval`	Value used for points outside the boundaries of the input if `mode='constant'`.
`interpolation_order`	int, order of spline interpolation. see `ndimage.interpolation.affine_transform`

Returns
Sheared Numpy image tensor.

TensorFlow

tf

tf.audio

tf.autograph

tf.bitwise

tf.compat

tf.config

tf.data

tf.debugging

tf.distribute

tf.dtypes

tf.errors

tf.estimator

tf.experimental

tf.feature_column

tf.graph_util

tf.image

tf.initializers

tf.io

tf.keras

tf.linalg

tf.lite

tf.lookup

tf.losses

tf.math

tf.metrics

tf.nest

tf.nn

tf.optimizers

tf.quantization

tf.queue

tf.ragged

tf.random

tf.raw_ops

tf.saved_model

tf.sets

tf.signal

tf.sparse

tf.strings

tf.summary

tf.sysconfig

tf.test

tf.tpu

tf.train

tf.version

tf.xla

tf.keras / preprocessing / preprocessing.image.random_channel_shift

View aliases

Arguments

Returns