Preprocessing layer for random inversion of image colors.
Source:R/layers-preprocessing.R
layer_random_invert.Rd
This layer randomly inverts the colors of input images with a specified probability range. When applied, each image has a chance of having its colors inverted, where the pixel values are transformed to their complementary values. Images that are not selected for inversion remain unchanged.
Usage
layer_random_invert(
object,
factor = 1,
value_range = list(0L, 255L),
seed = NULL,
data_format = NULL,
...
)
Arguments
- object
Object to compose the layer with. A tensor, array, or sequential model.
- factor
A single float or a tuple of two floats.
factor
controls the probability of inverting the image colors. If a tuple is provided, the value is sampled between the two values for each image, wherefactor[0]
is the minimum andfactor[1]
is the maximum probability. If a single float is provided, a value between0.0
and the provided float is sampled. Defaults to(0, 1)
.- value_range
a tuple or a list of two elements. The first value represents the lower bound for values in passed images, the second represents the upper bound. Images passed to the layer should have values within
value_range
. Defaults to(0, 255)
.- seed
Integer. Used to create a random seed.
- data_format
string, either
"channels_last"
or"channels_first"
. The ordering of the dimensions in the inputs."channels_last"
corresponds to inputs with shape(batch, height, width, channels)
while"channels_first"
corresponds to inputs with shape(batch, channels, height, width)
. It defaults to theimage_data_format
value found in your Keras config file at~/.keras/keras.json
. If you never set it, then it will be"channels_last"
.- ...
For forward/backward compatability.
See also
Other image preprocessing layers: layer_aug_mix()
layer_auto_contrast()
layer_center_crop()
layer_cut_mix()
layer_equalization()
layer_max_num_bounding_boxes()
layer_mix_up()
layer_rand_augment()
layer_random_color_degeneration()
layer_random_color_jitter()
layer_random_erasing()
layer_random_gaussian_blur()
layer_random_grayscale()
layer_random_hue()
layer_random_perspective()
layer_random_posterization()
layer_random_saturation()
layer_random_sharpness()
layer_random_shear()
layer_rescaling()
layer_resizing()
layer_solarization()
Other preprocessing layers: layer_aug_mix()
layer_auto_contrast()
layer_category_encoding()
layer_center_crop()
layer_cut_mix()
layer_discretization()
layer_equalization()
layer_feature_space()
layer_hashed_crossing()
layer_hashing()
layer_integer_lookup()
layer_max_num_bounding_boxes()
layer_mel_spectrogram()
layer_mix_up()
layer_normalization()
layer_rand_augment()
layer_random_brightness()
layer_random_color_degeneration()
layer_random_color_jitter()
layer_random_contrast()
layer_random_crop()
layer_random_erasing()
layer_random_flip()
layer_random_gaussian_blur()
layer_random_grayscale()
layer_random_hue()
layer_random_perspective()
layer_random_posterization()
layer_random_rotation()
layer_random_saturation()
layer_random_sharpness()
layer_random_shear()
layer_random_translation()
layer_random_zoom()
layer_rescaling()
layer_resizing()
layer_solarization()
layer_stft_spectrogram()
layer_string_lookup()
layer_text_vectorization()
Other layers: Layer()
layer_activation()
layer_activation_elu()
layer_activation_leaky_relu()
layer_activation_parametric_relu()
layer_activation_relu()
layer_activation_softmax()
layer_activity_regularization()
layer_add()
layer_additive_attention()
layer_alpha_dropout()
layer_attention()
layer_aug_mix()
layer_auto_contrast()
layer_average()
layer_average_pooling_1d()
layer_average_pooling_2d()
layer_average_pooling_3d()
layer_batch_normalization()
layer_bidirectional()
layer_category_encoding()
layer_center_crop()
layer_concatenate()
layer_conv_1d()
layer_conv_1d_transpose()
layer_conv_2d()
layer_conv_2d_transpose()
layer_conv_3d()
layer_conv_3d_transpose()
layer_conv_lstm_1d()
layer_conv_lstm_2d()
layer_conv_lstm_3d()
layer_cropping_1d()
layer_cropping_2d()
layer_cropping_3d()
layer_cut_mix()
layer_dense()
layer_depthwise_conv_1d()
layer_depthwise_conv_2d()
layer_discretization()
layer_dot()
layer_dropout()
layer_einsum_dense()
layer_embedding()
layer_equalization()
layer_feature_space()
layer_flatten()
layer_flax_module_wrapper()
layer_gaussian_dropout()
layer_gaussian_noise()
layer_global_average_pooling_1d()
layer_global_average_pooling_2d()
layer_global_average_pooling_3d()
layer_global_max_pooling_1d()
layer_global_max_pooling_2d()
layer_global_max_pooling_3d()
layer_group_normalization()
layer_group_query_attention()
layer_gru()
layer_hashed_crossing()
layer_hashing()
layer_identity()
layer_integer_lookup()
layer_jax_model_wrapper()
layer_lambda()
layer_layer_normalization()
layer_lstm()
layer_masking()
layer_max_num_bounding_boxes()
layer_max_pooling_1d()
layer_max_pooling_2d()
layer_max_pooling_3d()
layer_maximum()
layer_mel_spectrogram()
layer_minimum()
layer_mix_up()
layer_multi_head_attention()
layer_multiply()
layer_normalization()
layer_permute()
layer_rand_augment()
layer_random_brightness()
layer_random_color_degeneration()
layer_random_color_jitter()
layer_random_contrast()
layer_random_crop()
layer_random_erasing()
layer_random_flip()
layer_random_gaussian_blur()
layer_random_grayscale()
layer_random_hue()
layer_random_perspective()
layer_random_posterization()
layer_random_rotation()
layer_random_saturation()
layer_random_sharpness()
layer_random_shear()
layer_random_translation()
layer_random_zoom()
layer_repeat_vector()
layer_rescaling()
layer_reshape()
layer_resizing()
layer_rms_normalization()
layer_rnn()
layer_separable_conv_1d()
layer_separable_conv_2d()
layer_simple_rnn()
layer_solarization()
layer_spatial_dropout_1d()
layer_spatial_dropout_2d()
layer_spatial_dropout_3d()
layer_spectral_normalization()
layer_stft_spectrogram()
layer_string_lookup()
layer_subtract()
layer_text_vectorization()
layer_tfsm()
layer_time_distributed()
layer_torch_module_wrapper()
layer_unit_normalization()
layer_upsampling_1d()
layer_upsampling_2d()
layer_upsampling_3d()
layer_zero_padding_1d()
layer_zero_padding_2d()
layer_zero_padding_3d()
rnn_cell_gru()
rnn_cell_lstm()
rnn_cell_simple()
rnn_cells_stack()