ยป Keras API reference / KerasCV / Layers / Preprocessing layers / Grayscale layer

Grayscale layer

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Grayscale class

keras_cv.layers.Grayscale(output_channels=1, **kwargs)

Grayscale is a preprocessing layer that transforms RGB images to Grayscale images. Input images should have values in the range of [0, 255].

Input shape

3D (unbatched) or 4D (batched) tensor with shape: (..., height, width, channels), in "channels_last" format

Output shape

3D (unbatched) or 4D (batched) tensor with shape: (..., height, width, channels), in "channels_last" format

Arguments

output_channels. Number color channels present in the output image. The output_channels can be 1 or 3. RGB image with shape (..., height, width, 3) will have the following shapes after the Grayscale operation: a. (..., height, width, 1) if output_channels = 1 b. (..., height, width, 3) if output_channels = 3.

Usage:

(images, labels), _ = tf.keras.datasets.cifar10.load_data()
to_grayscale = keras_cv.layers.preprocessing.Grayscale()
augmented_images = to_grayscale(images)