tf.image.adjust_saturation  |  TensorFlow v2.16.1 (original) (raw)

tf.image.adjust_saturation

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Adjust saturation of RGB images.

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tf.compat.v1.image.adjust_saturation

tf.image.adjust_saturation(
    image, saturation_factor, name=None
)

Used in the notebooks

This is a convenience method that converts RGB images to float representation, converts them to HSV, adds an offset to the saturation channel, converts back to RGB and then back to the original data type. If several adjustments are chained it is advisable to minimize the number of redundant conversions.

image is an RGB image or images. The image saturation is adjusted by converting the images to HSV and multiplying the saturation (S) channel bysaturation_factor and clipping. The images are then converted back to RGB.

saturation_factor must be in the interval [0, inf).

Usage Example:

x = [[[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]], [[7.0, 8.0, 9.0], [10.0, 11.0, 12.0]]] tf.image.adjust_saturation(x, 0.5) <tf.Tensor: shape=(2, 2, 3), dtype=float32, numpy= array([[[ 2. , 2.5, 3. ], [ 5. , 5.5, 6. ]], [[ 8. , 8.5, 9. ], [11. , 11.5, 12. ]]], dtype=float32)>