# tf.image.adjust_contrast

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| [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.13.1/tensorflow/python/ops/image_ops_impl.py#L2243-L2299) |

Adjust contrast of RGB or grayscale images.

#### View aliases


**Compat aliases for migration**

See
[Migration guide](https://www.tensorflow.org/guide/migrate) for
more details.

[`tf.compat.v1.image.adjust_contrast`](https://www.tensorflow.org/api_docs/python/tf/image/adjust_contrast)

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    tf.image.adjust_contrast(
        images, contrast_factor
    )

This is a convenience method that converts RGB images to float
representation, adjusts their contrast, and then converts them back to the
original data type. If several adjustments are chained, it is advisable to
minimize the number of redundant conversions.

`images` is a tensor of at least 3 dimensions. The last 3 dimensions are
interpreted as `[height, width, channels]`. The other dimensions only
represent a collection of images, such as `[batch, height, width, channels].`

Contrast is adjusted independently for each channel of each image.

For each channel, this Op computes the mean of the image pixels in the
channel and then adjusts each component `x` of each pixel to
`(x - mean) * contrast_factor + mean`.

`contrast_factor` must be in the interval `(-inf, 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_contrast(x, 2.)
    <tf.Tensor: shape=(2, 2, 3), dtype=float32, numpy=
    array([[[-3.5, -2.5, -1.5],
            [ 2.5,  3.5,  4.5]],
           [[ 8.5,  9.5, 10.5],
            [14.5, 15.5, 16.5]]], dtype=float32)>

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| ## Args ||
|---|---|
| `images` | Images to adjust. At least 3-D. |
| `contrast_factor` | A float multiplier for adjusting contrast. |

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| ## Returns ||
|---|---|
| The contrast-adjusted image or images. ||

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