tf.image.adjust_contrast
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Adjust contrast of RGB or grayscale images.
tf.image.adjust_contrast(
images, contrast_factor
)
Used in the notebooks
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)>
Args |
|---|
images
|
Images to adjust. At least 3-D.
|
contrast_factor
|
A float multiplier for adjusting contrast.
|
Returns |
|---|
|
The contrast-adjusted image or images.
|
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Last updated 2024-04-26 UTC.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-04-26 UTC."],[],[],null,["# tf.image.adjust_contrast\n\n\u003cbr /\u003e\n\n|------------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.16.1/tensorflow/python/ops/image_ops_impl.py#L2253-L2309) |\n\nAdjust contrast of RGB or grayscale images.\n\n#### View aliases\n\n\n**Compat aliases for migration**\n\nSee\n[Migration guide](https://www.tensorflow.org/guide/migrate) for\nmore details.\n\n[`tf.compat.v1.image.adjust_contrast`](https://www.tensorflow.org/api_docs/python/tf/image/adjust_contrast)\n\n\u003cbr /\u003e\n\n tf.image.adjust_contrast(\n images, contrast_factor\n )\n\n### Used in the notebooks\n\n| Used in the guide |\n|--------------------------------------------------------------------------------------------------------|\n| - [Introduction to gradients and automatic differentiation](https://www.tensorflow.org/guide/autodiff) |\n\nThis is a convenience method that converts RGB images to float\nrepresentation, adjusts their contrast, and then converts them back to the\noriginal data type. If several adjustments are chained, it is advisable to\nminimize the number of redundant conversions.\n\n`images` is a tensor of at least 3 dimensions. The last 3 dimensions are\ninterpreted as `[height, width, channels]`. The other dimensions only\nrepresent a collection of images, such as `[batch, height, width, channels].`\n\nContrast is adjusted independently for each channel of each image.\n\nFor each channel, this Op computes the mean of the image pixels in the\nchannel and then adjusts each component `x` of each pixel to\n`(x - mean) * contrast_factor + mean`.\n\n`contrast_factor` must be in the interval `(-inf, inf)`.\n\n#### Usage Example:\n\n x = [[[1.0, 2.0, 3.0],\n [4.0, 5.0, 6.0]],\n [[7.0, 8.0, 9.0],\n [10.0, 11.0, 12.0]]]\n tf.image.adjust_contrast(x, 2.)\n \u003ctf.Tensor: shape=(2, 2, 3), dtype=float32, numpy=\n array([[[-3.5, -2.5, -1.5],\n [ 2.5, 3.5, 4.5]],\n [[ 8.5, 9.5, 10.5],\n [14.5, 15.5, 16.5]]], dtype=float32)\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|-------------------|--------------------------------------------|\n| `images` | Images to adjust. At least 3-D. |\n| `contrast_factor` | A float multiplier for adjusting contrast. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| The contrast-adjusted image or images. ||\n\n\u003cbr /\u003e"]]
View source on GitHub