Image Processing SciKit (Toolbox for SciPy)
scikit-image
(a.k.a. skimage
) is a collection of algorithms for image processing and computer vision.
The main package of skimage
only provides a few utilities for converting between image data types; for most features, you need to import one of the following subpackages:
img_as_float64
, but will not convert lower-precision floating point arrays to float64
.
skimage.dtype_limits (image[, clip_negative]) | Return intensity limits, i.e. |
skimage.img_as_bool (image[, force_copy]) | Convert an image to boolean format. |
skimage.img_as_float (image[, force_copy]) | Convert an image to floating point format. |
skimage.img_as_float32 (image[, force_copy]) | Convert an image to single-precision (32-bit) floating point format. |
skimage.img_as_float64 (image[, force_copy]) | Convert an image to double-precision (64-bit) floating point format. |
skimage.img_as_int (image[, force_copy]) | Convert an image to 16-bit signed integer format. |
skimage.img_as_ubyte (image[, force_copy]) | Convert an image to 8-bit unsigned integer format. |
skimage.img_as_uint (image[, force_copy]) | Convert an image to 16-bit unsigned integer format. |
skimage.lookfor (what) | Do a keyword search on scikit-image docstrings. |
skimage.test ([doctest, verbose]) | Run all unit tests. |
skimage.color | |
skimage.data | Standard test images. |
skimage.draw | |
skimage.exposure | |
skimage.external | |
skimage.filters | |
skimage.io | Utilities to read and write images in various formats. |
skimage.measure | |
skimage.restoration | Image restoration module. |
skimage.transform | |
skimage.util |
skimage.dtype_limits(image, clip_negative=None)
[source]
Return intensity limits, i.e. (min, max) tuple, of the image’s dtype.
Parameters: |
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Returns: |
|
skimage.img_as_bool(image, force_copy=False)
[source]
Convert an image to boolean format.
Parameters: |
|
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Returns: |
|
The upper half of the input dtype’s positive range is True, and the lower half is False. All negative values (if present) are False.
skimage.img_as_float(image, force_copy=False)
[source]
Convert an image to floating point format.
This function is similar to img_as_float64
, but will not convert lower-precision floating point arrays to float64
.
Parameters: |
|
---|---|
Returns: |
|
The range of a floating point image is [0.0, 1.0] or [-1.0, 1.0] when converting from unsigned or signed datatypes, respectively. If the input image has a float type, intensity values are not modified and can be outside the ranges [0.0, 1.0] or [-1.0, 1.0].
skimage.img_as_float32(image, force_copy=False)
[source]
Convert an image to single-precision (32-bit) floating point format.
Parameters: |
|
---|---|
Returns: |
|
The range of a floating point image is [0.0, 1.0] or [-1.0, 1.0] when converting from unsigned or signed datatypes, respectively. If the input image has a float type, intensity values are not modified and can be outside the ranges [0.0, 1.0] or [-1.0, 1.0].
skimage.img_as_float64(image, force_copy=False)
[source]
Convert an image to double-precision (64-bit) floating point format.
Parameters: |
|
---|---|
Returns: |
|
The range of a floating point image is [0.0, 1.0] or [-1.0, 1.0] when converting from unsigned or signed datatypes, respectively. If the input image has a float type, intensity values are not modified and can be outside the ranges [0.0, 1.0] or [-1.0, 1.0].
skimage.img_as_int(image, force_copy=False)
[source]
Convert an image to 16-bit signed integer format.
Parameters: |
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Returns: |
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The values are scaled between -32768 and 32767. If the input data-type is positive-only (e.g., uint8), then the output image will still only have positive values.
skimage.img_as_ubyte(image, force_copy=False)
[source]
Convert an image to 8-bit unsigned integer format.
Parameters: |
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Returns: |
|
Negative input values will be clipped. Positive values are scaled between 0 and 255.
skimage.img_as_uint(image, force_copy=False)
[source]
Convert an image to 16-bit unsigned integer format.
Parameters: |
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Returns: |
|
Negative input values will be clipped. Positive values are scaled between 0 and 65535.
skimage.lookfor(what)
[source]
Do a keyword search on scikit-image docstrings.
Parameters: |
|
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>>> import skimage >>> skimage.lookfor('regular_grid') Search results for 'regular_grid' --------------------------------- skimage.lookfor Do a keyword search on scikit-image docstrings. skimage.util.regular_grid Find `n_points` regularly spaced along `ar_shape`.
skimage.test(doctest=False, verbose=False)
[source]
Run all unit tests.
© 2011 the scikit-image team
Licensed under the BSD 3-clause License.
http://scikit-image.org/docs/0.14.x/api/skimage.html