dask_image.ndmeasure package

dask_image.ndmeasure.area(image, label_image=None, index=None)[source]

Find the area of specified subregions in an image.

Parameters
  • image (ndarray) – N-D image data

  • label_image (ndarray, optional) – Image features noted by integers. If None (default), returns area of total image dimensions.

  • index (int or sequence of ints, optional) – Labels to include in output. If None (default), all values where non-zero label_image are used. The index argument only works when label_image is specified.

Returns

area – Area of index selected regions from label_image.

Return type

ndarray

Example

>>> import dask.array as da
>>> image = da.random.random((3, 3))
>>> label_image = da.from_array(
    [[1, 1, 0],
     [1, 0, 3],
     [0, 7, 0]], chunks=(1, 3))
>>> # No labels given, returns area of total image dimensions
>>> area(image)
9
>>> # Combined area of all non-zero labels
>>> area(image, label_image).compute()
5
>>> # Areas of selected labels selected with the ``index`` keyword argument
>>> area(image, label_image, index=[0, 1, 2, 3]).compute()
array([4, 3, 0, 1], dtype=int64)
dask_image.ndmeasure.center_of_mass(image, label_image=None, index=None)[source]

Find the center of mass over an image at specified subregions.

Parameters
  • image (ndarray) – N-D image data

  • label_image (ndarray, optional) – Image features noted by integers. If None (default), all values.

  • index (int or sequence of ints, optional) –

    Labels to include in output. If None (default), all values where non-zero label_image are used.

    The index argument only works when label_image is specified.

Returns

center_of_mass – Coordinates of centers-of-mass of image over the index selected regions from label_image.

Return type

ndarray

dask_image.ndmeasure.extrema(image, label_image=None, index=None)[source]

Find the min and max with positions over an image at specified subregions.

Parameters
  • image (ndarray) – N-D image data

  • label_image (ndarray, optional) – Image features noted by integers. If None (default), all values.

  • index (int or sequence of ints, optional) –

    Labels to include in output. If None (default), all values where non-zero label_image are used.

    The index argument only works when label_image is specified.

Returns

minimums, maximums, min_positions, max_positions – Values and coordinates of minimums and maximums in each feature.

Return type

tuple of ndarrays

dask_image.ndmeasure.histogram(image, min, max, bins, label_image=None, index=None)[source]

Find the histogram over an image at specified subregions.

Histogram calculates the frequency of values in an array within bins determined by min, max, and bins. The label_image and index keywords can limit the scope of the histogram to specified sub-regions within the array.

Parameters
  • image (ndarray) – N-D image data

  • min (int) – Minimum value of range of histogram bins.

  • max (int) – Maximum value of range of histogram bins.

  • bins (int) – Number of bins.

  • label_image (ndarray, optional) – Image features noted by integers. If None (default), all values.

  • index (int or sequence of ints, optional) –

    Labels to include in output. If None (default), all values where non-zero label_image are used.

    The index argument only works when label_image is specified.

Returns

histogram – Histogram of image over the index selected regions from label_image.

Return type

ndarray

dask_image.ndmeasure.label(image, structure=None)[source]

Label features in an array.

Parameters
  • image (ndarray) – An array-like object to be labeled. Any non-zero values in image are counted as features and zero values are considered the background.

  • structure (ndarray, optional) –

    A structuring element that defines feature connections. structure must be symmetric. If no structuring element is provided, one is automatically generated with a squared connectivity equal to one. That is, for a 2-D image array, the default structuring element is:

    [[0,1,0],
     [1,1,1],
     [0,1,0]]
    

Returns

  • label (ndarray or int) – An integer ndarray where each unique feature in image has a unique label in the returned array.

  • num_features (int) – How many objects were found.

dask_image.ndmeasure.labeled_comprehension(image, label_image, index, func, out_dtype, default, pass_positions=False)[source]

Compute a function over an image at specified subregions.

Roughly equivalent to [func(image[labels == i]) for i in index].

Sequentially applies an arbitrary function (that works on array_like image) to subsets of an n-D image array specified by label_image and index. The option exists to provide the function with positional parameters as the second argument.

Parameters
  • image (ndarray) – N-D image data

  • label_image (ndarray, optional) – Image features noted by integers. If None (default), all values.

  • index (int or sequence of ints, optional) –

    Labels to include in output. If None (default), all values where non-zero label_image are used.

    The index argument only works when label_image is specified.

  • func (callable) – Python function to apply to label_image from image.

  • out_dtype (dtype) – Dtype to use for result.

  • default (int, float or None) – Default return value when a element of index does not exist in label_image.

  • pass_positions (bool, optional) – If True, pass linear indices to func as a second argument. Default is False.

Returns

result – Result of applying func on image over the index selected regions from label_image.

Return type

ndarray

dask_image.ndmeasure.maximum(image, label_image=None, index=None)[source]

Find the maxima over an image at specified subregions.

Parameters
  • image (ndarray) – N-D image data

  • label_image (ndarray, optional) – Image features noted by integers. If None (default), all values.

  • index (int or sequence of ints, optional) –

    Labels to include in output. If None (default), all values where non-zero label_image are used.

    The index argument only works when label_image is specified.

Returns

maxima – Maxima of image over the index selected regions from label_image.

Return type

ndarray

dask_image.ndmeasure.maximum_position(image, label_image=None, index=None)[source]

Find the positions of maxima over an image at specified subregions.

For each region specified by label_image, the position of the maximum value of image within the region is returned.

Parameters
  • image (ndarray) – N-D image data

  • label_image (ndarray, optional) – Image features noted by integers. If None (default), all values.

  • index (int or sequence of ints, optional) –

    Labels to include in output. If None (default), all values where non-zero label_image are used.

    The index argument only works when label_image is specified.

Returns

maxima_positions – Maxima positions of image over the index selected regions from label_image.

Return type

ndarray

dask_image.ndmeasure.mean(image, label_image=None, index=None)[source]

Find the mean over an image at specified subregions.

Parameters
  • image (ndarray) – N-D image data

  • label_image (ndarray, optional) – Image features noted by integers. If None (default), all values.

  • index (int or sequence of ints, optional) –

    Labels to include in output. If None (default), all values where non-zero label_image are used.

    The index argument only works when label_image is specified.

Returns

means – Mean of image over the index selected regions from label_image.

Return type

ndarray

dask_image.ndmeasure.median(image, label_image=None, index=None)[source]

Find the median over an image at specified subregions.

Parameters
  • image (ndarray) – N-D image data

  • label_image (ndarray, optional) – Image features noted by integers. If None (default), all values.

  • index (int or sequence of ints, optional) –

    Labels to include in output. If None (default), all values where non-zero label_image are used.

    The index argument only works when label_image is specified.

Returns

medians – Median of image over the index selected regions from label_image.

Return type

ndarray

dask_image.ndmeasure.minimum(image, label_image=None, index=None)[source]

Find the minima over an image at specified subregions.

Parameters
  • image (ndarray) – N-D image data

  • label_image (ndarray, optional) – Image features noted by integers. If None (default), all values.

  • index (int or sequence of ints, optional) –

    Labels to include in output. If None (default), all values where non-zero label_image are used.

    The index argument only works when label_image is specified.

Returns

minima – Minima of image over the index selected regions from label_image.

Return type

ndarray

dask_image.ndmeasure.minimum_position(image, label_image=None, index=None)[source]

Find the positions of minima over an image at specified subregions.

Parameters
  • image (ndarray) – N-D image data

  • label_image (ndarray, optional) – Image features noted by integers. If None (default), all values.

  • index (int or sequence of ints, optional) –

    Labels to include in output. If None (default), all values where non-zero label_image are used.

    The index argument only works when label_image is specified.

Returns

minima_positions – Maxima positions of image over the index selected regions from label_image.

Return type

ndarray

dask_image.ndmeasure.standard_deviation(image, label_image=None, index=None)[source]

Find the standard deviation over an image at specified subregions.

Parameters
  • image (ndarray) – N-D image data

  • label_image (ndarray, optional) – Image features noted by integers. If None (default), all values.

  • index (int or sequence of ints, optional) –

    Labels to include in output. If None (default), all values where non-zero label_image are used.

    The index argument only works when label_image is specified.

Returns

standard_deviation – Standard deviation of image over the index selected regions from label_image.

Return type

ndarray

dask_image.ndmeasure.sum(image, label_image=None, index=None)[source]

DEPRECATED FUNCTION. Use sum_labels instead.

dask_image.ndmeasure.sum_labels(image, label_image=None, index=None)[source]

Find the sum of all pixels over specified subregions of an image.

Parameters
  • image (ndarray) – N-D image data

  • label_image (ndarray, optional) – Image features noted by integers. If None (default), all values.

  • index (int or sequence of ints, optional) –

    Labels to include in output. If None (default), all values where non-zero label_image are used.

    The index argument only works when label_image is specified.

Returns

sum_lbl – Sum of image over the index selected regions from label_image.

Return type

ndarray

dask_image.ndmeasure.variance(image, label_image=None, index=None)[source]

Find the variance over an image at specified subregions.

Parameters
  • image (ndarray) – N-D image data

  • label_image (ndarray, optional) – Image features noted by integers. If None (default), all values.

  • index (int or sequence of ints, optional) –

    Labels to include in output. If None (default), all values where non-zero label_image are used.

    The index argument only works when label_image is specified.

Returns

variance – Variance of image over the index selected regions from label_image.

Return type

ndarray