CSemanticSegmentationIO

class ikomia.dataprocess.pydataprocess.CSemanticSegmentationIO

Define input or output managing common information extracted by semantic segmentation task. Such task are able to automatically set a class for each pixel of an image. Thus, this input/output stores labelled image, class names and class colors. Among others, algorithms like DeepLabV3+, UNet or TransUNet are semantic segmentation tasks.

Import

from ikomia.dataprocess import CSemanticSegmentationIO

Methods

__init__(arg1)

__init__( (object)self) -> None :

get_mask(self)

Get labelled image (ie graylevel) where each pixel has a specific value corresponding to its class.

get_class_names(self)

Get class names list associated with the semantic mask.

get_colors(self)

Get colors associated with class names.

get_polygons(self)

Get polygons of connected components extracted from segmentation mask.

set_class_colors(self, colors)

Set class colors associated with segmentation mask.

set_class_names(self, names)

Set class names associated with segmentation mask.

set_mask(self, mask)

Set the mask of the semantic segmentation output.

Overridden methods

clear_data(self)

See clear_data().

from_json(self, jsonStr)

Set input/output data from JSON formatted string.

is_data_available(self)

See is_data_available().

load(self, path)

Load instance segmentation input/output for JSON file.

save(self, path)

Save instance segmentation input/output to JSON file.

to_json(self)

Return input/output data in JSON formatted string (compact mode and image encoded as JPEG).

Inherited methods

copy_static_data(self, io)

Copy the static data from the given input or ouput.

get_unit_element_count(self)

Get the number of unit elements in terms of processing scheme.

Attributes

auto_save

Auto-save status

data_type

I/O data type

dim_count

Number of dimensions

description

Custom description to explain input/output type and use

displayable

Displayable status (Ikomia Studio)

name

I/O name

source_file_path

Path to the source file used as workflow input (if any)

Details

__init__((object)arg1) None
__init__( (object)self) -> None :

Default constructor

__init__( (object)arg1, (CSemanticSegmentationIO)arg2) -> None :

Copy constructor

from_json((CSemanticSegmentationIO)self, (str)jsonStr) None :

Set input/output data from JSON formatted string.

Args:

str: data as JSON formatted string

from_json( (CSemanticSegmentationIO)self, (str)jsonStr) -> None

get_mask((CSemanticSegmentationIO)self) object :

Get labelled image (ie graylevel) where each pixel has a specific value corresponding to its class. You can find the correspondence between pixel value and class name with ikomia.dataprocess.pydataprocess.CSemanticIO.get_class_names().

Returns:

grayscale mask

Return type:

Numpy array

get_class_names((CSemanticSegmentationIO)self) object :

Get class names list associated with the semantic mask. Class index in the list corresponds to the pixel value in the mask.

Returns:

class names

Return type:

list of str

get_colors((CSemanticSegmentationIO)self) object :

Get colors associated with class names.

Returns:

colors as [r, g, b] list

Return type:

list of int list

get_polygons((CSemanticSegmentationIO)self) object :

Get polygons of connected components extracted from segmentation mask.

Returns:

list of CGraphicsItem based objects

is_data_available((CSemanticSegmentationIO)self) bool :

See is_data_available().

is_data_available( (CSemanticSegmentationIO)self) -> bool

load((CSemanticSegmentationIO)self, (str)path) None :

Load instance segmentation input/output for JSON file.

Args:

path (str): path to JSON file

load( (CSemanticSegmentationIO)self, (str)path) -> None

save((CSemanticSegmentationIO)self, (str)path) None :

Save instance segmentation input/output to JSON file.

Args:

path (str): path to JSON file

save( (CSemanticSegmentationIO)self, (str)path) -> None

set_class_names((CSemanticSegmentationIO)self, (object)names) None :

Set class names associated with segmentation mask. If colors are not defined, random colors are automatically generated.

Parameters:

names (list of str) – class names, index in the list must match the pixel value in the mask

set_class_colors((CSemanticSegmentationIO)self, (object)colors) None :

Set class colors associated with segmentation mask. Sizes of names and colors must be equal.

Parameters:

colors (list of list of int) – colors as [r, g, b] list

set_mask((CSemanticSegmentationIO)self, (object)mask) None :

Set the mask of the semantic segmentation output.

Parameters:

mask (numpy array) – segmentation mask

to_json((CSemanticSegmentationIO)self) str :
Return input/output data in JSON formatted string (compact mode and image encoded as JPEG).

Returns:

string: JSON formatted string

to_json( (CSemanticSegmentationIO)self) -> str

to_json( (CSemanticSegmentationIO)self, (object)options) -> str :

Return input/output data in JSON formatted string. JSON format options can be set, possible values are:

  • [‘json_format’, ‘compact’] (default)

  • [‘json_format’, ‘indented’]

  • [‘image_format’, ‘jpg’](for the mask - default)

  • [‘image_format’, ‘png’]

Args:

list of str: format-specific options encoded as pairs [option_name, option_value]

Returns:

string: JSON formatted string

to_json( (CSemanticSegmentationIO)self, (object)options) -> str