CInstanceSegmentationTask¶
- class ikomia.dataprocess.pydataprocess.CInstanceSegmentationTask¶
Base class for instance segmentation task in Computer Vision. It consists in detecting object instances of various classes and compute pixel mask of each instance. Common outputs for such task are bounding boxes and binary masks for each instance and color labelled image for visualization. It defines a task with the following properties:
Inputs:
image (
CImageIO
)graphics (
CGraphicsInput
)
Outputs:
image IO (
CImageIO
): by default source image is forwarded.instance segmentation IO (
CInstanceSegmentationIO
)
Derived from
C2dImageTask
.Import
from ikomia.dataprocess import CInstanceSegmentationTask
Methods
__init__
(arg1)__init__( (object)self) -> None :
add_object
(self, id, type, class_index, ...)Add segmented instance result localized in image through regular bounding box and mask.
get_names
(self)Get class names.
get_results
(self)Get instance segmentation results as a
CInstanceSegmentationIO
instance.get_image_with_graphics
(self)Get visualization image where all extracted information are embedded (graphics items).
get_image_with_mask
(self)Get a visualization image composed by original input image and colored segmentation mask.
Get a visualization image composed by original input image, colored segmentation mask and embedded graphics (object detection).
read_class_names
(self, path)Populate class names from the given text file (one line per class).
set_colors
(self, colors)Set colors associated with class names.
set_names
(self, names)Set class names.
emit_add_sub_progress_steps
(self, count)emit_output_changed
(self)emit_step_progress
(self)See
emit_step_progress()
.Overridden methods
end_task_run
(self)See
end_task_run()
.Inherited methods
add_input
(self, input)Add new input to the task.
add_output
(self, output)Add new output to the task.
apply_graphics_mask
(self, origin, processed, ...)Apply the mask generated from graphics to the result image so that only masked areas seems to be processed.
apply_graphics_mask_to_binary
(self, origin, ...)Apply the mask generated from graphics to the binary source image.
begin_task_run
(self)See
begin_task_run()
.create_input_graphics_mask
(self, index, ...)Generate a binary mask image from the task graphics input at the specified index.
create_graphics_mask
(self, width, height, ...)Generate a binary mask image from the given graphics input object.
execute_actions
(self, action)Method called when a specific action is requested from the associated widget (see
emit_send_process_action()
).forward_input_image
(self, input_index, ...)Forward input image at position input_index to output at position output_index.
get_elapsed_time
(self)Get the time of the last execution in milliseconds.
get_graphics_mask
(self, index)Get the binary mask generated from graphics input at position index.
get_input
(self, index)Get input at position index.
get_input_count
(self)Get the number of inputs.
get_input_data_type
(self, index)Get input data type at position index.
get_inputs
(self)Get the whole list of inputs.
get_output
(self, index)Get output at position index.
get_output_count
(self)Get the number of outputs.
get_output_data_type
(self, index)Get output data type at position index.
get_outputs
(self)Get the whole list of outputs.
get_parameters
(self)Get values of task parameters.
get_progress_steps
(self)See
get_progress_steps()
.global_input_changed
(self, is_new_sequence)graphics_changed
(self)See
graphics_changed()
.is_graphics_changed_listening
(self)Check whether the task is listening to graphics changed event.
is_mask_available
(self, index)Check whether a binary mask from graphics input is available at position index.
parameters_modified
(self)Notify that the task parameters have changed.
remove_input
(self, index)Remove input at the given position.
run
(self)See
run()
.set_action_flag
(self, action, is_enable)Enable or disable the given action.
set_active
(self, is_active)See
set_active()
.set_input
(self, input, index)Set input at position index with the given one.
set_input_data_type
(self, data_type, index)Set the data type for the input at position index.
set_inputs
(self, inputs)Set the whole list of inputs with the given one.
set_output
(self, output, index)Set output at position index with the given one.
set_output_color_map
(self, index, ...)Bind a display color map to an image output.
set_output_data_type
(self, data_type, index)Set the data type for the output at position index.
set_outputs
(self, outputs)Set the whole list of outputs with the given one.
set_parameters
(self, values)Set values of task parameters.
stop
(self)See
stop()
.update_static_outputs
(self)Determine output data type automatically from input data types.
Attributes
name
Task name (must be unique)
type
Main purpose or data type on which the task is dedicated to.
Details
- __init__((object)arg1) None ¶
- __init__( (object)self) -> None :
Default constructor
- __init__( (object)self, (str)name) -> None :
Construct CInstanceSegmentationTask object with the given name.
Args:
name (str): task name, must be unique
- add_object((CInstanceSegmentationTask)self, (int)id, (int)type, (int)class_index, (float)confidence, (float)x, (float)y, (float)width, (float)height, (object)mask) None : ¶
Add segmented instance result localized in image through regular bounding box and mask.
- Parameters:
id (int) – instance identifier
type (int) – segmentation instance type (0:THING - 1:STUFF)
class_index (int) – index of the associated class
confidence (float) – confidence of the prediction
x (float) – left coordinate of object bounding box
y (float) – top coordinate of object bounding box
width (float) – width of object bounding box
height (float) – height of object bounding box
mask (numpy array) – binary mask
- get_names((CInstanceSegmentationTask)self) object : ¶
Get class names. Call
read_class_names()
to populate names from text file.- Returns:
class names
- Return type:
str list
- get_results((CInstanceSegmentationTask)self) CInstanceSegmentationIO : ¶
Get instance segmentation results as a
CInstanceSegmentationIO
instance.- Returns:
semantic segmentation data
- Return type:
- get_image_with_graphics((CInstanceSegmentationTask)self) object : ¶
Get visualization image where all extracted information are embedded (graphics items).
- Returns:
visualization image
- Return type:
2D Numpy array
- get_image_with_mask((CInstanceSegmentationTask)self) object : ¶
Get a visualization image composed by original input image and colored segmentation mask. A transparency factor is applied to see both information.
- Returns:
color mask image
- Return type:
2D numpy array (3 channels)
- get_image_with_mask_and_graphics((CInstanceSegmentationTask)self) object : ¶
Get a visualization image composed by original input image, colored segmentation mask and embedded graphics (object detection). A transparency factor is applied between original image and mask.
- Returns:
visualization image
- Return type:
2D numpy array (3 channels)
- read_class_names((CInstanceSegmentationTask)self, (str)path) None : ¶
Populate class names from the given text file (one line per class).
- Parameters:
path (str) – path to class names definition file
- set_colors((CInstanceSegmentationTask)self, (object)colors) None : ¶
Set colors associated with class names. The given list must have the same size as names list. If not provided, random colors are generated while populating the name list (
read_class_names()
).- Parameters:
list (colors (list of) – r, g, b integer values in range [0, 255])
- set_names((CInstanceSegmentationTask)self, (object)names) None : ¶
Set class names. The function generate associated random colors if none is defined.
- Parameters:
names (list of str)
- emit_add_sub_progress_steps((CInstanceSegmentationTask)self, (int)count) None : ¶
- emit_graphics_context_changed((CInstanceSegmentationTask)self) None : ¶
- emit_output_changed((CInstanceSegmentationTask)self) None : ¶
- emit_step_progress((CInstanceSegmentationTask)self) None : ¶
See
emit_step_progress()
.
- end_task_run((CInstanceSegmentationTask)self) None : ¶
See
end_task_run()
.end_task_run( (CInstanceSegmentationTask)self) -> None