Labelproject

class Labelproject(object)

This namespace represents each lebeling projects in LABELING AI.

init()

__init__(info, user)

Parmeters

• info (str) : Information about the current labeling project corresponding to the object.

• user (str) : User for creating, modifying, deleting the label project.

Fields

• id : Project id.

• workapp : Project workapp.

• url : DS2 API url information.

• user : User information.

• user_token : User token information.

• labelclasses : Label classes in the labeling projects.

repr()

Returns the Labeling AI's project ID as a printable format.

__repr__()

Return type

• str

delete()

Deletes the project in Labeling AI corresponding to the user object.

delete()

Return type

• None

get_labels()

Get each individual labels as a list form with their IDs.

get_labels()

Return type

• list

get_labelclasses()

Returns self.labelclasses.

get_labelclasses()

Return type

• list

get_labelfiles()

Get each individual image files for labeling as a list form.

get_labelfiles(sorting="created_at", tab="all", count=10, desc=False, searching="", workAssignee=None)

Parmeters

• sorting (str) : Sorting order, such as created_at

• tab (str) : "all" to get all the files.

• count (int) : Number of labelfiles to get.

• desc (Boolean) : Whether to add description or not.

• searching (str) : Specific status of the project.

• workAssignee (str or None) : Set workAssignee as the assignee's email if you want the specific labeling work of the corresponding assignee.

Return type

• list

create_labelclass()

Creates a new label class and returns the new Labelclass object.

create_labelclass(name, color="#000000")

Parameters

• name (str) : Label class's name.

• color (str) : Hex color code of the label.

Return type

• Labelclass

create_labelfile()

Uploads a new image file for labelling and add it to the current labeling project.

create_labelfile(data_file)

Parameters

• data_file (str) : Name of the new file.

Return type

• requests(dict)

create_custom_ai()

Creates a custom AI using the variables such as custom ai type and training column information.

create_custom_ai(custom_ai_type="box", use_class_info={},
                valueForPredictColumnId=None, trainingColumnInfo={})

Parameters

• custom_ai_type (str) : Labeling type, polygon or box.

• use_class_info (dict) : Label class to use for Autolabeling.

• valueForPredictColumnId (int) : Id of the column if the data is in csv format. Otherwise, None.

• trainingColumnInfo (dict) : Info of the training column as a dict.

Return type

• requests(dict)

autolabeling()

Starts auto-labeling with user's preferences as parameters.

autolabeling(amount, ai_type="general", autolabeling_type="box", general_ai_type="person",
        model_id=None, custom_ai_stage=0, preprocessing_ai_type={}, labeling_class=None )

Parameters

• amount (int) : Desired amount of auto-labeling.

• ai_type (str) : Auto-labeling AI type (custom or general or inference).

• autolabeling_type (str) : Auto-labeling type (box or polygon).

• general_ai_type (str) : None(when ai_type is "custom" or "inference") or general AI type(possible_values: 'person', 'animal', 'autonomous_driving', 'face_point detection','people_keypoints').

• model_id (int) : Model's id, as shown at the end of url.

• custom_ai_stage (int)

• preprocessing_ai_type (dict)

• labeling_class (str)

Return type

• requests(dict)

export()

Exports the current labeling project.

export(is_get_image=False)

Parameters

• is_get_image (Boolean) : Whether to get image or not when creating a new Asynctask object.

Return type

• Asynctask object