Python API

Client

class hasty.Client(api_key, base_url='https://api.hasty.ai')

Client for Hasty API

__init__(api_key, base_url='https://api.hasty.ai')

Initialize the client

api_key

Your API key

get_workspaces()

Returns the list of workspaces that the user can have an access to :returns: A list of Workspace objects.

get_projects()

Returns the list of projects :returns: A list of Project objects.

get_project(project_id)

Returns project Project by id

Parameters

project_id (str) – Project id

create_project(workspace: Union[str, Workspace], name: str, description: Optional[str] = None) → Project

Creates new project Project

Parameters

  • workspace (Workspace, str) – Workspace object or id which the project should belongs to

  • name (str) – Name of the project

  • description (str, optional) – Project description

Project

class hasty.Project(requester, data, obj_params=None)
property id

type: string

property name

type: string

property description

type: string

property workspace_id

type: string

edit(name, description)

Edits projects properties

Parameters

  • name (str) – Name of the project

  • description (str, optional) – Project description

delete()

Removes project

get_datasets()

Returns projects datasets Dataset objects.

get_dataset(dataset_id: str)

Get dataset by id, returns ~hasty.Dataset object

Parameters

dataset_id (str) – Dataset id

create_dataset(name: str, norder: float = 0)

Creates a new dataset, returns ~hasty.Dataset object

Parameters

  • name (str) – Name of the dataset

  • norder (float, optional) – Order in the list

get_images(dataset=None, image_status=None)

Retrieves the list of projects images.

Parameters

  • dataset (str, ~hasty.Dataset, list of str, list of ~hasty.Dataset) – filter images by dataset

  • image_status (str, list of str) –

    Filters images by status, valid values are:

    • ”NEW”

    • ”DONE”,

    • ”SKIPPED”

    • ”IN PROGRESS”

    • ”TO REVIEW”

    • ”AUTO-LABELLED”

get_image(image_id)

Retrieves the image by its id.

Parameters

image_id (str) – Image ID

upload_from_file(dataset, filepath, external_id: Optional[str] = None)

Uploads image from the given filepath

Parameters

  • dataset (~hasty.Dataset, str) – Dataset object or id that the image should belongs to

  • filepath (str) – Local path

  • external_id (str) – External ID (optional)

upload_from_url(dataset: Union[Dataset, str], filename: str, url: str, copy_original: bool = True, external_id: Optional[str] = None)

Uploads image from a given URL

Parameters

  • dataset (~hasty.Dataset, str) – Dataset object or id that the image should belongs to

  • filename (str) – Filename of the image

  • url (str) – Image url

  • copy_original (str) – If True Hasty makes a copy of the image. Default True.

  • external_id (str) – External ID (optional)

get_label_classes()

Get label classes, list of LabelClass objects.

get_label_class(label_class_id: str)

Get label class by id, returns ~hasty.LabelClass object

Parameters

label_class_id (str) – Label class id

create_label_class(name: str, color: Optional[str] = None, class_type: str = 'object', norder: Optional[float] = None, external_id: Optional[str] = None)

Create label class, returns LabelClass object.

Parameters

  • name (str) – Label class name

  • color (str, optional) – Color in HEX format #0f0f0faa

  • class_type (str, optional) – Class type [object or background] (default object)

  • norder (float, optional) – Order in the Hasty tool

  • external_id (str, optional) – External Identifier

get_tag_classes()

Get tag classes, list of TagClass objects.

get_tag_class(tag_class_id: str)

Get tag class by id, returns ~hasty.TagClass object

Parameters

tag_class_id (str) – Tag class id

create_tag_class(name: str, norder: Optional[float] = None)

Create tag class, returns TagClass object.

Parameters

  • name (str) – Tag class name

  • norder (float, optional) – Order in the Hasty tool

get_attributes()

Get label classes, list of Attribute objects.

create_attribute(name: str, attribute_type: str, description: Optional[str] = None, norder: Optional[float] = None, values: Optional[List[str]] = None)

Create attribute, returns Attribute object.

Parameters

  • name (str) – Attribute name

  • attribute_type (str) – Attribute type [‘SELECTION’, ‘MULTIPLE-SELECTION’, ‘TEXT’, ‘INT’, ‘FLOAT’, ‘BOOL’]

  • description (str, optional) – Attrbute description

  • norder (float, optional) – Order in the Hasty tool

  • values (list of str) – List of values for SELECTION and MULTIPLE-SELECTION attribute type

get_attribute_classes()
Get attributes - class mapping. Returns list of dict with a keys:

  • attribute_id - Attribute ID

  • class_id - Class ID

  • attribute_order - Order of attributes within the class

  • class_order - Order of classes within the attribute

set_attribute_classes(attribute_classes)

Set attribute - class mapping

Parameters

  • attribute_classes (dict) –

  • ID (- class_id - Class) –

  • ID –

  • class (- attribute_order - Order of attributes within the) –

  • attribute (- class_order - Order of classes within the) –

delete_attribute_classes(attribute_classes)

Removes attribute - class mapping

Parameters

  • attribute_classes (dict) –

  • ID (- class_id - Class) –

  • ID –

  • class (- attribute_order - Order of attributes within the) –

  • attribute (- class_order - Order of classes within the) –

export(name: str, export_format: str, dataset: Optional[Union[Dataset, str, List[Dataset], List[str]]] = None, image_status: Union[str, List[str]] = 'DONE', sign_urls: bool = False, semantic_format: str = 'gs_asc', labels_order: Optional[List[str]] = None)

Initiate export job. Returns ExportJob object.

Parameters

  • name (str) – Name of the export file

  • export_format (str) – Export format one of [“json_v1.1”, “semantic_png”, “json_coco”, “images”]

  • dataset (~hasty.Dataset, str, list of ~hasty.Dataset, list of str) – List of the datasets to export

  • image_status (list of str, str) – List of the image statuses to export. Default DONE

  • sign_urls (bool) – Whether to generate sign urls for images. Default False

  • semantic_format (str) – Format for semantic_png export. [“gs_desc”, “gs_asc”, “class_color”]

  • labels_order (list of str) – Draw order for semantic_png export [“z_index”, “class_type”, “class_order”]

get_detector()

Returns object detection model. Returns Detector object.

get_instance_segmentor()

Returns instance segmentation model. Returns InstanceSegmentor object.

get_semantic_segmentor()

Returns semantic segmentation model. Returns SemanticSegmentor object.

get_attributer()

Returns active attributer model for the project. Returns Attributer object.

get_automated_labeling_jobs()

Get automated labeling jobs, list of AutomatedLabelingJob objects.

get_automated_labeling_job(job_id: str)

Get automated labeling jobs, list of AutomatedLabelingJob objects.

Parameters

job_id (str) – Automated labeling job id

create_automated_labeling_job(experiment_id: str, confidence_threshold: float = 0.8, max_detections_per_image: int = 100, num_images: int = 0, masker_threshold: float = 0.5, dataset_id: Optional[str] = None)

Create automated labeling job, returns AutomatedLabelingJob object.

Parameters

  • experiment_id (str) – ID of an experiment, that would be used for automated labeling

  • confidence_threshold (float, optional) – Confidence threshold of the predictions that should be applied (default 0.8)

  • max_detections_per_image (int, optional) – Max number of labels that should be created, default 100

  • num_images (int, optional) – Total number of images that should be used for automated labeling (default all)

  • masker_threshold (float, optional) – Threshold for mask head (default 0.5)

  • dataset_id (str, optional) – Filter images by dataset

Dataset

class hasty.Dataset(requester, data, obj_params=None)
property id

type: string

property name

type: string

property project_id

type: string

property norder

type: float

edit(name: str, norder: float)

Edit dataset properties

Parameters

  • name (str) – Name of the dataset

  • norder (float) – Order in the list

delete()

Removes dataset

Image

class hasty.Image(requester, data, obj_params=None)
property id

type: string

property name

type: string

property project_id

type: string

property dataset_id

type: string

property dataset_name

type: string

property width

type: int

property height

type: int

property status

type: string

property public_url

type: string

property external_id

type: string

get_labels()

Returns image labels (list of ~hasty.Label objects)

create_label(label_class: Union[LabelClass, str], bbox: Optional[List[int]] = None, polygon: Optional[List[List[int]]] = None, mask: Optional[List[int]] = None, z_index: Optional[int] = None, external_id: Optional[str] = None)

Create label

Parameters

  • label_class (LabelClass, str) – Label class or label class ID of the label

  • bbox (list of int) – Coordinates of bounding box [x_min, y_min, x_max, y_max]

  • polygon (list) – List of x, y pairs [[x0, y0], [x1, y1], …. [x0, y0]]

  • mask (list of int) – RLE Encoded binary mask, (order right -> down)

  • z_index (int) – Z index of the label. A label with greater value is in front of a label with a lower one.

  • external_id (str, optional) – External Identifier

create_labels(labels)

Create multiple labels. Returns a list of ~hasty.Label objects

Parameters

labels (list of dict) – List of labels, keys: class_id: Label class ID of the label bbox: Coordinates of bounding box [x_min, y_min, x_max, y_max] polygon: List of x, y pairs [[x0, y0], [x1, y1], …. [x0, y0]] mask: RLE Encoded binary mask, (order right -> down) z_index: Z index of the label. external_id: External Identifier

edit_labels(labels)

Updates multiple labels. Returns a list of ~hasty.Label objects

Parameters

labels (list of dict) – List of labels, keys: label_id: Label id class_id: Label class ID of the label bbox: Coordinates of bounding box [x_min, y_min, x_max, y_max] polygon: List of x, y pairs [[x0, y0], [x1, y1], …. [x0, y0]] mask: RLE Encoded binary mask, (order right -> down) z_index: Z index of the label. external_id: External identifier

delete_labels(label_ids: List[str])

Removes multiple labels

Parameters

label_ids (list of str) – Returns list of ids

set_status(status: str)

Set image status

Parameters

status – New status one of [“NEW”, “DONE”, “SKIPPED”, “IN PROGRESS”, “TO REVIEW”]

download(filepath: str)

Downloads image to file

Parameters

filepath (str) – Local path

rename(new_name: str)

Rename image

Parameters

new_name (str) – New image name

move(dataset: Union[Dataset, str])

Move image to another dataset

delete()

Removes image

get_tags()

Returns image tags (list of ~hasty.Tag objects)

add_tags(tags: List[Union[Dict, TagClass]])

Create multiple tags. Returns a list of ~hasty.Tag objects

Parameters

tags (list of dict/~hasty.TagClass) – List of tags, keys: tag_class_id: Tag class ID

delete_tags(tags: List[Union[Dict, Tag, TagClass]])

Removes multiple tags

Parameters

tags (list of dict/~hasty.Tag/~hasty.TagClass) – List of tags, keys: tag_id: Tag ID of the label (optional if tag_class_id is specified) tag_class_id: Tag class ID of the label (optional if id is specified)

LabelClass

class hasty.LabelClass(requester, data, obj_params=None)
property id

type: string

property name

type: string

property project_id

type: string

property color

type: string

property class_type

type: string

property norder

type: float

property external_id

type: string

edit(name, color=None, class_type='object', norder=None, external_id=None)

Edit label class properties

Parameters

  • name (str) – Label class name

  • color (str, optional) – Color in HEX format #0f0f0faa

  • class_type (str, optional) – Class type [object or background] (default object)

  • norder (float, optional) – Order in the Hasty tool

  • external_id (str, optional) – External identifier

delete()

Deletes label class

TagClass

class hasty.TagClass(requester, data, obj_params=None)
property id

type: string

property name

type: string

property project_id

type: string

property norder

type: float

edit(name, norder=None)

Edit tag class properties

Parameters

  • name (str) – Taп class name

  • norder (float, optional) – Order in the Hasty tool

delete()

Deletes tag class

Attribute

class hasty.Attribute(requester, data, obj_params=None)
property id

type: string

property name

type: string

property project_id

type: string

property attribute_type

type: string

property description

type: string

property norder

type: float

property values

type: Dict

edit(name: str, attribute_type: str, description: Optional[str] = None, norder: Optional[float] = None, values: Optional[List[str]] = None)

Edit attribute properties

Parameters

  • Args –

  • name (str) – Attribute name

  • attribute_type (str) – Attribute type [‘SELECTION’, ‘MULTIPLE-SELECTION’, ‘TEXT’, ‘INT’, ‘FLOAT’, ‘BOOL’]

  • description (str, optional) – Attrbute description

  • norder (float, optional) – Order in the Hasty tool

  • values (list of str) – List of values for SELECTION and MULTIPLE-SELECTION attribute type

delete()

Deletes attribute

Label

class hasty.Label(requester, data, obj_params=None)
property id

type: string

property project_id

type: string

property image_id

type: string

property class_id

type: string

property bbox

type: string

property polygon

type: string

property mask

type: string

property z_index

type: string

property external_id

type: string

edit(label_class, bbox=None, polygon=None, mask=None, z_index=None, external_id=None)

Update label properties

Parameters

  • label_class (LabelClass, str) – Label class or label class ID of the label

  • bbox (list of int) – Coordinates of bounding box [x_min, y_min, x_max, y_max]

  • polygon (list) – List of x, y pairs [[x0, y0], [x1, y1], …. [x0, y0]]

  • mask (list of int) – RLE Encoded binary mask, (order right -> down)

  • z_index (float) – Z index of the label. A label with greater value is in front of a label with a lower one.

  • external_id (str, optional) – External Identifier

delete()

Delete label

get_attributes()

Get attributes values, list of LabelAttribute objects.

set_attribute(attribute, value)

Set label attribute

Parameters

  • attribute (~hasty.Attribute, str) –

  • value (str, float, int, bool, list of str) –

Tag

class hasty.Tag(requester, data, obj_params=None)
property id

type: string

property tag_class_id

type: string

property project_id

type: string

property image_id

type: string

property tag_class_name

type: string

Attributer

class hasty.Attributer(requester, data, obj_params=None)
discover_model()

Performs model discovery and loads model to GPU

predict(image_url: Optional[str] = None, image_path: Optional[str] = None, bboxes: Optional[List[List[str]]] = None, confidence_threshold: float = 0.5)

Returns predictions for provided image.

Parameters

  • image_url (str) – Image URL

  • image_path (str) – Path to local image file

  • bboxes (list of list of int) – List of bounding boxes [x_min, y_min, x_max, y_max]

  • confidence_threshold (float) – Confidence threshold [0, 1) (default 0.5)

Returns

  • bbox (list of int): Coordinates of bounding box [x_min, y_min, x_max, y_max]

  • attribute_id (str): Attribute id

  • lov_ids (list of str): List of attribute values

Return type

List of List of dict

Detector

class hasty.Detector(requester, data, obj_params=None)
discover_model()

Performs model discovery and loads model to GPU

predict(image_url: Optional[str] = None, image_path: Optional[str] = None, confidence_threshold: float = 0.5, max_detections_per_image: int = 100)

Returns predictions for provided image.

Parameters

  • image_url (str) – Image URL

  • image_path (str) – Path to local image file

  • confidence_threshold (float) – Confidence threshold [0, 1) (default 0.5)

  • max_detections_per_image (int) – Maximum detections per image (default 100)

Returns

  • bbox (list of int): Coordinates of bounding box [x_min, y_min, x_max, y_max]

  • score (float): Confidence score

  • class_id (str): Label class ID

Return type

List of dict

InstanceSegmentor

class hasty.InstanceSegmentor(requester, data, obj_params=None)
discover_model()

Performs model discovery and loads model to GPU

predict(image_url: Optional[str] = None, image_path: Optional[str] = None, confidence_threshold: float = 0.5, max_detections_per_image: int = 100)

Returns predictions for provided image.

Parameters

  • image_url (str) – Image URL

  • image_path (str) – Path to local image file

  • confidence_threshold (float) – Confidence threshold [0, 1) (default 0.5)

  • max_detections_per_image (int) – Maximum detections per image (default 100)

Returns

  • bbox (list of int): Coordinates of bounding box [x_min, y_min, x_max, y_max]

  • mask (list of int): RLE Encoded binary mask, (order right -> down)

  • score (float): Confidence score

  • class_id (str): Label class ID

Return type

List of dict

SemanticSegmentor

class hasty.SemanticSegmentor(requester, data, obj_params=None)
discover_model()

Performs model discovery and loads model to GPU

predict(image_url: Optional[str] = None, image_path: Optional[str] = None, min_size: float = 0.0)

Returns predictions for provided image.

Parameters

  • image_url (str) – Image URL

  • image_path (str) – Path to local image file

  • min_size (float) – Ignore prediction with an area less then min_size

Returns

  • bbox (list of int): Coordinates of bounding box [x_min, y_min, x_max, y_max]

  • mask (list of int): RLE Encoded binary mask, (order right -> down)

  • class_id (str): Label class ID

Return type

List of dict