Project - Encord

Project Objects

class Project()

Access project related data and manipulate the project.

project_hash

@property
def project_hash() -> str

Get the project hash (i.e. the Project ID).

status

@property
def status() -> ProjectStatus

Get the status of the project.

title

@property
def title() -> str

Get the title of the project.

description

@property
def description() -> str

Get the description of the project.

created_at

@property
def created_at() -> datetime.datetime

Get the time the project was created at.

last_edited_at

@property
def last_edited_at() -> datetime.datetime

Get the time the project was last edited at.

ontology

@property
@deprecated(version="0.1.95", alternative=".ontology_structure")
def ontology() -> Dict[str, Any]

Get the ontology of the project. DEPRECATED: Prefer using the :meth:encord.Project.ontology_structure method. This method returns the same structure as :meth:encord.Project.ontology_structure, just in raw python dictionary format.

ontology_hash

@property
def ontology_hash() -> str

Get the ontology hash of the project’s ontology.

ontology_structure

@property
def ontology_structure() -> OntologyStructure

Get the ontology structure of the project’s ontology.

user_role

@property
def user_role() -> Optional[ProjectUserRole]

Get the current user’s role in the project. This may return None if the user is an organizational admin and has accessed the project e.g. using include_org_access=True of :meth:encord.user_client.UserClient.list_projects.

source_projects

@property
def source_projects() -> Optional[List[str]]

Get the source projects for a Training project. Returns None for non-Training projects.

datasets

@property
@deprecated(version="0.1.117", alternative=".list_datasets")
def datasets() -> List[Dict[str, Any]]

DEPRECATED: Prefer using the :meth:encord.project.list_datasets class to work with the data. Get the info about datasets associated with this project.

project_type

@property
def project_type() -> ProjectType

Get the project type.

label_rows

@property
@deprecated(version="0.1.104", alternative=".list_label_rows_v2")
def label_rows() -> Dict

Get the label rows. DEPRECATED: Prefer using :meth:list_label_rows_v2() method and :meth:LabelRowV2 class to work with the data. .. code:: from encord.orm.label_row import LabelRowMetadata project = user_client.get_project(“[project_hash]”) label_rows = LabelRowMetadata.from_list(project.label_rows)

refetch_data

def refetch_data() -> None

The Project class will only fetch its properties once. Use this function if you suspect the state of those properties to be dirty.

refetch_ontology

def refetch_ontology() -> None

Update the ontology for the project to reflect changes on the backend.

get_project

def get_project() -> OrmProject

This function is exposed for convenience. You are encouraged to use the property accessors instead.

workflow

@property
def workflow() -> Workflow

Get the workflow of the project. Available only for workflow projects.

list_label_rows_v2

def list_label_rows_v2(
        data_hashes: Optional[Union[List[str], List[UUID]]] = None,
        label_hashes: Optional[Union[List[str], List[UUID]]] = None,
        edited_before: Optional[Union[str, datetime.datetime]] = None,
        edited_after: Optional[Union[str, datetime.datetime]] = None,
        label_statuses: Optional[List[AnnotationTaskStatus]] = None,
        shadow_data_state: Optional[ShadowDataState] = None,
        data_title_eq: Optional[str] = None,
        data_title_like: Optional[str] = None,
        workflow_graph_node_title_eq: Optional[str] = None,
        workflow_graph_node_title_like: Optional[str] = None,
        include_workflow_graph_node: bool = True,
        include_client_metadata: bool = False,
        include_images_data: bool = False,
        include_children: bool = False,
        include_all_label_branches: bool = False,
        branch_name: Optional[str] = None) -> List[LabelRowV2]

List label rows with various filtering options. Arguments:

data_hashes - List of data hashes to filter by.
label_hashes - List of label hashes to filter by.
edited_before - Optionally filter to only rows last edited before the specified time.
edited_after - Optionally filter to only rows last edited after the specified time.
label_statuses - Optionally filter to only those label rows that have one of the specified :class:~encord.orm.label_row.AnnotationTaskStatuses.
shadow_data_state - Optionally filter by data type in Benchmark QA projects. See :class:~encord.orm.label_row.ShadowDataState.
data_title_eq - Optionally filter by exact title match.
data_title_like - Optionally filter by fuzzy title match; SQL syntax.
workflow_graph_node_title_eq - Optionally filter by exact match with workflow node title.
workflow_graph_node_title_like - Optionally filter by fuzzy match with workflow node title; SQL syntax.
include_workflow_graph_node - Include workflow graph node metadata in all the results. True by default.
include_client_metadata - Optionally include client metadata into the result of this query.
include_images_data - Optionally include image group metadata into the result of this query.
include_children - Optionally include data group children rows into the result of this query.
include_all_label_branches - Optionally include all label branches. They will be included as separate label row objects.
branch_name - Optionally specify a branch name. A branch name cannot be specified if include_all_label_branches is set to True

Returns: A list of :class:~encord.objects.LabelRowV2 instances for all the matching label rows.

add_users

def add_users(user_emails: List[str],
              user_role: ProjectUserRole) -> List[ProjectUser]

Add users to the project. If the user already exists in the Project, this operation succeeds but the user_role remains unchanged. The existing user_role is reflected in the ProjectUser instance returned. Arguments:

user_emails - List of user emails to be added.
user_role - The user role to assign to all users.

Returns:

List[ProjectUser] - A list of ProjectUser objects representing the added users.

Raises:

AuthorisationError - If the project API key is invalid.
ResourceNotFoundError - If no project exists by the specified project EntityId.
UnknownError - If an error occurs while adding the users to the project.

list_users

def list_users() -> Iterable[ProjectUser]

List all users that have access to the project. Returns:

Iterable[ProjectUser] - An iterable of ProjectUser objects.

list_groups

def list_groups() -> Iterable[ProjectGroup]

List all groups that have access to a particular project. Returns:

Iterable[ProjectGroup] - An iterable of ProjectGroup objects.

add_group

def add_group(group_hash: Union[List[UUID], UUID], user_role: ProjectUserRole)

Add a group to the project. Arguments:

group_hash - List of group hashes or a single group hash to be added.
user_role - User role that the group will be given.

Returns: None

remove_group

def remove_group(group_hash: Union[List[UUID], UUID])

Remove a group from the project. Arguments:

group_hash - List of group hashes or a single group hash to be removed.

Returns: None

copy_project

def copy_project(copy_datasets: Union[bool, CopyDatasetOptions] = False,
                 copy_collaborators=False,
                 copy_models=False,
                 *,
                 copy_labels: Optional[CopyLabelsOptions] = None,
                 new_title: Optional[str] = None,
                 new_description: Optional[str] = None) -> str

Copy the current project into a new one with copied contents including settings, datasets, and users. Labels and models are optional. Arguments:

copy_datasets - If True, the datasets of the existing project are copied over, and new tasks are created from those datasets.
copy_collaborators - If True, all users of the existing project are copied over with their current roles. If label and/or annotator reviewer mapping is set, this will also be copied over.
copy_models - If True, all models with their training information will be copied into the new project.
copy_labels - Options for copying labels, defined in CopyLabelsOptions.
new_title - When provided, will be used as the title for the new project.
new_description - When provided, will be used as the description for the new project.

Returns:

str - The EntityId of the newly created project.

Raises:

AuthorisationError - If the project API key is invalid.
ResourceNotFoundError - If no project exists by the specified project EntityId.
UnknownError - If an error occurs while copying the project.

add_datasets

def add_datasets(dataset_hashes: List[str]) -> bool

Add datasets to the project. Arguments:

dataset_hashes - List of dataset hashes of the datasets to be added.

Returns:

bool - True if the datasets were successfully added, False otherwise.

Raises:

AuthenticationError - If the project API key is invalid.
AuthorisationError - If access to the specified resource is restricted.
ResourceNotFoundError - If one or more datasets don’t exist by the specified dataset_hashes.
UnknownError - If an error occurs while adding the datasets to the project.
OperationNotAllowed - If the write operation is not allowed by the API key.

remove_datasets

def remove_datasets(dataset_hashes: List[str]) -> bool

Remove datasets from the project. Arguments:

dataset_hashes - List of dataset hashes of the datasets to be removed.

Returns:

bool - True if the datasets were successfully removed, False otherwise.

Raises:

AuthenticationError - If the project API key is invalid.
AuthorisationError - If access to the specified resource is restricted.
ResourceNotFoundError - If no dataset exists by the specified dataset_hash (uid).
UnknownError - If an error occurs while removing the datasets from the project.
OperationNotAllowed - If the operation is not allowed by the API key.

get_project_ontology

@deprecated(version="0.1.95", alternative=".ontology_structure")
def get_project_ontology() -> LegacyOntology

DEPRECATED: Prefer using the ontology_structure property accessor instead. Returns:

LegacyOntology - The project’s ontology.

add_object

@deprecated("0.1.102", alternative="encord.ontology.Ontology class")
def add_object(name: str, shape: ObjectShape) -> bool

DEPRECATED: Prefer using :class:Ontology [encord.ontology.Ontology] to manipulate ontology. Add an object to an ontology. ATTENTION: This legacy method will affect all the projects sharing the same ontology. Arguments:

name - The name of the object.
shape - The shape of the object. (BOUNDING_BOX, POLYGON, POLYLINE, or KEY_POINT)

Returns:

bool - True if the object was added successfully, False otherwise.

Raises:

AuthenticationError - If the project API key is invalid.
AuthorisationError - If access to the specified resource is restricted.
UnknownError - If an error occurs while adding the object to the project ontology.
OperationNotAllowed - If the operation is not allowed by the API key.
ValueError - If invalid arguments are supplied in the function call.

add_classification

@deprecated("0.1.102", alternative="encord.ontology.Ontology class")
def add_classification(name: str,
                       classification_type: ClassificationType,
                       required: bool,
                       options: Optional[Iterable[str]] = None)

DEPRECATED: Prefer using :class:Ontology encord.ontology.Ontology to manipulate ontology. Add a classification to an ontology. ATTENTION: This legacy method will affect all the projects sharing the same ontology. Arguments:

name - The name of the classification.
classification_type - The classification type (RADIO, TEXT, or CHECKLIST).
required - Whether this classification is required by the annotator.
options - The list of options for the classification (to be set to None for texts).

Raises:

AuthenticationError - If the project API key is invalid.
AuthorisationError - If access to the specified resource is restricted.
UnknownError - If an error occurs while adding the classification to the project ontology.
OperationNotAllowed - If the operation is not allowed by the API key.
ValueError - If invalid arguments are supplied in the function call.

object_interpolation

def object_interpolation(key_frames, objects_to_interpolate)

Run object interpolation algorithm on project labels (requires an editor ontology and feature uids). Interpolation is supported for bounding box, polygon, and keypoint. Arguments:

key_frames - Labels for frames to be interpolated. Key frames are consumed in the form::

    {
        "[frame_number]": {
            "objects": [
                {
                    "objectHash": "[object_hash]",
                    "featureHash": "[feature_hash]",
                    "polygon": {
                        "0": { "x": x1, "y": y1, },
                        "1": { "x": x2, "y": y2, },
                        # ...,
                    }
                },
                # ...
            ]
        },
        # ...,
    }

objects_to_interpolate - List of object uids (hashes) of objects to interpolate.

Returns:

dict - Full set of filled frames including interpolated objects.

Raises:

AuthenticationError - If the project API key is invalid.
AuthorisationError - If access to the specified resource is restricted.
UnknownError - If an error occurs while running interpolation.

get_data

def get_data(
    data_hash: str,
    get_signed_url: bool = False
) -> Tuple[Optional[Video], Optional[List[Image]]]

Retrieve information about a video or image group. Arguments:

data_hash - The uid of the data object.
get_signed_url - Optionally return signed URLs for timed public access to that resource (default False).

Returns: A tuple consisting of the video (if it exists) and a list of individual images (if they exist). Raises:

AuthenticationError - If the project API key is invalid.
AuthorisationError - If access to the specified resource is restricted.
UnknownError - If an error occurs while retrieving the object.

get_label_logs

def get_label_logs(user_hash: Optional[str] = None,
                   data_hash: Optional[str] = None,
                   from_unix_seconds: Optional[int] = None,
                   to_unix_seconds: Optional[int] = None,
                   after: Optional[datetime.datetime] = None,
                   before: Optional[datetime.datetime] = None,
                   user_email: Optional[str] = None) -> List[LabelLog]

Get label logs, which represent the actions taken in the UI to create labels. All arguments can be left as None if no filtering should be applied. Arguments:

user_hash - Filter the label logs by the user.
data_hash - Filter the label logs by the data_hash.
from_unix_seconds - Filter the label logs to only include labels after this timestamp. Deprecated: use parameter after instead.
to_unix_seconds - Filter the label logs to only include labels before this timestamp. Deprecated: use parameter before instead.
after - Filter the label logs to only include labels after the specified time.
before - Filter the label logs to only include labels before the specified time.
user_email - Filter by the annotator email.

Returns: List of label logs.

get_editor_logs

def get_editor_logs(
        start_time: datetime.datetime,
        end_time: datetime.datetime,
        action: Optional[str] = None,
        actor_user_email: Optional[str] = None,
        workflow_stage_id: Optional[UUID] = None,
        data_unit_id: Optional[UUID] = None) -> Iterator[EditorLog]

Get editor logs, represents the actions taken in the Editor UI. The start_time and end_time parameters are required. The maximum time range is 30 days. Arguments:

action - Filter the editor logs by action.
actor_user_email - Filter the editor logs by the user email.
data_unit_id - Filter the editor logs by the data id (data_hash).
workflow_stage_id - Filter the editor logs by the workflow stage id.
end_time - Filter the editor logs to only include logs before the specified time.
start_time - Filter the editor logs to only include logs after the specified time.

Returns: An iterator on the editor logs.

get_cloud_integrations

@deprecated(version="0.1.154",
            alternative="EncordUserClient.get_cloud_integrations")
def get_cloud_integrations() -> List[CloudIntegration]

Get the list of cloud integrations. Returns: List of CloudIntegration objects.

list_label_rows

@deprecated(version="0.1.104", alternative=".list_label_rows_v2")
def list_label_rows(
        edited_before: Optional[Union[str, datetime.datetime]] = None,
        edited_after: Optional[Union[str, datetime.datetime]] = None,
        label_statuses: Optional[List[AnnotationTaskStatus]] = None,
        shadow_data_state: Optional[ShadowDataState] = None,
        *,
        include_uninitialised_labels=False,
        label_hashes: Optional[List[str]] = None,
        data_hashes: Optional[List[str]] = None) -> List[LabelRowMetadata]

DEPRECATED - use list_label_rows_v2 to manage label rows instead. Arguments:

edited_before - Optionally filter to only rows last edited before the specified time.
edited_after - Optionally filter to only rows last edited after the specified time.
label_statuses - Optionally filter to only those label rows that have one of the specified AnnotationTaskStatus.
shadow_data_state - Optionally filter by data type in Benchmark QA projects. See ShadowDataState.
include_uninitialised_labels - Whether to return only label rows that are “created” and have a label_hash (default). If set to True, this will return all label rows, including those that do not have a label_hash.
data_hashes - List of data hashes to filter by.
label_hashes - List of label hashes to filter by.

Returns: A list of LabelRowMetadata instances for all the matching label rows. Raises:

UnknownError - If an error occurs while retrieving the data.

get_label_row

@deprecated(version="0.1.123", alternative=".list_label_rows_v2")
def get_label_row(uid: str,
                  get_signed_url: bool = True,
                  *,
                  include_object_feature_hashes: Optional[Set[str]] = None,
                  include_classification_feature_hashes: Optional[
                      Set[str]] = None,
                  include_reviews: bool = False) -> LabelRow

DEPRECATED: Prefer using the list_label_rows_v2 function to interact with label rows. Retrieve label row. If you need to retrieve multiple label rows, prefer using get_label_rows instead. Arguments:

uid - A label_hash (uid) string.
get_signed_url - Whether to generate signed urls to the data asset. Generating these should be disabled if the signed urls are not used to speed up the request.
include_object_feature_hashes - If None all the objects will be included. Otherwise, only objects labels will be included of which the feature_hash has been added.
include_classification_feature_hashes - If None all the classifications will be included. Otherwise, only classification labels will be included of which the feature_hash has been added.
include_reviews - Whether to request read only information about the reviews of the label row.

Returns:

LabelRow - A label row instance.

Raises:

AuthenticationError - If the project API key is invalid.
AuthorisationError - If access to the specified resource is restricted.
ResourceNotFoundError - If no label exists by the specified label_hash (uid).
UnknownError - If an error occurs while retrieving the label.
OperationNotAllowed - If the read operation is not allowed by the API key.

get_label_rows

@deprecated(version="0.1.123", alternative=".list_label_rows_v2")
def get_label_rows(uids: List[str],
                   get_signed_url: bool = True,
                   *,
                   include_object_feature_hashes: Optional[Set[str]] = None,
                   include_classification_feature_hashes: Optional[
                       Set[str]] = None,
                   include_reviews: bool = False) -> List[LabelRow]

DEPRECATED: Prefer using the list_label_rows_v2 function to interact with label rows. Retrieve a list of label rows. Duplicates will be dropped. The result will come back in a random order. Arguments:

uids - A list of label_hash (uid).
get_signed_url - Whether to generate signed urls to the data asset. Generating these should be disabled if the signed urls are not used to speed up the request.
include_object_feature_hashes - If None all the objects will be included. Otherwise, only objects labels will be included of which the feature_hash has been added.
include_classification_feature_hashes - If None all the classifications will be included. Otherwise, only classification labels will be included of which the feature_hash has been added.
include_reviews - Whether to request read only information about the reviews of the label row.

Returns: List of LabelRow instances. Raises:

MultiLabelLimitError - If too many labels were requested. Check the error’s maximum_labels_allowed field to read the most up to date error limit.
AuthenticationError - If the project API key is invalid.
AuthorisationError - If access to the specified resource is restricted.
ResourceNotFoundError - If no label exists by the specified label_hash (uid).
UnknownError - If an error occurs while retrieving the label.
OperationNotAllowed - If the read operation is not allowed by the API key.

save_label_row

@deprecated(version="0.1.123", alternative=".list_label_rows_v2")
def save_label_row(uid, label, validate_before_saving: bool = False)

DEPRECATED: Prefer using the list_label_rows_v2 function to interact with label rows. Save an existing label row. If you have a series of frame labels and have not updated answer dictionaries, call the construct_answer_dictionaries utility function to do so prior to saving labels. Arguments:

uid - A label_hash (uid) string.
label - A label row instance.
validate_before_saving - Enable stricter server-side integrity checks. Boolean, False by default.

Returns:

bool - True if the label row is successfully saved, False otherwise.

Raises:

AuthenticationError - If the project API key is invalid.
AuthorisationError - If access to the specified resource is restricted.
ResourceNotFoundError - If no label exists by the specified label_hash (uid).
UnknownError - If an error occurs while saving the label.
OperationNotAllowed - If the write operation is not allowed by the API key.
AnswerDictionaryError - If an object or classification instance is missing in answer dictionaries.
CorruptedLabelError - If a blurb is corrupted (e.g., if the frame labels have more frames than the video).

create_label_row

@deprecated(version="0.1.123", alternative=".list_label_rows_v2")
def create_label_row(uid: str)

DEPRECATED: Prefer using the list_label_rows_v2 function to interact with label rows. Create a label row (for data in a project not previously labeled). Arguments:

uid - The data_hash (uid) of the data unit being labeled. Available in client.get_project().get(‘label_rows’) where label_status is NOT_LABELLED.

Returns:

LabelRow - A label row instance.

Raises:

AuthenticationError - If the project API key is invalid.
AuthorisationError - If access to the specified resource is restricted.
UnknownError - If an error occurs while saving the label.
OperationNotAllowed - If the write operation is not allowed by the API key.
AnswerDictionaryError - If an object or classification instance is missing in answer dictionaries.
CorruptedLabelError - If a blurb is corrupted (e.g., if the frame labels have more frames than the video).
ResourceExistsError - If a label row already exists for this project data. Avoids overriding existing work.

create_bundle

def create_bundle(bundle_size: Optional[int] = None) -> Bundle

Initializes a bundle to reduce the number of network calls performed by the Encord SDK. See the :class:encord.http.bundle.Bundle documentation for more details. Arguments:

bundle_size - maximum number of items bundled. If more actions provided to the bundle, they will be automatically split into separate api calls.

Returns:

Bundle - An instance of the Bundle class.

list_collaborator_timers

@deprecated(version="0.1.157", alternative=".list_time_spent")
def list_collaborator_timers(
        after: datetime.datetime,
        before: Optional[datetime.datetime] = None,
        group_by_data_unit: bool = True) -> Iterable[CollaboratorTimer]

DEPRECATED - Use list_time_spent. list_time_spent provides more comprehensive and accurate information. Provides information about time spent by each collaborator who has worked on the project within a specified range of dates. This endpoint is deprecated and retrieves collaborator timers from the Legacy Performance Dashboards, not the Upgraded Analytics Dashboard. Arguments:

after - The beginning of the period of interest.
before - The end of the period of interest.
group_by_data_unit - If True, time spent by a collaborator for each data unit is provided separately. If False, all time spent in the scope of the project is aggregated together.

Yields:

CollaboratorTimer - Information about the time spent by each collaborator.

list_time_spent

def list_time_spent(
        start: datetime.datetime,
        end: Optional[datetime.datetime] = None,
        workflow_stage_uuid: Union[List[UUID], List[str], UUID, str,
                                   None] = None,
        user_email: Union[List[str], str, None] = None) -> Iterable[TimeSpent]

Get time spent by collaborators on a task per day. If a task spans multiple days, the time spent on each day will be returned separately. Arguments:

start - The beginning of the period of interest.
end - The end of the period of interest.
workflow_stage_uuid - The UUID or list of UUIDs of the workflow stages of interest.
user_email - The email or list of emails of the users of interest.

Returns:

Iterable[TimeSpent] - Information about the time spent by a collaborator on a task per day.

list_datasets

def list_datasets() -> Iterable[ProjectDataset]

List all datasets associated with the project. Returns:

Iterable[ProjectDataset] - An iterable of ProjectDataset instances.

import_coco_labels

def import_coco_labels(labels_dict: Dict[str, Any],
                       category_id_to_feature_hash: Dict[CategoryID, str],
                       image_id_to_frame_index: Dict[ImageID, FrameIndex],
                       branch_name: Optional[str] = None,
                       confidence_field_name: Optional[str] = None) -> None

Import labels in COCO format to an Encord Project. Arguments:

labels_dict Dict[str, Any] - A dictionary in COCO annotation format.
category_id_to_feature_hash Dict[CategoryID, str] - A mapping of category IDs from the COCO data to their corresponding feature hashes in the Project’s Ontology.
image_id_to_frame_index Dict[ImageID, FrameIndex] - A mapping of image IDs to FrameIndex(data_hash, frame_offset), used to locate the corresponding frames in the Encord Project.
branch_name Optional[str] - Optionally specify a branch name. Defaults to the main branch.
confidence_field_name Optional[str] - Optionally specify the name of the confidence field in the COCO annotations. Defaults to assigning 1.0 as confidence value to all annotations.

export_coco_labels

def export_coco_labels(
        label_hashes: Optional[List[str]] = None,
        include_object_feature_hashes: Optional[Set[str]] = None,
        include_classification_feature_hashes: Optional[Set[str]] = None,
        branch_name: Optional[str] = None) -> Dict[str, Any]

Export labels from the project to the COCO format. This method requires the ‘coco’ extra to be installed. Install it using: pip install encord[coco]. Arguments:

label_hashes - List of label hashes to include. If not provided, all label rows will be included.
include_object_feature_hashes - If None, all objects will be included. Otherwise, only objects with the specified feature hashes will be included.
include_classification_feature_hashes - If None, all classifications will be included. Otherwise, only classifications with the specified feature hashes will be included.
branch_name - Optionally specify a branch name. Defaults to the main branch.

Returns: Dict[str, Any]: A dictionary in the COCO format containing the exported labels, including annotations and metadata conforming to COCO standards. The dictionary also includes additional fields specific to Encord, providing supplementary information not defined in the COCO standard. Raises:

ImportError - If the ‘coco’ extra dependencies are not installed.

list_collections

def list_collections(
        collection_uuids: Optional[List[Union[str, UUID]]] = None,
        page_size: Optional[int] = None) -> Iterator[ProjectCollection]

List all collections associated to the project. Arguments:

collection_uuids - The unique identifiers (UUIDs) of the collections to retrieve.
page_size int - Number of items to return per page. Default if not specified is 100. Maximum value is 1000.

Returns: The list of collections which match the given criteria. Raises:

ValueError - If any of the collection uuids is a badly formed UUID. :class:encord.exceptions.AuthorizationError : If the user does not have access to it.

delete_collection

def delete_collection(collection_uuid: Union[str, UUID]) -> None

Delete a project collection by its UUID if it exists. Arguments:

collection_uuid - The unique identifier (UUID) of the collection to delete.

Returns: None Raises:

ValueError - If collection_uuid is a badly formed UUID. :class:encord.exceptions.AuthorizationError : If the user does not have access to it.

create_collection

def create_collection(
    name: str,
    description: str = "",
    collection_type: ProjectCollectionType = ProjectCollectionType.FRAME
) -> ProjectCollection

Create a project collection. Arguments:

name - The name of the collection.
description - The description of the collection.
collection_type - The type of the collection, could be either frame or label.

Returns:

ProjectCollection - Newly created collection.

Raises: :class:encord.exceptions.AuthorizationError : If the user does not have access to the folder.

active_sync

def active_sync() -> None

Sync the associated Active project

active_import

def active_import(project_mode: ActiveProjectMode,
                  *,
                  video_sampling_rate: Optional[float] = None) -> None

Import the associated Active project. Progress in the app Arguments:

project_mode - Active projects can be imported up to a certain stage. Use the ActiveProjectModeEnum to select the stage
video_sampling_rate - Optional[float]: For videos, what’s the sampling rate of frames for analysis

Returns: None

list_filter_presets

def list_filter_presets(
        filter_preset_uuids: Optional[List[Union[str, UUID]]] = None,
        page_size: Optional[int] = None) -> Iterator[ProjectFilterPreset]

List all filter presets associated to the project. Arguments:

filter_preset_uuids - The unique identifiers (UUIDs) of the filter presets to retrieve.
page_size int - Number of items to return per page. Default if not specified is 100. Maximum value is 1000.

Returns: The list of filter presets which match the given criteria. Raises:

ValueError - If any of the filter preset uuids is a badly formed UUID. :class:encord.exceptions.AuthorizationError : If the user does not have access to it.

set_status

def set_status(status: ProjectStatus)

Set the status of the project. Arguments:

status - The new status of the project.

Get Started

General

Index

Ontologies

Projects

Labels

Datasets

DICOM

Active API & SDK

​Project Objects

​project_hash

​status

​title

​description

​created_at

​last_edited_at

​ontology

​ontology_hash

​ontology_structure

​user_role

​source_projects

​datasets

​project_type

​label_rows

​refetch_data

​refetch_ontology

​get_project

​workflow

​list_label_rows_v2

​add_users

​list_users

​list_groups

​add_group

​remove_group

​copy_project

​add_datasets

​remove_datasets

​get_project_ontology

​add_object

​add_classification

​object_interpolation

​get_data

​get_label_logs

​get_editor_logs

​get_cloud_integrations

​list_label_rows

​get_label_row

​get_label_rows

​save_label_row

​create_label_row

​create_bundle

​list_collaborator_timers

​list_time_spent

​list_datasets

​import_coco_labels

​export_coco_labels

​list_collections

​delete_collection

​create_collection

​active_sync

​active_import

​list_filter_presets

​set_status

Project Objects

project_hash

status

title

description

created_at

last_edited_at

ontology

ontology_hash

ontology_structure

user_role

source_projects

datasets

project_type

label_rows

refetch_data

refetch_ontology

get_project

workflow

list_label_rows_v2

add_users

list_users

list_groups

add_group

remove_group

copy_project

add_datasets

remove_datasets

get_project_ontology

add_object

add_classification

object_interpolation

get_data

get_label_logs

get_editor_logs

get_cloud_integrations

list_label_rows

get_label_row

get_label_rows

save_label_row

create_label_row

create_bundle

list_collaborator_timers

list_time_spent

list_datasets

import_coco_labels

export_coco_labels

list_collections

delete_collection

create_collection

active_sync

active_import

list_filter_presets

set_status