Resources

Property

Value

Description

dataset_id

string

Id of the dataset

client_id

string

Id of the workspace the dataset belongs to

dataset_name

string

Name of the dataset

pipeline_status

object

Number of objects/frames completed in each pipeline stage

pipeline_stage_status

object

Number of object/frames for each stage in each status

sensor_config

object

Instance of SensorConfigResource

uploaded_files

array

List of uploaded files

fps

integer

Fps (Frames per second) information for video type datasets

frame_sizes

array

List of number of points in each frame for point cloud datasets

create_timestamp_millis

float

Timestamp at which dataset was created

dataset_format

string

Format of uploaded file for Point Cloud datasets

dataset_type

string

Type of dataset (images, videos, 3d)

labelling_mode

string

Labelling mode for the dataset

• frame_by_frame: for Individual datasets

• label_by_label : for Sequence datasets

tags

array

List of TagResource

files

array

Array of file metadata objects. Each object represents metadata about a file being uploaded as part of the dataset.

processing_status

string

Processing status of the dataset.

files_to_be_uploaded: Dataset created but, dataset files are not yet uploaded, or waiting for the upload to finish.

files_uploaded: Dataset files uploaded. Deepen AI will take a few minutes to preprocess the uploaded dataset files.

preprocessing_error: Preprocess failed. Please check the processing_error_message field for a more detailed description of the error.

files_getting_labelled: Preprocess succeeded, and the files are being labelled by the labellers.

processing_status_message

string

Description of the error in case there is a preprocessing error while preprocessing uploaded dataset files.

status

object

Current labelling status. This has the following fields:

1. finished: Number of files finished labelling and QA and labels ready to download.

2. labelling_in_progress: Number of files getting labelled now.

3. qa_in_progress: Number of files, finished labelling, but waiting for QA.

4. Total: total number of files in the dataset

user_scopes

array

Array of DatasetUserScopeResource

user_group_scopes

array

Array of DatasetUserGroupScopeResource

{ "dataset_id": "dataset_id", "client_id": "client_id", "create_timestamp_millis": 1591397296799, "dataset_format": "json", "dataset_name": "dataset_name", "dataset_type": "3d", "files": [{ "file_size": 18611529.0, "file_type": "application/zip", "resumable_upload_url": "https://www.googleapis.com/upload/storage/v1/b/url_for_file" }], "labelling_mode": "frame_by_frame", "processing_status": "files_getting_labelled", "tags": [], "uploaded_files": ["json_data.zip"], "processing_status_message": "Processing Json Files", "sensor_config": { "primary_sensor_id": "lidar", "sensors": { "lidar": { "content": "path_to_lidar", "sensor_type": "lidar", "calibration": {}, "square_dimensions": [], "sensor_fusion": { "camera_0": { "view_matrix": [ [1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 0, 1], [0, 0, 1, 0] ] } } }, "camera_0": { "content": "path_to_camera_0_img", "sensor_type": "camera", "extension": "jpg", "calibration": {}, "square_dimensions": [], "sensor_fusion": {} } } }, "folder_path": "clent_id/defaultproject/dataset_id", "frame_sizes": [51162, 51156, 51102, 51046, 51068, 51064, 51041, 50953, 51064, 51065, 51065], "pipeline_stage_status": { "Labelling": { "done": 0, "failed": 0, "in_progress": 0, "ready": 0, "waiting": 0 }, "QA": { "done": 0, "failed": 0, "in_progress": 0, "ready": 0, "waiting": 0 } }, "pipeline_status": { "Labelling": 0, "QA": 0, "__ALL_STAGES_DONE": 0, "__TOTAL": 0 } }

file_id

string

File Id of the label resource

label_type

string

Label type of label resource

label_category_id

string

Label category Id of the label resource

label_id

string

Label Id of the label resource

box

array

Array of four float numbers representing the x, y coordinates, x-length, y-length of the box respectively.

polygons

array

Array of polygons. Each polygon is an array of points.

attributes

object

Object containing key value pairs of attribute keys and values.

{ "file_id": "000019.png", "label_category_id": "bus", "label_id": "bus:1", "label_type": "box", "attributes": { "attribute2": "attribute2_value1", "attribute1": "attribute_value1" }, "box": [366, 87, 174, 116], "polygons": [ [[338, 330], [460, 253], [567, 179], [773, 91], [862, 59]] ] }

Property

Value

Description

file_id

string

File Id of the file resource

{ "file_id": "000009.png", }

Property

Value

Description

dataset_id

string

Dataset Id of the notification

file_id

string

File Id of the notification

notification_type

string

Represents the type of notification. Currently, we support two notification types:

DatasetLabellingComplete: Sent after the dataset is completely labelled

FileLabellingComplete: Send after an individual file is labelled.

{ "dataset_id": "testdataset", "notification_type": "DatasetLabellingComplete" }

issue_id

string

Issue Id of the issue resource

status

string

Status of the issue resource

issue_description

string

Description of the issue resource

file_id

string

File Id of the issue resource

author_email

string

Email of author for issue resource

label_category

string

Label category of the issue resource

label_id

string

Label Id of the issue resource

issue_creation_timestamp

Object (date)

Created time for issue resource in millis

region

Object(PolygonResource)

Extruded polygon defining the region for the issue.

{ "issues": [ { "author_email": "[email protected]", "issue_title": "test Issue", "label_id": "test", "issue_creation_timestamp": { "$date": 1551194067161 }, "issue_description": "Issue Description", "issue_id": "6005288", "status": "to do", "label_category": "test", "region": { "extruded_polygon": { "center_z": 1.0, "xy_polygon": [ [ 1.0, 2.0 ], [ 3.0, 4.0 ], [ 5.0, 6.0 ] ], "height": 1.0 } } } ] }

task_id

string

Id of the task resource

status

string

Status of the task resource

client_id

string

Client_id of client

file_id

string

File Id of the task resource

email

string

Assigned user email for task resource

label_category_id

string

Label category of the task resource

sensor_id

string

Sensor Id of the task resource

stage_id

string

Stage Id of the task resource

label_id

string

Label Id of the task resource

label_type

string

Label type of task resource

task_type

string

Task type of task resource. File for a single frame

Label for sequence

dataset_id

string

dataset_id of dataset

previous_task_ids

List

List of task ids to be completed before starting a task

next_task_ids

List

List of task ids to be started after completion of a task

{ "file_tasks": [ { "task_id": "12345", "client_id": "test client", "dataset_id": "test dataset",

"file_id": "test file", "status": "ready", "stage_id": "labelling", "email": "[email protected]",

"next_task_ids": [12345],

"previous_task_ids": [12345678],

} ] }

{ "label_tasks": [ { "task_id": "12345", "client_id": "test client", "dataset_id": "test dataset",

"label_type": "box",

"label_category_id": "car",

"label_id": "car:1",

"sensor_id": "lidar", "status": "ready", "stage_id": "labelling", "email": "[email protected]",

"next_task_ids": [12345],

"previous_task_ids": [12345678],

} ] }

client_id

string

clientId of the viewer

create_timestamp_millis

long

Created timestamp millis of viewer

dataset_id

string

datasetId of the viewer

jwt_token

string

Access token

viewer_id

string

viewerId of viewer

launching_frame_index

int

Frame id of viewer

title

string

Name of viewer

enable_camera_view

boolean

Flag to show camera

expiry_timestamp_millis

long

End timestamp millis of viewer

deletion_status

string

Deletion status of viewer

created_by

string

User created viewer

{ "client_id": "testclient",

"dataset_id": "testdataset",

"jwt_token": "xtlz1235",

"viewer_id": "1234567",

"create_timestamp_millis": 100000000000,

"title": "testviewer",

"launching_frame_index": 1,

"enable_camera_view": true,

"expiry_timestamp_millis": 100000000000,

"created_by": "[email protected]"

}

center_z

float

Z value of center for the extruded polygon

xy_polygon

list(list(float))

List of xy points for the polygon. First point is the x value and second is the y value.

height

float

Height of the polygon

{ "extruded_polygon": { "center_z": 1.0, "xy_polygon":[ [1.0,2.0], [3.0,4.0], [5.0,6.0] ], "height":1.0 } }

stage_id

string

Id of the pipeline stage

can_edit

boolean

Flag representing the editability of labels present in this stage.

{ "stage_id": "Labelling", "can_edit": "true" }

dataset_id

string

Id of the dataset

client_id

string

Id of the client

created_email

string

Email of author for labelling profile resource

created_timestamp_millis

long

Timestamp during creation

features

Object

Object with keys as label types (‘box’, ‘3d_bbox’, ‘polygon’, ‘lane’ etc) and value of type FeaturesResource

instructions

Object

​

notification_url

string

​

pipeline_spec

Object

Pipeline stages

profile_id

string

Id of profile

profile_type

string

Type of profile, e.g : dataset

updated_email

string

Email of the user who modifies it

updated_timestamp_millis

long

Timestamp during modification

{ "dataset_id" : "datset_id", "client_id" : "client_id", "created_email" : "[email protected]", "created_timestamp_millis" : 1590037884298, "features" : { "box" : { "attributes" : {}, "label_category_ids" : [] }, "lane" : { "attributes" : {}, "label_category_ids" : [] }, "polygon" : { "attributes" : {}, "label_category_ids" : [] }, "point" : { "attributes" : {}, "label_category_ids" : [] }, "3d_bbox" : { "attributes" : {}, "label_category_ids" : [ "car" ], "label_category_default_dimensions" : { "car" : { "width" : 2.25, "height" : 2.25, "length" : 2.25 } } }, "3d_polyline" : { "attributes" : {}, "label_category_ids" : [] }, "3d_polygon" : { "attributes" : {}, "label_category_ids" : [] }, "3d_point" : { "attributes" : {}, "label_category_ids" : [] }, "3d_instance_point" : { "attributes" : {}, "label_category_ids" : [] } }, "instructions" : { "text" : "" }, "notification_url" : "", "pipeline_spec" : [ { "stage_id" : "Labelling", "can_edit" : true }, { "stage_id" : "QA", "can_edit" : false } ], "profile_id" : "profile_id", "profile_type" : "dataset", "updated_email" : "[email protected]", "updated_timestamp_millis" : 1590038192070 }

tags : ["project: testDeepenProject", "testtag"]

email

string

Email of the user

scopes

array

Array of user scopes

{ "email" : "[email protected]", "scopes" : ["scope1", "scope2"] }

user_group_id

string

Id of the user group

scopes

array

Array of user scopes

{ "user_group_id" : "asdfrtfdv", "scopes" : ["scope1", "scope2"] }

primary_sensor_id

string

Id of the primary sensor

sensors

object

Object containing different sensor ids as keys with value as SensorConfigSensorDetailsResource

{ "primary_sensor_id": "lidar", "sensors": { "lidar": { "content": "path_to_lidar", "sensor_type": "lidar", "sensor_fusion": { "camera_0": { "view_matrix": [ [1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 0, 1], [0, 0, 1, 0] ] } } }, "camera_0": { "content": "path_to_camera_0_img", "sensor_type": "camera", "extension": "jpg" } } }

content

string

Relative path to the directory containing sensor data

sensor_type

string

Type of sensor.

• lidar

• camera

sensor_fusion

object

Object containing each other sensor id as key and the view matrix as value. View matrix is the matrix used to transform the points from the current sensor coordinates to the other sensor coordinates.

{ "content": "path_to_lidar", "sensor_type": "lidar", "sensor_fusion": { "camera_0": { "view_matrix": [ [1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 0, 1], [0, 0, 1, 0] ] } } }

user_group_id

string

Id of the user group

client_id

string

Id of the client user group belongs to

create_email

string

Email of the user who created the user group

create_timestamp_millis

int

Timestamp in milliseconds for the time at which the user group was created

emails

array

Array of user emails belonging to the group

update_timestamp_millis

int

Timestamp in milliseconds for the time at which the user group was updated

user_group_name

string

Name of the User Group

{ "user_group_id" : "user_group_id", "client_id" : "client_id", "create_email" : "[email protected]", "create_timestamp_millis" : 1595484956292, "emails" : [ "[email protected]", "[email protected]" ], "update_timestamp_millis" : 1595484956292, "user_group_name" : "TestUserGroup" }

label_category_ids

List

List of label category ids

attributes

Object

Object with key as attribute name and value of type AttributesResource

label_category_attributes_config

Object

Object with key as label category name and value of type AttributesConfigResource

label_category_colors

Object

Object with key as attribute name and value as list of integer RGBA values

label_category_default_dimensions

Object

Object with key as label category name and value as DefaultDimensionResource for 3d_bbox label type.

{ "box" : { "attributes" : {}, "label_category_ids" : [ "Person", "VehicleOther", "Tank", "Gator", "PickupTruck" ] }, "lane" : { "attributes" : {}, "label_category_ids" : [] }, "polygon" : { "attributes" : {}, "label_category_ids" : [ "Car", "Road", "Person", "Truck", "Bicycle" ] }, "point" : { "attributes" : {}, "label_category_ids" : [] }, "3d_bbox" : { "attributes" : { "direction" : { "attribute_values_array" : [ "same", "opposite" ] }, "occluded" : { "attribute_values_array" : [ "yes", "no" ], } }, "label_category_ids" : [ "Trailer", "LargeVehicle_Bus", "LargeVehicle_Truck", "Human", "Car", ], "label_category_default_dimensions" : { "Trailer" : { "width" : 2.25, "height" : 2.25, "length" : 2.25 }, "LargeVehicle_Bus" : { "width" : 2.25, "height" : 2.25, "length" : 2.25 }, "Car" : { "width" : 2, "height" : 1, "length" : 4 } }, "label_category_attributes_config" : { "Car" : { "color" : { "attribute_values_array" : [ "red", "black", "blue", "white", "grey", "other" ] } } } }, "3d_polyline" : { "attributes" : {}, "label_category_ids" : [] }, "3d_polygon" : { "attributes" : {}, "label_category_ids" : [] }, "3d_point" : { "attributes" : {}, "label_category_ids" : [ "Building", "Road", "Sidewalk", "Vegetation", "Pedestrian" ] }, "3d_instance_point" : { "attributes" : {}, "label_category_ids" : [] } }

attribute_values_array

List

List of attribute values

{ "attribute_values_array" : [ "yes", "no" ] }

[attribute name]

Object

Object with attribute name as key and AttrbutesResource as value

{ "Car" : { "color" : { "attribute_values_array" : [ "red", "black", "blue", "white", "grey", "other" ] } } } }

width

float

Float value depicting default width of the bounding box

height

float

Float value depicting default height of the bounding box

length

float

Float value depicting default length of the bounding box

{ "width" : 2.25, "height" : 2.25, "length" : 2.25 }