PointcloudAnnotation¶

class PointcloudAnnotation(objects=None, figures=None, tags=None, description='', key=None)[source]¶

Bases: VideoAnnotation

Annotation for a single point cloud item in Supervisely format.

Stores point cloud-level tags, objects and figures (e.g. cuboids) and supports JSON (de)serialization via to_json() / from_json().

Class for creating and using PointcloudAnnotation

Parameters:

objects=None¶: Pointcloud objects collection.
figures=None¶: Pointcloud figures collection.
tags=None¶: Pointcloud tags collection.
description : str¶: Description text
key : uuid.UUID¶: UUID object.

Usage Example:

import supervisely as sly

from supervisely.video_annotation.key_id_map import KeyIdMap

# PointcloudAnnotation example 1
pointcloud_ann = sly.PointcloudAnnotation()
print(pointcloud_ann.to_json())
# Output: {
#     "description": "",
#     "key": "ad97e8a4a8524b8a992d1f083c5e6b00",
#     "tags": [],
#     "objects": [],
#     "figures": []
# }

# PointcloudAnnotation example 2
key_id_map = KeyIdMap()
project_meta_json = api.project.get_meta(pcd_info.project_id)
project_meta = sly.ProjectMeta.from_json(project_meta_json)
ann_json = api.pointcloud.annotation.download(pointcloud_id)
ann = sly.PointcloudAnnotation.from_json(
    data=ann_json,
    project_meta=project_meta,
    key_id_map=key_id_map
)

Methods

`clone`	Makes a copy of PointcloudAnnotation with new fields, if fields are given, otherwise it will use fields of the original PointcloudAnnotation.
`from_json`	Convert pointcloud annotation from json format in PointcloudAnnotation object.
`get_objects_from_figures`	Get PointcloudObjectCollection object from annotation figures.
`is_empty`	Check whether video annotation contains objects or tags, or not.
`key`	Annotation key value.
`load_json_file`	Loads json file and converts it to PointcloudAnnotation.
`to_json`	Convert PointcloudAnnotation to json format.
`validate_figures_bounds`	Not supported for pointcloud

Attributes

`description`	Video description.
`figures`	PointcloudFigure objects.
`frames`	Not supported for pointcloud
`frames_count`	Not supported for pointcloud
`img_size`	Not supported for pointcloud
`objects`	PointcloudObject objects collection.
`tags`	PointcloudTag objects collection.

classmethod from_json(data, project_meta, key_id_map=None)[source]¶

Convert pointcloud annotation from json format in PointcloudAnnotation object.

Parameters:

data : Dict¶: Pointcloud annotation in json format.
project_meta¶: Project metadata.

Returns:

Pointcloud annotation object.

Return type:

PointcloudAnnotation

Usage Example:

import os
from dotenv import load_dotenv

import supervisely as sly
from supervisely.video_annotation.key_id_map import KeyIdMap

# Load secrets and create API object from .env file (recommended)
# Learn more here: https://developer.supervisely.com/getting-started/basics-of-authentication
if sly.is_development():
    load_dotenv(os.path.expanduser("~/supervisely.env"))

api = sly.Api.from_env()

key_id_map = KeyIdMap()
pointcloud_id = pointcloud_id
project_id = 19441
project_meta_json = api.project.get_meta(project_id)
project_meta = sly.ProjectMeta.from_json(project_meta_json)
ann_json = api.pointcloud.annotation.download(pointcloud_id)

ann = sly.PointcloudAnnotation.from_json(
    data=ann_json,
    project_meta=project_meta,
    key_id_map=key_id_map
)

classmethod load_json_file(path, project_meta, key_id_map=None)[source]¶

Loads json file and converts it to PointcloudAnnotation.

Parameters:

path : str¶: Path to the json file.
project_meta¶: Input project metadata.
key_id_map=None¶: Key ID map.

Returns:

Pointcloud annotation object.

Return type:

PointcloudAnnotation

Usage Example:

import os
from dotenv import load_dotenv

import supervisely as sly

# Load secrets and create API object from .env file (recommended)
# Learn more here: https://developer.supervisely.com/getting-started/basics-of-authentication
if sly.is_development():
    load_dotenv(os.path.expanduser("~/supervisely.env"))

api = sly.Api.from_env()

team_name = 'Vehicle Detection'
workspace_name = 'Cities'
project_name =  'London'

team = api.team.get_info_by_name(team_name)
workspace = api.workspace.get_info_by_name(team.id, workspace_name)
project = api.project.get_info_by_name(workspace.id, project_name)

project_meta_json = api.project.get_meta(project_id)
project_meta = sly.ProjectMeta.from_json(project_meta_json)

# Load json file
path = "/home/admin/work/docs/my_dataset/ann/annotation.json"
ann = sly.PointcloudAnnotation.load_json_file(path, project_meta)

clone(objects=None, figures=None, tags=None, description=None)[source]¶

Makes a copy of PointcloudAnnotation with new fields, if fields are given, otherwise it will use fields of the original PointcloudAnnotation.

Parameters:

objects=None¶: Pointcloud objects collection.
figures=None¶: List of pointcloud figures.
tags=None¶: Pointcloud tags collection.
description : str¶: Description text

Returns:

PointcloudAnnotation class object

Usage Example:

import os
from dotenv import load_dotenv

import supervisely as sly
from supervisely.video_annotation.key_id_map import KeyIdMap

# Load secrets and create API object from .env file (recommended)
# Learn more here: https://developer.supervisely.com/getting-started/basics-of-authentication
if sly.is_development():
    load_dotenv(os.path.expanduser("~/supervisely.env"))

api = sly.Api.from_env()

key_id_map = KeyIdMap()
pointcloud_id = 19481098
project_id = 19441
project_meta_json = api.project.get_meta(project_id)
project_meta = sly.ProjectMeta.from_json(project_meta_json)
ann_json = api.pointcloud.annotation.download(pointcloud_id)
ann = sly.PointcloudAnnotation.from_json(
    data=ann_json,
    project_meta=project_meta,
    key_id_map=key_id_map
)

obj_class_car = sly.ObjClass('car', sly.Cuboid)
pointcloud_obj_car = sly.PointcloudObject(obj_class_car)
new_objects = sly.PointcloudObjectCollection([pointcloud_obj_car])

new_ann = ann.clone(objects=new_objects)

print(new_ann.to_json())
# Output: {
#     "description": "",
#     "figures": [],
#     "key": "2cc443272aca4cfa9c4f404614938aa7",
#     "objects": [
#         {
#         "classTitle": "Pole",
#         "createdAt": "2023-03-16T06:38:44.934Z",
#         "key": "eff2ec5e3cda47968f45bc51b36a0dc1",
#         "labelerLogin": "almaz",
#         "tags": [],
#         "updatedAt": "2023-03-16T06:38:44.934Z"
#         },
#         {
#         "classTitle": "Tram",
#         "createdAt": "2023-03-16T06:38:44.934Z",
#         "key": "6baa92e09ceb413ba8fbfcfae74be1c7",
#         "labelerLogin": "almaz",
#         "tags": [],
#         "updatedAt": "2023-03-16T06:38:44.934Z"
#         },
#         {
#         "classTitle": "car",
#         "key": "6b1bced23061437b8ddbcdd267548c96",
#         "tags": []
#         }
#     ],
#     "tags": []
# }

get_objects_from_figures()[source]¶

Get PointcloudObjectCollection object from annotation figures.

Returns:

Pointcloud objects collection from annotation figures.

Return type:

PointcloudObjectCollection

Usage Example:

import supervisely as sly

key_id_map = KeyIdMap()
project_id = 19441
project_meta_json = api.project.get_meta(project_id)
project_meta = sly.ProjectMeta.from_json(project_meta_json)
ann_json = api.pointcloud.annotation.download(pointcloud_id)
ann = sly.PointcloudAnnotation.from_json(
    data=ann_json,
    project_meta=project_meta,
    key_id_map=key_id_map
)

objects = ann.get_objects_from_figures()

is_empty()¶

Check whether video annotation contains objects or tags, or not.

Returns:

True if video annotation is empty, False otherwise.

Return type:

bool

Usage Example:

import os
from dotenv import load_dotenv

import supervisely as sly
from supervisely.video_annotation.key_id_map import KeyIdMap

# Load secrets and create API object from .env file (recommended)
# Learn more here: https://developer.supervisely.com/getting-started/basics-of-authentication
if sly.is_development():
    load_dotenv(os.path.expanduser("~/supervisely.env"))

api = sly.Api.from_env()

project_id = 17208
video_id = 19371139
key_id_map = KeyIdMap()
meta_json = api.project.get_meta(project_id)
meta = sly.ProjectMeta.from_json(meta_json)

ann_json = api.video.annotation.download(video_id)
ann = sly.VideoAnnotation.from_json(ann_json, meta, key_id_map)

print(ann.is_empty()) # False

key()¶

Annotation key value.

Returns:

Key value of annotation object.

Return type:

UUID

Usage Example:

import supervisely as sly

height, width = 500, 700
frames_count = 1
# VideoObjectCollection
obj_class_car = sly.ObjClass('car', sly.Rectangle)
video_obj_car = sly.VideoObject(obj_class_car)
objects = sly.VideoObjectCollection([video_obj_car])
video_ann = sly.VideoAnnotation((height, width), frames_count, objects)

print(video_ann.key())
# Output: 6e5bd622-4d7b-45ee-8bc5-807d5a5e2134

to_json(key_id_map=None)[source]¶

Convert PointcloudAnnotation to json format.

Returns:

PointcloudAnnotation in json format

Return type:

Dict

Usage Example:

import supervisely as sly

pointcloud_ann = sly.PointcloudAnnotation()
print(pointcloud_ann.to_json())
# Output: {
#     "description": "",
#     "key": "ad97e8a4a8524b8a992d1f083c5e6b00",
#     "tags": [],
#     "objects": [],
#     "figures": []
# }

validate_figures_bounds()[source]¶: Not supported for pointcloud

property description : str¶

Video description.

Returns:

Video description

Return type:

str

Usage Example:

import supervisely as sly

height, width = 500, 700
frames_count = 1
descr = 'example'
video_ann = sly.VideoAnnotation((height, width), frames_count, description=descr)
print(video_ann.description) # example

property figures : list[supervisely.pointcloud_annotation.pointcloud_figure.PointcloudFigure]¶

PointcloudFigure objects.

Returns:

List of pointcloud figures from PointcloudAnnotation object.

Return type:

List[PointcloudFigure]

Usage Example:

import os
from dotenv import load_dotenv

import supervisely as sly

# Load secrets and create API object from .env file (recommended)
# Learn more here: https://developer.supervisely.com/getting-started/basics-of-authentication
if sly.is_development():
    load_dotenv(os.path.expanduser("~/supervisely.env"))

api = sly.Api.from_env()

project_id = 19441
project_meta_json = api.project.get_meta(project_id)
project_meta = sly.ProjectMeta.from_json(project_meta_json)

# Load json file
path = "/home/admin/work/docs/my_dataset/ann/annotation.json"
ann = sly.PointcloudAnnotation.load_json_file(path, project_meta)

figures = ann.figures

property frames¶: Not supported for pointcloud

property frames_count¶: Not supported for pointcloud

property img_size¶: Not supported for pointcloud

property objects : supervisely.pointcloud_annotation.pointcloud_object_collection.PointcloudObjectCollection¶

PointcloudObject objects collection.

Returns:

Pointcloud objects collection.

Return type:

PointcloudObjectCollection

Usage Example:

import os
from dotenv import load_dotenv

import supervisely as sly

# Load secrets and create API object from .env file (recommended)
# Learn more here: https://developer.supervisely.com/getting-started/basics-of-authentication
if sly.is_development():
    load_dotenv(os.path.expanduser("~/supervisely.env"))

api = sly.Api.from_env()

project_id = 19441
project_meta_json = api.project.get_meta(project_id)
project_meta = sly.ProjectMeta.from_json(project_meta_json)

# Load json file
path = "/home/admin/work/docs/my_dataset/ann/annotation.json"
ann = sly.PointcloudAnnotation.load_json_file(path, project_meta)

objects = ann.objects

property tags : supervisely.pointcloud_annotation.pointcloud_tag_collection.PointcloudTagCollection¶

PointcloudTag objects collection.

Returns:

Pointcloud tags collection.

Return type:

PointcloudTagCollection

Usage Example:

import os
from dotenv import load_dotenv

import supervisely as sly

# Load secrets and create API object from .env file (recommended)
# Learn more here: https://developer.supervisely.com/getting-started/basics-of-authentication
if sly.is_development():
    load_dotenv(os.path.expanduser("~/supervisely.env"))

api = sly.Api.from_env()

project_id = 19441
project_meta_json = api.project.get_meta(project_id)
project_meta = sly.ProjectMeta.from_json(project_meta_json)

# Load json file
path = "/home/admin/work/docs/my_dataset/ann/annotation.json"
ann = sly.PointcloudAnnotation.load_json_file(path, project_meta)

tags = ann.tags