PointcloudProject¶

class PointcloudProject[source]¶

Bases: supervisely.project.video_project.VideoProject

PointcloudProject is a parent directory for pointcloud datasets. PointcloudProject object is immutable.

Parameters

directory : str: Path to pointcloud project directory.
mode : OpenMode: Determines working mode for the given project.

Usage example

import supervisely as sly
project_path = "/home/admin/work/supervisely/projects/ptc_project"
project = sly.PointcloudProject(project_path, sly.OpenMode.READ)

Methods

`copy_data`	Makes a copy of the `VideoProject`.
`create_dataset`	Creates a subdirectory with given name and all intermediate subdirectories for items and annotations in project directory, and also adds created dataset to the collection of all datasets in the project.
`download`	Download pointcloud project from Supervisely to the given directory.
`download_async`
`download_bin`	Download project to the local directory in binary format.
`get_classes_stats`
`get_item_paths`	rtype `ItemPaths`
`get_train_val_splits_by_count`	Get train and val items information from project by given train and val counts.
`get_train_val_splits_by_dataset`	Get train and val items information from project by given train and val datasets names.
`get_train_val_splits_by_tag`	Get train and val items information from project by given train and val tags names.
`get_url`	Get URL to video datasets list in Supervisely.
`read_single`	rtype `PointcloudProject`
`remove_classes`	Not available for VideoProject class.
`remove_classes_except`	Not available for VideoProject class.
`remove_items_without_both_objects_and_tags`	Not available for VideoProject class.
`remove_items_without_objects`	Not available for VideoProject class.
`remove_items_without_tags`	Not available for VideoProject class.
`set_key_id_map`	Save given KeyIdMap object to project dir in json format.
`set_meta`	Saves given `meta` to project directory in json format.
`to_coco`	Convert Supervisely project to COCO format.
`to_detection_task`	Not available for VideoProject class.
`to_pascal_voc`	Convert Supervisely project to Pascal VOC format.
`to_segmentation_task`	Not available for VideoProject class.
`to_yolo`	Convert Supervisely project to YOLO format.
`upload`	Uploads pointcloud project to Supervisely from the given directory.
`upload_bin`	Uploads project to Supervisely from the given binary file and suitable only for projects downloaded in binary format.
`validate`

Attributes

`datasets`	Project datasets.
`directory`	Path to the project directory.
`key_id_map`
`meta`	Project meta.
`name`	Project name.
`parent_dir`	Project parent directory.
`total_items`	Total number of items in project.
`type`	Project type.

copy_data(dst_directory, dst_name=None, _validate_item=True, _use_hardlink=False)¶

Makes a copy of the VideoProject.

Parameters

dst_directory : str: Path to video project parent directory.
dst_name : str, optional: Video Project name.
_validate_item : bool, optional: Checks input files format.
_use_hardlink : bool, optional: If True creates a hardlink pointing to src named dst, otherwise don’t.

Returns

VideoProject object.

Return type

VideoProject

Usage example

import supervisely as sly
project = sly.VideoProject("/home/admin/work/supervisely/projects/videos_example", sly.OpenMode.READ)
print(project.total_items)
# Output: 6

new_project = project.copy_data("/home/admin/work/supervisely/projects/", "videos_example_copy")
print(new_project.total_items)
# Output: 6

create_dataset(ds_name, ds_path=None)¶

Creates a subdirectory with given name and all intermediate subdirectories for items and annotations in project directory, and also adds created dataset to the collection of all datasets in the project.

Parameters

ds_name : str: Dataset name.

Returns

Dataset object

Return type

Dataset

Usage example

import supervisely as sly
project = sly.Project("/home/admin/work/supervisely/projects/lemons_annotated", sly.OpenMode.READ)

for dataset in project.datasets:
    print(dataset.name)

# Output: ds1
#         ds2

project.create_dataset("ds3")

for dataset in project.datasets:
    print(dataset.name)

# Output: ds1
#         ds2
#         ds3

static download(api, project_id, dest_dir, dataset_ids=None, download_pointclouds=True, download_related_images=True, download_pointclouds_info=False, batch_size=10, log_progress=True, progress_cb=None, **kwargs)[source]¶

Download pointcloud project from Supervisely to the given directory.

Parameters

api : sly.Api: Supervisely API address and token.
project_id : int: Supervisely downloadable project ID.
dest_dir : str: Destination directory.
dataset_ids : List[int], optional: Dataset IDs.
download_pointclouds : bool, optional: Download pointcloud data files or not.
download_related_images : bool, optional: Download related images or not.
download_pointclouds_info : bool, optional: Download pointcloud info .json files or not.
batch_size : int, optional: The number of images in the batch when they are loaded to a host.
log_progress : bool: Show uploading progress bar.
progress_cb : tqdm or callable, optional: Function for tracking download progress.

Returns

None

Return type

NoneType

Usage example

import supervisely as sly

# Local destination Pointcloud Project folder
save_directory = "/home/admin/work/supervisely/source/ptc_project"

# Obtain server address and your api_token from environment variables
# Edit those values if you run this notebook on your own PC
address = os.environ['SERVER_ADDRESS']
token = os.environ['API_TOKEN']

# Initialize API object
api = sly.Api(address, token)
project_id = 8888

# Download Project
sly.PointcloudProject.download(api, project_id, save_directory)
project_fs = sly.PointcloudProject(save_directory, sly.OpenMode.READ)

static download_bin(api, project_id, dest_dir=None, dataset_ids=None, batch_size=100, log_progress=True, progress_cb=None, return_bytesio=False)¶

Download project to the local directory in binary format. Faster than downloading project in the usual way. This type of project download is more suitable for creating local backups. It is also suitable for cases where you don’t need access to individual project files, such as images or annotations.

Binary file contains the following data: - ProjectInfo - ProjectMeta - List of DatasetInfo - List of ImageInfo - Dict of Figures - Dict of AlphaGeometries

Parameters

api : Api: Supervisely API address and token.
project_id : int: Project ID to download.
dest_dir : str, optional: Destination path to local directory.
dataset_ids : list [ int ], optional: Specified list of Dataset IDs which will be downloaded. If you want to download nested datasets, you should specify all nested IDs.
batch_size : int, optional: Size of a downloading batch.
log_progress : bool, optional: Show downloading logs in the output.
progress_cb : tqdm or callable, optional: Function for tracking download progress. Has a higher priority than log_progress.
return_bytesio : bool, optional: If True, returns BytesIO object instead of saving it to the disk.

Returns

Path to the binary file or BytesIO object.

Return type

str or BytesIO

Usage example

import supervisely as sly

# Local destination Project folder
save_directory = "/home/admin/work/supervisely/source/project"

# Obtain server address and your api_token from environment variables
# Edit those values if you run this notebook on your own PC
address = os.environ['SERVER_ADDRESS']
token = os.environ['API_TOKEN']

# Initialize API object
api = sly.Api(address, token)
project_id = 8888

# Download Project in binary format
project_bin_path = sly.Project.download_bin(api, project_id, save_directory)

static get_train_val_splits_by_count(project_dir, train_count, val_count)[source]¶

Get train and val items information from project by given train and val counts.

Parameters

project_dir : str: Path to project directory.
train_count : int: Number of train items.
val_count : int: Number of val items.

Raises

ValueError if total_count != train_count + val_count

Returns

Tuple with lists of train items information and val items information

Return type

Tuple[List[PointcloudItemInfo], List[PointcloudItemInfo]]

Usage example

from supervisely.project.pointcloud_project import PointcloudProject
project_path = "/home/admin/work/supervisely/projects/pointcloud_project"
project = PointcloudProject(project_path, sly.OpenMode.READ)
train_count = 4
val_count = 2
train_items, val_items = project.get_train_val_splits_by_count(project_path, train_count, val_count)

static get_train_val_splits_by_dataset(project_dir, train_datasets, val_datasets)[source]¶

Get train and val items information from project by given train and val datasets names.

Parameters

project_dir : str: Path to project directory.
train_datasets : List[str]: List of train datasets names.
val_datasets : List[str]: List of val datasets names.

Raises

KeyError if dataset name not found in project

Returns

Tuple with lists of train items information and val items information

Return type

Tuple[List[PointcloudItemInfo], List[PointcloudItemInfo]]

Usage example

import supervisely as sly
project_path = "/home/admin/work/supervisely/projects/pointcloud_project"
project = sly.PointcloudProject(project_path, sly.OpenMode.READ)
train_datasets = ['ds1', 'ds2']
val_datasets = ['ds3', 'ds4']
train_items, val_items = project.get_train_val_splits_by_dataset(project_path, train_datasets, val_datasets)

static get_train_val_splits_by_tag(project_dir, train_tag_name, val_tag_name, untagged='ignore')[source]¶

Get train and val items information from project by given train and val tags names.

Parameters

project_dir : str: Path to project directory.
train_tag_name : str: Train tag name.
val_tag_name : str: Val tag name.
untagged : str, optional: Actions in case of absence of train_tag_name and val_tag_name in project.

Raises

ValueError if untagged not in [“ignore”, “train”, “val”]

Returns

Tuple with lists of train items information and val items information

Return type

Tuple[List[PointcloudItemInfo], List[PointcloudItemInfo]]

Usage example

import supervisely as sly
project_path = "/home/admin/work/supervisely/projects/pointcloud_project"
project = sly.PointcloudProject(project_path, sly.OpenMode.READ)
train_tag_name = 'train'
val_tag_name = 'val'
train_items, val_items = project.get_train_val_splits_by_tag(project_path, train_tag_name, val_tag_name)

static get_url(id)¶

Get URL to video datasets list in Supervisely.

Parameters

id : int: VideoProject ID in Supervisely.

Returns

URL to datasets list.

Return type

str

Usage example

from supervisely import VideoProject

project_id = 10093
datasets_link = VideoProject.get_url(project_id)

print(datasets_link)
# Output: "/projects/10093/datasets"

static remove_classes(project_dir, classes_to_remove=None, inplace=False)¶

Not available for VideoProject class. :raises: NotImplementedError in all cases.

Return type: None

static remove_classes_except(project_dir, classes_to_keep=None, inplace=False)¶

Not available for VideoProject class. :raises: NotImplementedError in all cases.

Return type: None

static remove_items_without_both_objects_and_tags(project_dir, inplace=False)¶

Not available for VideoProject class. :raises: NotImplementedError in all cases.

Return type: None

static remove_items_without_objects(project_dir, inplace=False)¶

Not available for VideoProject class. :raises: NotImplementedError in all cases.

Return type: None

static remove_items_without_tags(project_dir, inplace=False)¶

Not available for VideoProject class. :raises: NotImplementedError in all cases.

Return type: None

set_key_id_map(new_map)¶: Save given KeyIdMap object to project dir in json format. :type new_map: KeyIdMap :param new_map: KeyIdMap class object

set_meta(new_meta)¶

Saves given meta to project directory in json format.

Parameters

new_meta : ProjectMeta: ProjectMeta object.

Returns

None

Return type

NoneType

Usage example

import supervisely as sly
proj_lemons = sly.Project("/home/admin/work/supervisely/projects/lemons_annotated", sly.OpenMode.READ)
proj_kiwi = sly.Project("/home/admin/work/supervisely/projects/kiwi_annotated", sly.OpenMode.READ)

proj_lemons.set_meta(proj_kiwi.meta)

print(project.proj_lemons)
# Output:
# +-------+--------+----------------+--------+
# |  Name | Shape  |     Color      | Hotkey |
# +-------+--------+----------------+--------+
# |  kiwi | Bitmap |  [255, 0, 0]   |        |
# +-------+--------+----------------+--------+

to_coco(dest_dir=None, copy_images=False, with_captions=False, log_progress=True, progress_cb=None)¶

Convert Supervisely project to COCO format.

Parameters

dest_dir : str, optional: Destination directory.
copy_images : bool: Copy images to the destination directory.
with_captions : bool: Return captions for images.
log_progress : bool: Show uploading progress bar.
progress_cb : callable, optional: Function for tracking conversion progress (for all items in the project).

Returns

None

Return type

NoneType

Usage example

import supervisely as sly

# Local folder with Project
project_directory = "/home/admin/work/supervisely/source/project"

# Convert Project to COCO format
sly.Project(project_directory).to_coco(log_progress=True)
# or
from supervisely.convert import to_coco
to_coco(project_directory, dest_dir="./coco_project")

static to_detection_task(src_project_dir, dst_project_dir=None, inplace=False, progress_cb=None)¶

Not available for VideoProject class. :raises: NotImplementedError in all cases.

Return type: None

to_pascal_voc(dest_dir=None, train_val_split_coef=0.8, log_progress=True, progress_cb=None)¶

Convert Supervisely project to Pascal VOC format.

Parameters

dest_dir : str, optional: Destination directory.
train_val_split_coef : float, optional: Coefficient for splitting images into train and validation sets.
log_progress : bool: Show uploading progress bar.
progress_cb : callable, optional: Function for tracking conversion progress (for all items in the project).

Returns

None

Return type

NoneType

Usage example

import supervisely as sly

# Local folder with Project
project_directory = "/home/admin/work/supervisely/source/project"

# Convert Project to YOLO format
sly.Project(project_directory).to_pascal_voc(log_progress=True)
# or
from supervisely.convert import to_pascal_voc
to_pascal_voc(project_directory, dest_dir="./pascal_voc_project")

static to_segmentation_task(src_project_dir, dst_project_dir=None, inplace=False, target_classes=None, progress_cb=None, segmentation_type='semantic')¶

Not available for VideoProject class. :raises: NotImplementedError in all cases.

Return type: None

to_yolo(dest_dir=None, task_type='detect', log_progress=True, progress_cb=None, val_datasets=None)¶

Convert Supervisely project to YOLO format.

Parameters

dest_dir : str, optional: Destination directory.
task_type : str or TaskType, optional: Task type for YOLO format. Possible values: ‘detection’, ‘segmentation’, ‘pose’.
log_progress : bool: Show uploading progress bar.
progress_cb : callable, optional: Function for tracking conversion progress (for all items in the project).
val_datasets : list [ str ], optional: List of dataset names for validation. Full dataset names are required (e.g., ‘ds0/nested_ds1/ds3’). If specified, datasets from the list will be marked as val, others as train. If not specified, the function will determine the validation datasets automatically.

Returns

None

Return type

NoneType

Usage example

import supervisely as sly

# Local folder with Project
project_directory = "/home/admin/work/supervisely/source/project"

# Convert Project to YOLO format
sly.Project(project_directory).to_yolo(log_progress=True)
# or
from supervisely.convert import to_yolo
to_yolo(project_directory, dest_dir="./yolo_project")

static upload(directory, api, workspace_id, project_name=None, log_progress=True, progress_cb=None)[source]¶

Uploads pointcloud project to Supervisely from the given directory.

Parameters

directory : str: Path to project directory.
api : sly.Api: Supervisely API address and token.
workspace_id : int: Workspace ID, where project will be uploaded.
project_name : str, optional: Name of the project in Supervisely. Can be changed if project with the same name is already exists.
log_progress : bool: Show uploading progress bar.
progress_cb : tqdm or callable, optional: Function for tracking download progress.

Returns

Project ID and name. It is recommended to check that returned project name coincides with provided project name.

Return type

int, str

Usage example

import supervisely as sly

# Local folder with Pointcloud Project
project_directory = "/home/admin/work/supervisely/source/ptc_project"

# Obtain server address and your api_token from environment variables
# Edit those values if you run this notebook on your own PC
address = os.environ['SERVER_ADDRESS']
token = os.environ['API_TOKEN']

# Initialize API object
api = sly.Api(address, token)

# Upload Pointcloud Project
project_id, project_name = sly.PointcloudProject.upload(
    project_directory,
    api,
    workspace_id=45,
    project_name="My Pointcloud Project"
)

static upload_bin(api, file, workspace_id, project_name=None, with_custom_data=True, log_progress=True, progress_cb=None, skip_missed=False)¶

Uploads project to Supervisely from the given binary file and suitable only for projects downloaded in binary format. This method is a counterpart to download_bin(). Faster than uploading project in the usual way.

Parameters

api : Api: Supervisely API address and token.
file : str or BytesIO: Path to the binary file or BytesIO object.
workspace_id : int: Workspace ID, where project will be uploaded.
project_name : str, optional: Name of the project in Supervisely. Can be changed if project with the same name is already exists.
with_custom_data : bool, optional: If True, custom data from source project will be added to a new project.
log_progress : bool, optional: Show uploading progress bar.
progress_cb : tqdm or callable, optional: Function for tracking upload progress for datasets. Has a higher priority than log_progress.
skip_missed : bool, optional: Skip missed images.

Returns

ProjectInfo object.

Return type

ProjectInfo

Usage example

import supervisely as sly

# Local folder with Project
project_path = "/home/admin/work/supervisely/source/project/222_ProjectName"

# Obtain server address and your api_token from environment variables
# Edit those values if you run this notebook on your own PC
address = os.environ['SERVER_ADDRESS']
token = os.environ['API_TOKEN']

# Initialize API object
api = sly.Api(address, token)

# Upload Project
project_info = sly.Project.upload_bin(
    api,
    project_path,
    workspace_id=45,
    project_name="My Project"
)

property datasets¶

Project datasets.

Returns

Datasets

Return type

DatasetDict

Usage example

import supervisely as sly
project = sly.Project("/home/admin/work/supervisely/projects/lemons_annotated", sly.OpenMode.READ)
for dataset in project.datasets:
    print(dataset.name)
    # Output: ds1
    #         ds2

property directory¶

Path to the project directory.

Returns

Path to the project directory

Return type

str

Usage example

import supervisely as sly
project = sly.Project("/home/admin/work/supervisely/projects/lemons_annotated", sly.OpenMode.READ)
print(project.directory)
# Output: '/home/admin/work/supervisely/projects/lemons_annotated'

property meta¶

Project meta.

Returns

ProjectMeta object

Return type

ProjectMeta

Usage example

import supervisely as sly
project = sly.Project("/home/admin/work/supervisely/projects/lemons_annotated", sly.OpenMode.READ)
print(project.meta)
# Output:
# +-------+--------+----------------+--------+
# |  Name | Shape  |     Color      | Hotkey |
# +-------+--------+----------------+--------+
# |  kiwi | Bitmap |  [255, 0, 0]   |        |
# | lemon | Bitmap | [81, 198, 170] |        |
# +-------+--------+----------------+--------+
# Tags
# +------+------------+-----------------+--------+---------------+--------------------+
# | Name | Value type | Possible values | Hotkey | Applicable to | Applicable classes |
# +------+------------+-----------------+--------+---------------+--------------------+

property name¶

Project name.

Returns

Project name.

Return type

str

Usage example

import supervisely as sly
project = sly.Project("/home/admin/work/supervisely/projects/lemons_annotated", sly.OpenMode.READ)
print(project.name)
# Output: 'lemons_annotated'

property parent_dir¶

Project parent directory.

Returns

Path to project parent directory

Return type

str

Usage example

import supervisely as sly
project = sly.Project("/home/admin/work/supervisely/projects/lemons_annotated", sly.OpenMode.READ)
print(project.parent_dir)
# Output: '/home/admin/work/supervisely/projects'

property total_items¶

Total number of items in project.

Returns

Total number of items in project

Return type

int

Usage example

import supervisely as sly
project = sly.Project("/home/admin/work/supervisely/projects/lemons_annotated", sly.OpenMode.READ)
print(project.total_items)
# Output: 12

property type¶

Project type.

Returns

Project type.

Return type

str

Usage example

import supervisely as sly
project = sly.PointcloudProject("/home/admin/work/supervisely/projects/pointclouds", sly.OpenMode.READ)
print(project.type)
# Output: 'point_clouds'