Project¶

class Project[source]¶

Bases: object

Project is a parent directory for dataset. Project object is immutable.

Parameters

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

Usage example

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

Methods

`copy_data`	Makes a copy of the `Project`.
`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 project from Supervisely to the given directory.
`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 datasets list in Supervisely.
`remove_classes`	Removes given classes from Project.
`remove_classes_except`	Removes classes from Project with the exception of some classes.
`remove_items_without_both_objects_and_tags`	Remove items(images and annotations) without objects and tags from Project.
`remove_items_without_objects`	Remove items(images and annotations) without objects from Project.
`remove_items_without_tags`	Remove items(images and annotations) without tags from Project.
`set_meta`	Saves given `meta` to project directory in json format.
`to_detection_task`	Makes a copy of the `Project`, converts annotations to `Rectangles` and updates `project meta`.
`to_segmentation_task`	Makes a copy of the `Project`, converts annotations to `Bitmaps` and updates `project meta`.
`upload`	Uploads project to Supervisely from the given directory.
`validate`

Attributes

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

class DatasetDict[source]¶

Bases: supervisely.collection.key_indexed_collection.KeyIndexedCollection

Datasets collection of Project.

item_type¶: alias of supervisely.project.project.Dataset

add(item)¶

Add given item to collection.

Parameters

item : KeyObject: ObjClassCollection, TagMetaCollection or TagCollection object.

Returns

New instance of KeyIndexedCollection

Return type

KeyIndexedCollection

Usage Example

import supervisely as sly

item_cat = sly.TagMeta('cat', sly.TagValueType.NONE)
item_turtle = sly.TagMeta('turtle', sly.TagValueType.ANY_STRING)
collection = sly.collection.key_indexed_collection.KeyIndexedCollection([item_cat, item_turtle])
# Remember that KeyIndexedCollection object is immutable, and we need to assign new instance of KeyIndexedCollection to a new variable
item_dog = sly.ObjClass('dog', sly.Rectangle)
new_collection = collection.add(item_dog)

add_items(items)¶

Add items from given list to collection.

Parameters

items : List[KeyObject]: List of ObjClassCollection, TagMetaCollection or TagCollection objects.

Returns

New instance of KeyIndexedCollection

Return type

KeyIndexedCollection

Usage Example

import supervisely as sly

item_cat = sly.TagMeta('cat', sly.TagValueType.NONE)
item_turtle = sly.TagMeta('turtle', sly.TagValueType.ANY_STRING)
collection = sly.collection.key_indexed_collection.KeyIndexedCollection([item_cat, item_turtle])
# Remember that KeyIndexedCollection object is immutable, and we need to assign new instance of KeyIndexedCollection to a new variable
item_dog = sly.ObjClass('dog', sly.Rectangle)
item_mouse = sly.ObjClass('mouse', sly.Bitmap)
new_collection = collection.add_items([item_dog, item_mouse])

clone(items=None)¶

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

Parameters

items : List[KeyObject], optional: List of ObjClassCollection, TagMetaCollection or TagCollection objects.

Returns

New instance of KeyIndexedCollection

Return type

KeyIndexedCollection

Usage Example

import supervisely as sly

item_cat = sly.TagMeta('cat', sly.TagValueType.NONE)
item_turtle = sly.TagMeta('turtle', sly.TagValueType.ANY_STRING)
collection = sly.collection.key_indexed_collection.KeyIndexedCollection([item_cat, item_turtle])
# Remember that KeyIndexedCollection object is immutable, and we need to assign new instance of KeyIndexedCollection to a new variable
new_collection = collection.clone()

difference(other)¶

Find difference between collection and given list of instances.

Parameters

key : List[KeyObject]: List of ObjClassCollection, TagMetaCollection or TagCollection objects.

Returns

KeyIndexedCollection object

Return type

KeyIndexedCollection

Usage Example

import supervisely as sly

item_cat = sly.TagMeta('cat', sly.TagValueType.NONE)
item_turtle = sly.TagMeta('turtle', sly.TagValueType.ANY_STRING)
collection = sly.collection.key_indexed_collection.KeyIndexedCollection([item_cat, item_turtle])

item_dog = sly.TagMeta('dog', sly.TagValueType.NONE)
item_turtle = sly.TagMeta('turtle', sly.TagValueType.ANY_STRING)
items = [item_dog, item_turtle]

diff = collection.difference(items)
print(diff.to_json())
# Output: [
#     {
#         "name": "cat",
#         "value_type": "none",
#         "color": "#8A150F",
#         "hotkey": "",
#         "applicable_type": "all",
#         "classes": []
#     }
# ]

get(key, default=None)¶

Get item from collection with given key(name).

Parameters

items : str: Name of KeyObject in collection.
default : optional: The value that is returned if there is no key in the collection.

Returns

ObjClassCollection, TagMetaCollection or TagCollection object

Return type

KeyObject

Usage Example

import supervisely as sly

item_cat = sly.TagMeta('cat', sly.TagValueType.NONE)
item_turtle = sly.TagMeta('turtle', sly.TagValueType.ANY_STRING)
collection = sly.collection.key_indexed_collection.KeyIndexedCollection([item_cat, item_turtle])

item_cat = collection.get('cat')
print(item_cat)
# Output:
# Name:  cat                      Value type:none          Possible values:None       Hotkey                  Applicable toall        Applicable classes[]

item_not_exist = collection.get('no_item', {1: 2})
print(item_not_exist)
# Output:
# {1: 2}

has_key(key)¶

Check if given key(item name exist in collection).

Parameters

key : str: The key to look for in the collection.

Returns

Is the key in the collection or not

Return type

bool

Usage Example

import supervisely as sly

item_cat = sly.TagMeta('cat', sly.TagValueType.NONE)
item_turtle = sly.TagMeta('turtle', sly.TagValueType.ANY_STRING)
collection = sly.collection.key_indexed_collection.KeyIndexedCollection([item_cat, item_turtle])

collection.has_key('cat') # True
collection.has_key('hamster') # False

intersection(other)¶

Find intersection of given list of instances with collection items.

Parameters

key : List[KeyObject]: List of ObjClassCollection, TagMetaCollection or TagCollection objects.

Raises

ValueError if find items with same keys(item names)

Returns

KeyIndexedCollection object

Return type

KeyIndexedCollection

Usage Example

import supervisely as sly

item_cat = sly.TagMeta('cat', sly.TagValueType.NONE)
item_turtle = sly.TagMeta('turtle', sly.TagValueType.ANY_STRING)
collection = sly.collection.key_indexed_collection.KeyIndexedCollection([item_cat, item_turtle])

item_dog = sly.TagMeta('dog', sly.TagValueType.NONE)
item_turtle = sly.TagMeta('turtle', sly.TagValueType.ANY_STRING)
items = [item_dog, item_turtle]

intersection = collection.intersection(items)
print(intersection.to_json())
# Output: [
#     {
#         "name": "turtle",
#         "value_type": "any_string",
#         "color": "#760F8A",
#         "hotkey": "",
#         "applicable_type": "all",
#         "classes": []
#     }
# ]

items()¶

Get list of all items in collection.

Returns

List of ObjClassCollection, TagMetaCollection or TagCollection objects

Return type

List[KeyObject]

Usage Example

import supervisely as sly

item_cat = sly.TagMeta('cat', sly.TagValueType.NONE)
item_turtle = sly.TagMeta('turtle', sly.TagValueType.ANY_STRING)
collection = sly.collection.key_indexed_collection.KeyIndexedCollection([item_cat, item_turtle])
items = collection.items()
print(items)
# Output:
# [<supervisely.annotation.tag_meta.TagMeta object at 0x7fd08eae4340>,
#  <supervisely.annotation.tag_meta.TagMeta object at 0x7fd08eae4370>]

keys()¶

Get list of all keys(item names) in collection.

Returns

List of collection keys

Return type

List[str]

Usage Example

import supervisely as sly

item_cat = sly.TagMeta('cat', sly.TagValueType.NONE)
item_turtle = sly.TagMeta('turtle', sly.TagValueType.ANY_STRING)
collection = sly.collection.key_indexed_collection.KeyIndexedCollection([item_cat, item_turtle])
keys = collection.keys() # ['cat', 'turtle']

merge(other)¶

Merge collection and other KeyIndexedCollection object.

Parameters

key : KeyIndexedCollection: KeyIndexedCollection object.

Raises

ValueError if item name from given list is in collection but items in both are different

Returns

KeyIndexedCollection object

Return type

KeyIndexedCollection

Usage Example

import supervisely as sly

item_cat = sly.TagMeta('cat', sly.TagValueType.NONE)
item_turtle = sly.TagMeta('turtle', sly.TagValueType.ANY_STRING)
collection = sly.collection.key_indexed_collection.KeyIndexedCollection([item_cat, item_turtle])

item_dog = sly.TagMeta('dog', sly.TagValueType.NONE)
item_turtle = sly.TagMeta('turtle', sly.TagValueType.ANY_STRING)
other_collection = sly.collection.key_indexed_collection.KeyIndexedCollection([item_dog, item_turtle])

merge = collection.merge(other_collection)
print(merge.to_json())
# Output: [
#     {
#         "name": "dog",
#         "value_type": "none",
#         "color": "#8A6C0F",
#         "hotkey": "",
#         "applicable_type": "all",
#         "classes": []
#     },
#     {
#         "name": "cat",
#         "value_type": "none",
#         "color": "#0F4A8A",
#         "hotkey": "",
#         "applicable_type": "all",
#         "classes": []
#     },
#     {
#         "name": "turtle",
#         "value_type": "any_string",
#         "color": "#4F0F8A",
#         "hotkey": "",
#         "applicable_type": "all",
#         "classes": []
#     }
# ]

to_json()¶

Convert the KeyIndexedCollection to a json serializable list.

Returns

List of json serializable dicts

Return type

List[dict]

Usage Example

import supervisely as sly

item_cat = sly.TagMeta('cat', sly.TagValueType.NONE)
item_turtle = sly.TagMeta('turtle', sly.TagValueType.ANY_STRING)
collection = sly.collection.key_indexed_collection.KeyIndexedCollection([item_cat, item_turtle])
collection_json = collection.to_json()
# Output: [
#     {
#         "name": "cat",
#         "value_type": "none",
#         "color": "#8A0F12",
#         "hotkey": "",
#         "applicable_type": "all",
#         "classes": []
#     },
#     {
#         "name": "turtle",
#         "value_type": "any_string",
#         "color": "#8A860F",
#         "hotkey": "",
#         "applicable_type": "all",
#         "classes": []
#     }
# ]

dataset_class¶: alias of supervisely.project.project.Dataset

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

Makes a copy of the Project.

Parameters

dst_directory : str: Path to project parent directory.
dst_name : str, optional: 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

Project object.

Return type

Project

Usage example

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

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

create_dataset(ds_name)[source]¶

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, log_progress=False, batch_size=10, cache=None, progress_cb=None, only_image_tags=False, save_image_info=False, save_images=True, save_image_meta=False)[source]¶

Download project from Supervisely to the given directory.

Parameters

api : 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.
log_progress : bool, optional: Show uploading progress bar.
batch_size : int, optional: The number of images in the batch when they are loaded to a host.
cache : FileCache, optional: FileCache object.
progress_cb : tqdm or callable, optional: Function for tracking download progress.
only_image_tags : bool, optional: Download project with only images tags (without objects tags).
save_image_info : bool, optional: Download images infos or not.
save_images : bool, optional: Download images or not.
save_image_meta : bool, optional: Download images metadata in JSON format or not.

Returns

None

Return type

NoneType

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

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

list [ ItemInfo ], list [ ItemInfo ]

Usage example

import supervisely as sly
train_count = 4
val_count = 2
train_items, val_items = sly.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

list [ ItemInfo ], list [ ItemInfo ]

Usage example

import supervisely as sly
train_datasets = ['ds1', 'ds2']
val_datasets = ['ds3', 'ds4']
train_items, val_items = sly.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

list [ ItemInfo ], list [ ItemInfo ]

Usage example

import supervisely as sly
train_tag_name = 'train'
val_tag_name = 'val'
train_items, val_items = sly.Project.get_train_val_splits_by_tag(
    project_path,
    train_tag_name,
    val_tag_name
)

static get_url(id)[source]¶

Get URL to datasets list in Supervisely.

Parameters

id : int: Project ID in Supervisely.

Returns

URL to datasets list.

Return type

str

Usage example

from supervisely import Project

project_id = 10093
datasets_link = Project.get_url(project_id)

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

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

Removes given classes from Project.

Parameters

project_dir : str: Path to project directory.
classes_to_remove : list [ str ], optional: Classes to remove.
inplace : bool, optional: Сheckbox that determines whether to change the source data in project or not.

Returns

None

Return type

NoneType

Usage example

import supervisely as sly
project = sly.Project(project_path, sly.OpenMode.READ)
classes_to_remove = ['lemon']
project.remove_classes(project_path, classes_to_remove, inplace=True)

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

Removes classes from Project with the exception of some classes.

Parameters

project_dir : str: Path to project directory.
classes_to_keep : list [ str ], optional: Classes to keep in project.
inplace : bool, optional: Сheckbox that determines whether to change the source data in project or not.

Returns

None

Return type

NoneType

Usage example

import supervisely as sly
project = sly.Project(project_path, sly.OpenMode.READ)
project.remove_classes_except(project_path, inplace=True)

static remove_items_without_both_objects_and_tags(project_dir, inplace=False)[source]¶

Remove items(images and annotations) without objects and tags from Project.

Parameters

project_dir : str: Path to project directory.
inplace : bool, optional: Сheckbox that determines whether to change the source data in project or not.

Returns

None

Return type

NoneType

Usage example

import supervisely as sly
sly.Project.remove_items_without_both_objects_and_tags(project_path, inplace=True)

static remove_items_without_objects(project_dir, inplace=False)[source]¶

Remove items(images and annotations) without objects from Project.

Parameters

project_dir : str: Path to project directory.
inplace : bool, optional: Сheckbox that determines whether to change the source data in project or not.

Returns

None

Return type

NoneType

Usage example

import supervisely as sly
sly.Project.remove_items_without_objects(project_path, inplace=True)

static remove_items_without_tags(project_dir, inplace=False)[source]¶

Remove items(images and annotations) without tags from Project.

Parameters

project_dir : str: Path to project directory.
inplace : bool, optional: Сheckbox that determines whether to change the source data in project or not.

Returns

None

Return type

NoneType

Usage example

import supervisely as sly
sly.Project.remove_items_without_tags(project_path, inplace=True)

set_meta(new_meta)[source]¶

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]   |        |
# +-------+--------+----------------+--------+

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

Makes a copy of the Project, converts annotations to Rectangles and updates project meta.

Parameters

src_project_dir : str: Path to source project directory.
dst_project_dir : str, optional: Path to destination project directory. Must be None If inplace=True.
inplace : bool, optional: Modifies source project If True. Must be False If dst_project_dir is specified.
progress_cb : tqdm or callable, optional: Function for tracking download progress.

Returns

None

Return type

NoneType

Usage example

import supervisely as sly
source_project = sly.Project("/home/admin/work/supervisely/projects/lemons_annotated", sly.OpenMode.READ)
det_project_path = "/home/admin/work/supervisely/projects/lemons_detection"
sly.Project.to_detection_task(
    src_project_dir=source_project.directory,
    dst_project_dir=det_project_path
)
det_project = sly.Project(det_project_path, sly.OpenMode.READ)

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

Makes a copy of the Project, converts annotations to Bitmaps and updates project meta.

You will able to get item’s segmentation masks location by dataset.get_seg_path(item_name) method.

Parameters

src_project_dir : str: Path to source project directory.
dst_project_dir : str, optional: Path to destination project directory. Must be None If inplace=True.
inplace : bool, optional: Modifies source project If True. Must be False If dst_project_dir is specified.
target_classes : list [ str ], optional: Classes list to include to destination project. If segmentation_type=”semantic”, background class “__bg__” will be added automatically.
progress_cb : tqdm or callable, optional: Function for tracking download progress.
segmentation_type : str: One of: {“semantic”, “instance”}. If segmentation_type=”semantic”, background class “__bg__” will be added automatically and instances will be converted to non overlapping semantic segmentation mask.

Returns

None

Return type

NoneType

Usage example

import supervisely as sly
source_project = sly.Project("/home/admin/work/supervisely/projects/lemons_annotated", sly.OpenMode.READ)
seg_project_path = "/home/admin/work/supervisely/projects/lemons_segmentation"
sly.Project.to_segmentation_task(
    src_project_dir=source_project.directory,
    dst_project_dir=seg_project_path
)
seg_project = sly.Project(seg_project_path, sly.OpenMode.READ)

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

Uploads project to Supervisely from the given directory.

Parameters

dir : str: Path to project directory.
api : 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, optional: 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 Project
project_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)

# Upload Project
project_id, project_name = sly.Project.upload(
    project_directory,
    api,
    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