How can I use export_snapshot_create & export_snapshot_download to download a zip including images?

[Yobol]

Hi! I encountered an issue when I use label studio SDK for Python. I use export_snapshot_create & export_snapshot_download to download project task results in type of YOLO as a zipfile, but no image files in it, my code as following:

# Define the URL where Label Studio is accessible and the API key for your user account
LABEL_STUDIO_URL = 'http://172.16.250.101:31010' # 'http://mlops-ls-app:80'
API_KEY = '3f968a3eefd3d17aa1f4fb70dc13e677995f88f8'

# Import the SDK and the client module
from label_studio_sdk import Client

# Connect to the Label Studio API and check the connection
ls = Client(url=LABEL_STUDIO_URL, api_key=API_KEY)
ls.check_connection()

PROJECT_ID = 1
'''
https://github.com/heartexlabs/label-studio-converter/blob/master/label_studio_converter/converter.py#L44

SUPPORTED FORMATS:
    JSON = 1
    JSON_MIN = 2
    CSV = 3
    TSV = 4
    CONLL2003 = 5
    COCO = 6
    VOC = 7
    BRUSH_TO_NUMPY = 8
    BRUSH_TO_PNG = 9
    ASR_MANIFEST = 10
    YOLO = 11
    CSV_OLD = 12
'''
EXPORT_TYPE = 'YOLO'

project = ls.get_project(PROJECT_ID)

result = project.export_snapshot_create(
    title='export-test-01',
    task_filter_options={
        'view': 1,
        'finished': 'only', # include all finished tasks (is_labeled = true)
        'annotated': 'only', # include all tasks with at least one not skipped annotation
    }
)
print('create snapshot for project {}: {}'.format(PROJECT_ID, result['status']))

result = project.export_snapshot_download(
    export_id=result['id'],
    export_type=EXPORT_TYPE,
    path='.'
)
status, zip_file_path = result
print('download snapshot for project {}: {}'.format(PROJECT_ID, status))

I successfully downloaded a YOLO annotation result zipfile, but it has no any files in image folder. What parameters can I set to do this?

[Parxd]

Using project.export_snapshot_create() gives me RecursionError: maximum recursion depth exceeded.
Is anyone else facing this issue?

[Digital2Slave]

same issue. How to fix it ?

• label-studio

label-studio                   1.10.0.post0
label-studio-converter         0.0.33rc5
label-studio-evalme            0.0.18
label-studio-sdk               0.0.32
label-studio-tools             0.0.3

• os

No LSB modules are available.
Distributor ID:	Ubuntu
Description:	Ubuntu 20.04.6 LTS
Release:	20.04
Codename:	focal

[Digital2Slave]

1. export JSON file with the following function.

import time
from label_studio_sdk import Client

# https://labelstud.io/guide/export
# https://github.com/HumanSignal/label-studio-sdk/blob/master/examples/export_snapshots.py
def ExportSnapshot(LABEL_STUDIO_URL, API_KEY, PROJECT_ID, SAVE_PATH):
    # connect to Label Studio
    ls = Client(url=LABEL_STUDIO_URL, api_key=API_KEY)
    ls.check_connection()

    # get existing project
    project = ls.get_project(PROJECT_ID)

    # get the first tab
    views = project.get_views()
    task_filter_options = {'view': views[0]['id']} if views else {}

    # create new export snapshot
    export_result = project.export_snapshot_create(
        title='Export SDK Snapshot', task_filter_options=task_filter_options
    )
    # assert 'id' in export_result
    export_id = export_result['id']

    # # wait until snapshot is ready
    while project.export_snapshot_status(export_id).is_in_progress():
        time.sleep(1.0)

    # download snapshot file
    status, file_name = project.export_snapshot_download(export_id, export_type='JSON', path=SAVE_PATH)
    assert status == 200
    assert file_name is not None
    print(f"Status of the export is {status}.\nFile name is {file_name}")

2. set LS_UPLOAD_DIR in .zshrc or .bashrc and source ~/.zshrc or source ~/.bashrc

# label studio
export LS_UPLOAD_DIR=/home/epbox/AI/data/media/upload

3. save .xml file of the export project

4. use label-studio-converter to convert JSON to YOLO format

pip install label-studio-converter

label-studio-converter export -i <ExportSnapshot export>.json --config <export project config>.xml -o "train" -f YOLO

5. check the convert YOLO train folder

(label) ➜  train -h --filelimit=10 --dirsfirst
train
├── [ 20K]  images [208 entries exceeds filelimit, not opening dir]
├── [ 20K]  labels [208 entries exceeds filelimit, not opening dir]
├── [ 124]  classes.txt
└── [ 840]  notes.json

2 directories, 2 files