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# Ultralytics YOLO 🚀, AGPL-3.0 license
import requests
from ultralytics.hub.auth import Auth
from ultralytics.hub.utils import PREFIX
from ultralytics.yolo.data.utils import HUBDatasetStats
from ultralytics.yolo.utils import LOGGER, SETTINGS, USER_CONFIG_DIR, yaml_save
def login(api_key=''):
"""
Log in to the Ultralytics HUB API using the provided API key.
Args:
api_key (str, optional): May be an API key or a combination API key and model ID, i.e. key_id
Example:
from ultralytics import hub
hub.login('API_KEY')
"""
Auth(api_key, verbose=True)
def logout():
"""
Log out of Ultralytics HUB by removing the API key from the settings file. To log in again, use 'yolo hub login'.
Example:
from ultralytics import hub
hub.logout()
"""
SETTINGS['api_key'] = ''
yaml_save(USER_CONFIG_DIR / 'settings.yaml', SETTINGS)
LOGGER.info(f"{PREFIX}logged out ✅. To log in again, use 'yolo hub login'.")
def start(key=''):
"""
Start training models with Ultralytics HUB (DEPRECATED).
Args:
key (str, optional): A string containing either the API key and model ID combination (apikey_modelid),
or the full model URL (https://hub.ultralytics.com/models/apikey_modelid).
"""
api_key, model_id = key.split('_')
LOGGER.warning(f"""
WARNING ⚠️ ultralytics.start() is deprecated after 8.0.60. Updated usage to train Ultralytics HUB models is:
from ultralytics import YOLO, hub
hub.login('{api_key}')
model = YOLO('https://hub.ultralytics.com/models/{model_id}')
model.train()""")
def reset_model(model_id=''):
"""Reset a trained model to an untrained state."""
r = requests.post('https://api.ultralytics.com/model-reset', json={'apiKey': Auth().api_key, 'modelId': model_id})
if r.status_code == 200:
LOGGER.info(f'{PREFIX}Model reset successfully')
return
LOGGER.warning(f'{PREFIX}Model reset failure {r.status_code} {r.reason}')
def export_fmts_hub():
"""Returns a list of HUB-supported export formats."""
from ultralytics.yolo.engine.exporter import export_formats
return list(export_formats()['Argument'][1:]) + ['ultralytics_tflite', 'ultralytics_coreml']
def export_model(model_id='', format='torchscript'):
"""Export a model to all formats."""
assert format in export_fmts_hub(), f"Unsupported export format '{format}', valid formats are {export_fmts_hub()}"
r = requests.post(f'https://api.ultralytics.com/v1/models/{model_id}/export',
json={'format': format},
headers={'x-api-key': Auth().api_key})
assert r.status_code == 200, f'{PREFIX}{format} export failure {r.status_code} {r.reason}'
LOGGER.info(f'{PREFIX}{format} export started ✅')
def get_export(model_id='', format='torchscript'):
"""Get an exported model dictionary with download URL."""
assert format in export_fmts_hub(), f"Unsupported export format '{format}', valid formats are {export_fmts_hub()}"
r = requests.post('https://api.ultralytics.com/get-export',
json={
'apiKey': Auth().api_key,
'modelId': model_id,
'format': format})
assert r.status_code == 200, f'{PREFIX}{format} get_export failure {r.status_code} {r.reason}'
return r.json()
def check_dataset(path='', task='detect'):
"""
Function for error-checking HUB dataset Zip file before upload. It checks a dataset for errors before it is
uploaded to the HUB. Usage examples are given below.
Args:
path (str, optional): Path to data.zip (with data.yaml inside data.zip). Defaults to ''.
task (str, optional): Dataset task. Options are 'detect', 'segment', 'pose', 'classify'. Defaults to 'detect'.
Example:
```python
from ultralytics.hub import check_dataset
check_dataset('path/to/coco8.zip', task='detect') # detect dataset
check_dataset('path/to/coco8-seg.zip', task='segment') # segment dataset
check_dataset('path/to/coco8-pose.zip', task='pose') # pose dataset
```
"""
HUBDatasetStats(path=path, task=task).get_json()
LOGGER.info('Checks completed correctly ✅. Upload this dataset to https://hub.ultralytics.com/datasets/.')
if __name__ == '__main__':
start()
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