# Ultralytics YOLO 🚀, AGPL-3.0 license import requests from ultralytics.data.utils import HUBDatasetStats from ultralytics.hub.auth import Auth from ultralytics.hub.utils import HUB_API_ROOT, HUB_WEB_ROOT, PREFIX from ultralytics.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: ```python 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: ```python 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('{HUB_WEB_ROOT}/models/{model_id}') model.train()""") def reset_model(model_id=''): """Reset a trained model to an untrained state.""" r = requests.post(f'{HUB_API_ROOT}/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.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'{HUB_API_ROOT}/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(f'{HUB_API_ROOT}/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(f'Checks completed correctly ✅. Upload this dataset to {HUB_WEB_ROOT}/datasets/.') if __name__ == '__main__': start()