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