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import requests |
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from ultralytics.hub.auth import Auth |
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from ultralytics.hub.utils import PREFIX |
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from ultralytics.yolo.data.utils import HUBDatasetStats |
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from ultralytics.yolo.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('https://hub.ultralytics.com/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('https://api.ultralytics.com/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.yolo.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'https://api.ultralytics.com/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('https://api.ultralytics.com/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 |
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Arguments |
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path: Path to data.zip (with data.yaml inside data.zip) |
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task: Dataset task. Options are 'detect', 'segment', 'pose', 'classify'. |
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Usage |
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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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HUBDatasetStats(path=path, task=task).get_json() |
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LOGGER.info('Checks completed correctly ✅. Upload this dataset to https://hub.ultralytics.com/datasets/.') |
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if __name__ == '__main__': |
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start() |
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