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* Update LICENSE to AGPL-3.0 This pull request updates the license of the YOLOv5 project from GNU General Public License v3.0 (GPL-3.0) to GNU Affero General Public License v3.0 (AGPL-3.0). We at Ultralytics have decided to make this change in order to better protect our intellectual property and ensure that any modifications made to the YOLOv5 source code will be shared back with the community when used over a network. AGPL-3.0 is very similar to GPL-3.0, but with an additional clause to address the use of software over a network. This change ensures that if someone modifies YOLOv5 and provides it as a service over a network (e.g., through a web application or API), they must also make the source code of their modified version available to users of the service. This update includes the following changes: - Replace the `LICENSE` file with the AGPL-3.0 license text - Update the license reference in the `README.md` file - Update the license headers in source code files We believe that this change will promote a more collaborative environment and help drive further innovation within the YOLOv5 community. Please review the changes and let us know if you have any questions or concerns. Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Update headers to AGPL-3.0 --------- Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
77 lines
2.6 KiB
Python
77 lines
2.6 KiB
Python
# YOLOv5 🚀 by Ultralytics, AGPL-3.0 license
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"""
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Callback utils
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"""
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import threading
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class Callbacks:
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""""
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Handles all registered callbacks for YOLOv5 Hooks
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"""
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def __init__(self):
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# Define the available callbacks
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self._callbacks = {
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'on_pretrain_routine_start': [],
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'on_pretrain_routine_end': [],
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'on_train_start': [],
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'on_train_epoch_start': [],
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'on_train_batch_start': [],
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'optimizer_step': [],
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'on_before_zero_grad': [],
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'on_train_batch_end': [],
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'on_train_epoch_end': [],
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'on_val_start': [],
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'on_val_batch_start': [],
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'on_val_image_end': [],
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'on_val_batch_end': [],
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'on_val_end': [],
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'on_fit_epoch_end': [], # fit = train + val
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'on_model_save': [],
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'on_train_end': [],
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'on_params_update': [],
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'teardown': [],}
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self.stop_training = False # set True to interrupt training
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def register_action(self, hook, name='', callback=None):
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"""
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Register a new action to a callback hook
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Args:
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hook: The callback hook name to register the action to
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name: The name of the action for later reference
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callback: The callback to fire
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"""
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assert hook in self._callbacks, f"hook '{hook}' not found in callbacks {self._callbacks}"
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assert callable(callback), f"callback '{callback}' is not callable"
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self._callbacks[hook].append({'name': name, 'callback': callback})
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def get_registered_actions(self, hook=None):
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""""
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Returns all the registered actions by callback hook
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Args:
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hook: The name of the hook to check, defaults to all
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"""
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return self._callbacks[hook] if hook else self._callbacks
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def run(self, hook, *args, thread=False, **kwargs):
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"""
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Loop through the registered actions and fire all callbacks on main thread
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Args:
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hook: The name of the hook to check, defaults to all
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args: Arguments to receive from YOLOv5
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thread: (boolean) Run callbacks in daemon thread
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kwargs: Keyword Arguments to receive from YOLOv5
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"""
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assert hook in self._callbacks, f"hook '{hook}' not found in callbacks {self._callbacks}"
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for logger in self._callbacks[hook]:
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if thread:
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threading.Thread(target=logger['callback'], args=args, kwargs=kwargs, daemon=True).start()
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else:
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logger['callback'](*args, **kwargs)
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