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ultralytics 8.2.62 add Explorer CLI model and data args (#14581)

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: Mohammed Yasin <32206511+Y-T-G@users.noreply.github.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
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Glenn Jocher 2024-07-22 03:29:44 +02:00 • committed by GitHub
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ultralytics/engine/model.py
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@ -583,7 +583,7 @@ class Model(nn.Module):
**kwargs (Any): Additional keyword arguments for configuring the tracking process.
Returns:
(List[ultralytics.engine.results.Results]): A list of tracking results, each encapsulated in a Results object.
(List[ultralytics.engine.results.Results]): A list of tracking results, each a Results object.
Raises:
AttributeError: If the predictor does not have registered trackers.
@ -1028,8 +1028,8 @@ class Model(nn.Module):
The default callbacks are defined in the 'callbacks.default_callbacks' dictionary, which contains predefined
functions for various events in the model's lifecycle, such as on_train_start, on_epoch_end, etc.
This method is useful when you want to revert to the original set of callbacks after making custom modifications,
ensuring consistent behavior across different runs or experiments.
This method is useful when you want to revert to the original set of callbacks after making custom
modifications, ensuring consistent behavior across different runs or experiments.
Examples:
>>> model = YOLO('yolov8n.pt')
@ -1122,7 +1122,7 @@ class Model(nn.Module):
nested dictionaries. Each nested dictionary has keys 'model', 'trainer', 'validator', and
'predictor', mapping to their respective class implementations.
Example:
Examples:
>>> model = Model()
>>> task_map = model.task_map
>>> detect_class_map = task_map['detect']