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Ruff format docstring Python code (#15792)

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Signed-off-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
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Glenn Jocher 2024-08-25 01:08:07 +08:00 • committed by GitHub
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ultralytics/engine/model.py
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@ -72,11 +72,11 @@ class Model(nn.Module):
Examples:
>>> from ultralytics import YOLO
>>> model = YOLO('yolov8n.pt')
>>> results = model.predict('image.jpg')
>>> model.train(data='coco128.yaml', epochs=3)
>>> model = YOLO("yolov8n.pt")
>>> results = model.predict("image.jpg")
>>> model.train(data="coco128.yaml", epochs=3)
>>> metrics = model.val()
>>> model.export(format='onnx')
>>> model.export(format="onnx")
"""
def __init__(
@ -166,8 +166,8 @@ class Model(nn.Module):
Results object.
Examples:
>>> model = YOLO('yolov8n.pt')
>>> results = model('https://ultralytics.com/images/bus.jpg')
>>> model = YOLO("yolov8n.pt")
>>> results = model("https://ultralytics.com/images/bus.jpg")
>>> for r in results:
... print(f"Detected {len(r)} objects in image")
"""
@ -188,9 +188,9 @@ class Model(nn.Module):
(bool): True if the model string is a valid Triton Server URL, False otherwise.
Examples:
>>> Model.is_triton_model('http://localhost:8000/v2/models/yolov8n')
>>> Model.is_triton_model("http://localhost:8000/v2/models/yolov8n")
True
>>> Model.is_triton_model('yolov8n.pt')
>>> Model.is_triton_model("yolov8n.pt")
False
"""
from urllib.parse import urlsplit
@ -253,7 +253,7 @@ class Model(nn.Module):
Examples:
>>> model = Model()
>>> model._new('yolov8n.yaml', task='detect', verbose=True)
>>> model._new("yolov8n.yaml", task="detect", verbose=True)
"""
cfg_dict = yaml_model_load(cfg)
self.cfg = cfg
@ -284,8 +284,8 @@ class Model(nn.Module):
Examples:
>>> model = Model()
>>> model._load('yolov8n.pt')
>>> model._load('path/to/weights.pth', task='detect')
>>> model._load("yolov8n.pt")
>>> model._load("path/to/weights.pth", task="detect")
"""
if weights.lower().startswith(("https://", "http://", "rtsp://", "rtmp://", "tcp://")):
weights = checks.check_file(weights, download_dir=SETTINGS["weights_dir"]) # download and return local file
@ -348,7 +348,7 @@ class Model(nn.Module):
AssertionError: If the model is not a PyTorch model.
Examples:
>>> model = Model('yolov8n.pt')
>>> model = Model("yolov8n.pt")
>>> model.reset_weights()
"""
self._check_is_pytorch_model()
@ -377,8 +377,8 @@ class Model(nn.Module):
Examples:
>>> model = Model()
>>> model.load('yolov8n.pt')
>>> model.load(Path('path/to/weights.pt'))
>>> model.load("yolov8n.pt")
>>> model.load(Path("path/to/weights.pt"))
"""
self._check_is_pytorch_model()
if isinstance(weights, (str, Path)):
@ -402,8 +402,8 @@ class Model(nn.Module):
AssertionError: If the model is not a PyTorch model.
Examples:
>>> model = Model('yolov8n.pt')
>>> model.save('my_model.pt')
>>> model = Model("yolov8n.pt")
>>> model.save("my_model.pt")
"""
self._check_is_pytorch_model()
from copy import deepcopy
@ -439,7 +439,7 @@ class Model(nn.Module):
TypeError: If the model is not a PyTorch model.
Examples:
>>> model = Model('yolov8n.pt')
>>> model = Model("yolov8n.pt")
>>> model.info() # Prints model summary
>>> info_list = model.info(detailed=True, verbose=False) # Returns detailed info as a list
"""
@ -494,8 +494,8 @@ class Model(nn.Module):
AssertionError: If the model is not a PyTorch model.
Examples:
>>> model = YOLO('yolov8n.pt')
>>> image = 'https://ultralytics.com/images/bus.jpg'
>>> model = YOLO("yolov8n.pt")
>>> image = "https://ultralytics.com/images/bus.jpg"
>>> embeddings = model.embed(image)
>>> print(embeddings[0].shape)
"""
@ -531,8 +531,8 @@ class Model(nn.Module):
Results object.
Examples:
>>> model = YOLO('yolov8n.pt')
>>> results = model.predict(source='path/to/image.jpg', conf=0.25)
>>> model = YOLO("yolov8n.pt")
>>> results = model.predict(source="path/to/image.jpg", conf=0.25)
>>> for r in results:
... print(r.boxes.data) # print detection bounding boxes
@ -592,8 +592,8 @@ class Model(nn.Module):
AttributeError: If the predictor does not have registered trackers.
Examples:
>>> model = YOLO('yolov8n.pt')
>>> results = model.track(source='path/to/video.mp4', show=True)
>>> model = YOLO("yolov8n.pt")
>>> results = model.track(source="path/to/video.mp4", show=True)
>>> for r in results:
... print(r.boxes.id) # print tracking IDs
@ -635,8 +635,8 @@ class Model(nn.Module):
AssertionError: If the model is not a PyTorch model.
Examples:
>>> model = YOLO('yolov8n.pt')
>>> results = model.val(data='coco128.yaml', imgsz=640)
>>> model = YOLO("yolov8n.pt")
>>> results = model.val(data="coco128.yaml", imgsz=640)
>>> print(results.box.map) # Print mAP50-95
"""
custom = {"rect": True} # method defaults
@ -677,8 +677,8 @@ class Model(nn.Module):
AssertionError: If the model is not a PyTorch model.
Examples:
>>> model = YOLO('yolov8n.pt')
>>> results = model.benchmark(data='coco8.yaml', imgsz=640, half=True)
>>> model = YOLO("yolov8n.pt")
>>> results = model.benchmark(data="coco8.yaml", imgsz=640, half=True)
>>> print(results)
"""
self._check_is_pytorch_model()
@ -727,8 +727,8 @@ class Model(nn.Module):
RuntimeError: If the export process fails due to errors.
Examples:
>>> model = YOLO('yolov8n.pt')
>>> model.export(format='onnx', dynamic=True, simplify=True)
>>> model = YOLO("yolov8n.pt")
>>> model.export(format="onnx", dynamic=True, simplify=True)
'path/to/exported/model.onnx'
"""
self._check_is_pytorch_model()
@ -782,8 +782,8 @@ class Model(nn.Module):
ModuleNotFoundError: If the HUB SDK is not installed.
Examples:
>>> model = YOLO('yolov8n.pt')
>>> results = model.train(data='coco128.yaml', epochs=3)
>>> model = YOLO("yolov8n.pt")
>>> results = model.train(data="coco128.yaml", epochs=3)
"""
self._check_is_pytorch_model()
if hasattr(self.session, "model") and self.session.model.id: # Ultralytics HUB session with loaded model
@ -847,7 +847,7 @@ class Model(nn.Module):
AssertionError: If the model is not a PyTorch model.
Examples:
>>> model = YOLO('yolov8n.pt')
>>> model = YOLO("yolov8n.pt")
>>> results = model.tune(use_ray=True, iterations=20)
>>> print(results)
"""
@ -907,7 +907,7 @@ class Model(nn.Module):
AttributeError: If the model or predictor does not have a 'names' attribute.
Examples:
>>> model = YOLO('yolov8n.pt')
>>> model = YOLO("yolov8n.pt")
>>> print(model.names)
{0: 'person', 1: 'bicycle', 2: 'car', ...}
"""
@ -957,7 +957,7 @@ class Model(nn.Module):
(object | None): The transform object of the model if available, otherwise None.
Examples:
>>> model = YOLO('yolov8n.pt')
>>> model = YOLO("yolov8n.pt")
>>> transforms = model.transforms
>>> if transforms:
... print(f"Model transforms: {transforms}")
@ -986,9 +986,9 @@ class Model(nn.Module):
Examples:
>>> def on_train_start(trainer):
... print("Training is starting!")
>>> model = YOLO('yolov8n.pt')
>>> model = YOLO("yolov8n.pt")
>>> model.add_callback("on_train_start", on_train_start)
>>> model.train(data='coco128.yaml', epochs=1)
>>> model.train(data="coco128.yaml", epochs=1)
"""
self.callbacks[event].append(func)
@ -1005,9 +1005,9 @@ class Model(nn.Module):
recognized by the Ultralytics callback system.
Examples:
>>> model = YOLO('yolov8n.pt')
>>> model.add_callback('on_train_start', lambda: print('Training started'))
>>> model.clear_callback('on_train_start')
>>> model = YOLO("yolov8n.pt")
>>> model.add_callback("on_train_start", lambda: print("Training started"))
>>> model.clear_callback("on_train_start")
>>> # All callbacks for 'on_train_start' are now removed
Notes:
@ -1035,8 +1035,8 @@ class Model(nn.Module):
modifications, ensuring consistent behavior across different runs or experiments.
Examples:
>>> model = YOLO('yolov8n.pt')
>>> model.add_callback('on_train_start', custom_function)
>>> model = YOLO("yolov8n.pt")
>>> model.add_callback("on_train_start", custom_function)
>>> model.reset_callbacks()
# All callbacks are now reset to their default functions
"""
@ -1059,7 +1059,7 @@ class Model(nn.Module):
(dict): A new dictionary containing only the specified include keys from the input arguments.
Examples:
>>> original_args = {'imgsz': 640, 'data': 'coco.yaml', 'task': 'detect', 'batch': 16, 'epochs': 100}
>>> original_args = {"imgsz": 640, "data": "coco.yaml", "task": "detect", "batch": 16, "epochs": 100}
>>> reset_args = Model._reset_ckpt_args(original_args)
>>> print(reset_args)
{'imgsz': 640, 'data': 'coco.yaml', 'task': 'detect'}
@ -1090,9 +1090,9 @@ class Model(nn.Module):
NotImplementedError: If the specified key is not supported for the current task.
Examples:
>>> model = Model(task='detect')
>>> predictor = model._smart_load('predictor')
>>> trainer = model._smart_load('trainer')
>>> model = Model(task="detect")
>>> predictor = model._smart_load("predictor")
>>> trainer = model._smart_load("trainer")
Notes:
- This method is typically used internally by other methods of the Model class.
@ -1128,8 +1128,8 @@ class Model(nn.Module):
Examples:
>>> model = Model()
>>> task_map = model.task_map
>>> detect_class_map = task_map['detect']
>>> segment_class_map = task_map['segment']
>>> detect_class_map = task_map["detect"]
>>> segment_class_map = task_map["segment"]
Note:
The actual implementation of this method may vary depending on the specific tasks and