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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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63 changed files with 370 additions and 374 deletions
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22
ultralytics/models/sam/model.py
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@ -41,8 +41,8 @@ class SAM(Model):
info: Logs information about the SAM model.
Examples:
>>> sam = SAM('sam_b.pt')
>>> results = sam.predict('image.jpg', points=[[500, 375]])
>>> sam = SAM("sam_b.pt")
>>> results = sam.predict("image.jpg", points=[[500, 375]])
>>> for r in results:
>>> print(f"Detected {len(r.masks)} masks")
"""
@ -58,7 +58,7 @@ class SAM(Model):
NotImplementedError: If the model file extension is not .pt or .pth.
Examples:
>>> sam = SAM('sam_b.pt')
>>> sam = SAM("sam_b.pt")
>>> print(sam.is_sam2)
"""
if model and Path(model).suffix not in {".pt", ".pth"}:
@ -78,8 +78,8 @@ class SAM(Model):
task (str | None): Task name. If provided, it specifies the particular task the model is being loaded for.
Examples:
>>> sam = SAM('sam_b.pt')
>>> sam._load('path/to/custom_weights.pt')
>>> sam = SAM("sam_b.pt")
>>> sam._load("path/to/custom_weights.pt")
"""
self.model = build_sam(weights)
@ -100,8 +100,8 @@ class SAM(Model):
(List): The model predictions.
Examples:
>>> sam = SAM('sam_b.pt')
>>> results = sam.predict('image.jpg', points=[[500, 375]])
>>> sam = SAM("sam_b.pt")
>>> results = sam.predict("image.jpg", points=[[500, 375]])
>>> for r in results:
... print(f"Detected {len(r.masks)} masks")
"""
@ -130,8 +130,8 @@ class SAM(Model):
(List): The model predictions, typically containing segmentation masks and other relevant information.
Examples:
>>> sam = SAM('sam_b.pt')
>>> results = sam('image.jpg', points=[[500, 375]])
>>> sam = SAM("sam_b.pt")
>>> results = sam("image.jpg", points=[[500, 375]])
>>> print(f"Detected {len(results[0].masks)} masks")
"""
return self.predict(source, stream, bboxes, points, labels, **kwargs)
@ -151,7 +151,7 @@ class SAM(Model):
(Tuple): A tuple containing the model's information (string representations of the model).
Examples:
>>> sam = SAM('sam_b.pt')
>>> sam = SAM("sam_b.pt")
>>> info = sam.info()
>>> print(info[0]) # Print summary information
"""
@ -167,7 +167,7 @@ class SAM(Model):
class. For SAM2 models, it maps to SAM2Predictor, otherwise to the standard Predictor.
Examples:
>>> sam = SAM('sam_b.pt')
>>> sam = SAM("sam_b.pt")
>>> task_map = sam.task_map
>>> print(task_map)
{'segment': <class 'ultralytics.models.sam.predict.Predictor'>}