HongChuang/ultralytics-ascend
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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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commit d27664216b
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63 changed files with 370 additions and 374 deletions
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20
ultralytics/models/sam/predict.py
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@ -69,8 +69,8 @@ class Predictor(BasePredictor):
Examples:
>>> predictor = Predictor()
>>> predictor.setup_model(model_path='sam_model.pt')
>>> predictor.set_image('image.jpg')
>>> predictor.setup_model(model_path="sam_model.pt")
>>> predictor.set_image("image.jpg")
>>> masks, scores, boxes = predictor.generate()
>>> results = predictor.postprocess((masks, scores, boxes), im, orig_img)
"""
@ -90,8 +90,8 @@ class Predictor(BasePredictor):
Examples:
>>> predictor = Predictor(cfg=DEFAULT_CFG)
>>> predictor = Predictor(overrides={'imgsz': 640})
>>> predictor = Predictor(_callbacks={'on_predict_start': custom_callback})
>>> predictor = Predictor(overrides={"imgsz": 640})
>>> predictor = Predictor(_callbacks={"on_predict_start": custom_callback})
"""
if overrides is None:
overrides = {}
@ -188,8 +188,8 @@ class Predictor(BasePredictor):
Examples:
>>> predictor = Predictor()
>>> predictor.setup_model(model_path='sam_model.pt')
>>> predictor.set_image('image.jpg')
>>> predictor.setup_model(model_path="sam_model.pt")
>>> predictor.set_image("image.jpg")
>>> masks, scores, logits = predictor.inference(im, bboxes=[[0, 0, 100, 100]])
"""
# Override prompts if any stored in self.prompts
@ -475,8 +475,8 @@ class Predictor(BasePredictor):
Examples:
>>> predictor = Predictor()
>>> predictor.setup_source('path/to/images')
>>> predictor.setup_source('video.mp4')
>>> predictor.setup_source("path/to/images")
>>> predictor.setup_source("video.mp4")
>>> predictor.setup_source(None) # Uses default source if available
Notes:
@ -504,8 +504,8 @@ class Predictor(BasePredictor):
Examples:
>>> predictor = Predictor()
>>> predictor.set_image('path/to/image.jpg')
>>> predictor.set_image(cv2.imread('path/to/image.jpg'))
>>> predictor.set_image("path/to/image.jpg")
>>> predictor.set_image(cv2.imread("path/to/image.jpg"))
Notes:
- This method should be called before performing inference on a new image.