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Model coverage cleanup (#4585)

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Glenn Jocher 2023-08-27 04:19:41 +02:00 • committed by GitHub
parent c635418a27
commit deac7575b1
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12 changed files with 132 additions and 175 deletions
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18
ultralytics/models/sam/modules/sam.py
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@ -20,12 +20,14 @@ class Sam(nn.Module):
mask_threshold: float = 0.0
image_format: str = 'RGB'
def __init__(self,
image_encoder: ImageEncoderViT,
prompt_encoder: PromptEncoder,
mask_decoder: MaskDecoder,
pixel_mean: List[float] = None,
pixel_std: List[float] = None) -> None:
def __init__(
self,
image_encoder: ImageEncoderViT,
prompt_encoder: PromptEncoder,
mask_decoder: MaskDecoder,
pixel_mean: List[float] = (123.675, 116.28, 103.53),
pixel_std: List[float] = (58.395, 57.12, 57.375)
) -> None:
"""
SAM predicts object masks from an image and input prompts.
@ -37,10 +39,6 @@ class Sam(nn.Module):
pixel_mean (list(float)): Mean values for normalizing pixels in the input image.
pixel_std (list(float)): Std values for normalizing pixels in the input image.
"""
if pixel_mean is None:
pixel_mean = [123.675, 116.28, 103.53]
if pixel_std is None:
pixel_std = [58.395, 57.12, 57.375]
super().__init__()
self.image_encoder = image_encoder
self.prompt_encoder = prompt_encoder