noises¶
Features for introducing noise to images.
Classes¶
- Noise
Base abstract noise class.
- Offset, Add, Background
Adds a constant value to an image.
- Gaussian
Adds IID Gaussian noise to an image.
- Poisson
Adds Poisson-distributed noise to an image.
Module classes¶
Add¶
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class
deeptrack.noises.Add(offset, **kwargs)¶ Adds a constant value to an image :param offset: The value to add to the image :type offset: float
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get(image, offset, **kwargs)¶ Method for altering an image Abstract method that define how the feature transforms the input. The current value of all properties will be passed as keyword arguments.
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Background¶
-
deeptrack.noises.Background¶ alias of
deeptrack.noises.Add
Gaussian¶
-
class
deeptrack.noises.Gaussian(*args, mu, sigma, **kwargs)¶ Adds IID Gaussian noise to an image
- Parameters
mu (float) – The mean of the distribution.
sigma (float) – The root of the variance of the distribution.
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get(image, mu, sigma, **kwargs)¶ Method for altering an image Abstract method that define how the feature transforms the input. The current value of all properties will be passed as keyword arguments.
Offset¶
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deeptrack.noises.Offset¶ alias of
deeptrack.noises.Add
Poisson¶
-
class
deeptrack.noises.Poisson(*args: dict, **kwargs)¶ Adds Poisson-distributed noise to an image
- Parameters
snr (float) – Signal to noise ratio of the final image. The signal is determined by the peak value of the image.
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get(image, snr=None, **kwargs)¶ Method for altering an image Abstract method that define how the feature transforms the input. The current value of all properties will be passed as keyword arguments.