Benjamin Loison
7af96d6bf6
Verified with:
```py
myIterativeMean = iterativeMean()
print(myIterativeMean.mean)
myIterativeMean.addElement(2)
print(myIterativeMean.mean)
myIterativeMean.addElement(3)
print(myIterativeMean.mean)
```
Note that cannot simplify as follows in the general case of using images as
`element`s for instance:
```diff
diff --git a/datasets/raise/utils.py b/datasets/raise/utils.py
index fba5523..a116edb 100644
--- a/datasets/raise/utils.py
+++ b/datasets/raise/utils.py
@@ -27,12 +27,9 @@ def denoise(imageNpArray, denoiserName):
return imageDenoisedNpArray
class iterativeMean():
- mean = None
+ mean = 0
numberOfElementsInMean = 0
def addElement(self, element):
- if self.mean is None:
- self.mean = element
- else:
- self.mean = ((self.mean * self.numberOfElementsInMean) + element) / (self.numberOfElementsInMean + 1)
+ self.mean = ((self.mean * self.numberOfElementsInMean) + element) / (self.numberOfElementsInMean + 1)
self.numberOfElementsInMean += 1
\ No newline at end of file
```
35 lines
1.1 KiB
Python
35 lines
1.1 KiB
Python
from enum import Enum, auto
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import skimage.restoration
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class Color(Enum):
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RED = auto()
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GREEN_RIGHT = auto()
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GREEN_BOTTOM = auto()
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BLUE = auto()
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def __str__(self):
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return self.name.lower()
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# Among:
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# - `wavelet`
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# - `bilateral`
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# - `tv_chambolle`
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def denoise(imageNpArray, denoiserName):
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skImageRestorationDenoise = getattr(skimage.restoration, f'denoise_{denoiserName}')
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match denoiserName:
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case 'wavelet':
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imageDenoisedNpArray = skImageRestorationDenoise(imageNpArray, rescale_sigma=True)
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case 'bilateral':
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imageDenoisedNpArray = skImageRestorationDenoise(imageNpArray, sigma_color=0.05, sigma_spatial=15)
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case 'tv_chambolle':
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imageDenoisedNpArray = skImageRestorationDenoise(imageNpArray, weight=0.2)
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return imageDenoisedNpArray
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class iterativeMean():
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mean = 0
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numberOfElementsInMean = 0
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def addElement(self, element):
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self.mean = ((self.mean * self.numberOfElementsInMean) + element) / (self.numberOfElementsInMean + 1)
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self.numberOfElementsInMean += 1 |