e9038bdb76
Hide inappropriate figure title
2024-04-27 15:21:57 +02:00
af947dbf65
Add articles/Euclidean distance - Wikipedia/
2024-04-27 15:08:56 +02:00
5baabae99d
Make mean initialization more general in iterativeMean
2024-04-26 15:56:10 +02:00
1ea1bde910
Leverage iterativeMean in extract_noise.py
2024-04-26 14:25:08 +02:00
674f87d480
Remove unnecessary iterativeMean parentheses and rename addElement to add
2024-04-26 14:22:59 +02:00
7af96d6bf6
Add iterativeMean to utils
...
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
```
2024-04-26 14:16:35 +02:00
7684e1408d
Remove unused imports in split_and_compare_prnus_of_subgroups.py
2024-04-26 13:58:19 +02:00
9c469cf67a
Leverage utils.py denoise in split_and_compare_prnus_of_subgroups.py
2024-04-26 13:58:00 +02:00
9d2903af60
Move denoise from extract_noise.py to utils.py
...
See next commit leveraging it in `split_and_compare_prnus_of_subgroups.py`
2024-04-26 13:57:18 +02:00
6a93b04686
Remove already used previous temporary analysis commit code
2024-04-26 13:49:31 +02:00
b52fff9deb
Add commented code to enforce merging Numpy arrays with a greyscale
...
colormap.
2024-04-26 13:48:44 +02:00
3ffcd33efe
Add Gaussian filter to blur images when using mean as denoiser
...
See
https://docs.scipy.org/doc/scipy-1.13.0/reference/generated/scipy.ndimage.gaussian_filter.html#ba1e4df0-d4be-47c2-81e5-059286837a2b .
2024-04-26 04:39:06 +02:00
9641641b61
Remove commented code from analyze_bayer_filter_mean_denoiser.py
2024-04-26 04:13:08 +02:00
3e8b607b97
Add analyze_bayer_filter_mean_denoiser.py
2024-04-26 04:12:13 +02:00
f1cafc1eb1
Improve yticks of boxplot in flat-field_pointer.py
2024-04-26 04:10:41 +02:00
25b3b30634
Remove a commented print in plot_dates.py
2024-04-26 04:10:02 +02:00
3ada720db9
Add execution results, plot of locations and distance analysis
2024-04-26 03:05:17 +02:00
56037b058b
Add Zoom to rectangle by default
2024-04-26 01:49:57 +02:00
f5c235c3cd
Add support to TIF for RAISE flat-field
2024-04-26 01:49:13 +02:00
ab72da470e
Ready for pointing
2024-04-26 01:34:55 +02:00
981e2a48ae
Add flat-field_pointer.py
...
https://matplotlib.org/3.8.4/gallery/event_handling/coords_demo.html
2024-04-26 01:21:20 +02:00
1e8d9d844c
Make plot_dates.py leverage photo exifs
2024-04-26 00:52:52 +02:00
7cfe566290
Add plot_dates.py as it is as a Matplotlib example
...
https://matplotlib.org/3.8.0/gallery/lines_bars_and_markers/timeline.html
2024-04-26 00:51:12 +02:00
719bb487dd
Restore other than raw images support
2024-04-25 18:12:36 +02:00
f88b6ec1a9
Save mean of each color channel to merge them into a single image being
...
the mean of images
Otherwise for each color channel could use:
```py
plt.imsave(f'{fileName}.png', colorMean)
```
2024-04-25 16:00:23 +02:00
4907d0c0fb
Add and use saveNpArray
2024-04-25 15:59:26 +02:00
65708e4977
Correctly implement mean denoiser
...
Used to have:
```py
imageDenoisedNpArray = imageNpArray - means[color]
imageNoiseNpArray = imageNpArray - imageDenoisedNpArray
```
so:
```py
imageNoiseNpArray = means[color]
```
then we mean the mean...
While should have:
```py
imageDenoisedNpArray = means[color]
```
2024-04-25 15:58:24 +02:00
60a4f78fa6
Ease providing {min,max}Color
2024-04-25 15:30:23 +02:00
c642fa430e
Add commented code to crop image
...
It is commented as it does not seem to be finally what we are looking
for.
2024-04-25 14:37:08 +02:00
674ce8dabe
Use relative path for os.chdir in generate_histogram.py
2024-04-25 14:36:38 +02:00
807f586841
Remove no more relevant print in show_mean_noise.py
2024-04-25 14:28:36 +02:00
5c1f346f2e
Clean single image histogram
...
Source: https://www.codespeedy.com/plot-a-histogram-for-an-image-in-pil-python/
2024-04-25 14:16:58 +02:00
e2602347d4
Use a single figure to generate histogram
2024-04-25 12:39:24 +02:00
ec3ddd9c94
Add generate_histogram.py
2024-04-25 12:37:21 +02:00
Benjamin Loison
a78dcd6f99
Clean extract_noise.py
2024-04-24 14:10:22 +02:00
Benjamin Loison
c65b3642d8
Precise multiple_colors.png file name
2024-04-23 05:01:22 +02:00
be9d4f8f4b
Add denoiser mean possibility
2024-04-23 04:39:28 +02:00
a15b356e16
Add and use getImageNpArray
2024-04-23 04:38:40 +02:00
809aa7fb43
Correct Rafael images filtering
2024-04-23 04:37:46 +02:00
e3bbb2c63d
Precise possibilities for denoiser
2024-04-23 03:57:43 +02:00
fc0cc8808a
Add the missing import numpy as np in merge_single_color_channel_images_according_to_bayer_filter.py
2024-04-23 03:51:56 +02:00
Benjamin Loison
9f2334ceea
Precise imagesFolderPathFileName depending on sky or wall
2024-04-21 19:54:04 +02:00
Benjamin Loison
e2406071d4
Simplify specifying colors
2024-04-21 19:53:21 +02:00
Benjamin Loison
29f3acc479
Enable computing specific colors
...
For instance if have tested on one and do not want to waste its
computation.
2024-04-21 19:52:52 +02:00
9365b58d1d
#49 : Remove intermediary bias by not working on images but numpy arrays instead
2024-04-19 17:21:54 +02:00
675b01271a
#49 : Remove shift per color channel
2024-04-19 17:19:47 +02:00
77330e24d2
Make datasets/raise/merge_single_color_channel_images_according_to_bayer_filter.py production ready
2024-04-18 01:21:31 +02:00
0b52e781e3
First try to merge multiple single color channel images
2024-04-18 01:00:41 +02:00
6aca1126a1
Complete dict assignment
2024-04-18 00:53:15 +02:00
3636335b63
Add match statement
2024-04-18 00:52:08 +02:00
