Benjamin_Loison/Robust_image_source_identification_on_modern_smartphones
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Use v{min,max} for enforcing matplotlib colormap

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If it proceeds linearly to *covers the complete value range of the supplied data* then doing so is unnecessary and even if it is another not very different scale transformation then it is still fine for my goal.
This commit is contained in:
Benjamin Loison 2024-03-29 12:11:41 +01:00
parent 5fa61f7ff8
commit b375acbb3a
Signed by: Benjamin_Loison
SSH Key Fingerprint: SHA256:BtnEgYTlHdOg1u+RmYcDE0mnfz1rhv5dSbQ2gyxW8B8
2 changed files with 11 additions and 3 deletions
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5
algorithms/image_utils/image_utils.py
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@ -5,10 +5,11 @@ from matplotlib import pyplot as plt
def randomGaussianImage(scale, size):
return np.random.normal(loc = 0, scale = scale, size = size)
def showImageWithMatplotlib(npArray, title = None):
# `cmap` source: https://matplotlib.org/3.8.0/api/_as_gen/matplotlib.pyplot.imshow.html
def showImageWithMatplotlib(npArray, title = None, cmap = 'viridis'):
if title is not None:
plt.title(title)
plt.imshow(npArray)
plt.imshow(npArray, cmap = cmap)
plt.show()
def toPilImage(npArray):

9
datasets/noise_free_test_images/estimate_prnu.py
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@ -62,5 +62,12 @@ for imageName in os.listdir(datasetPath):
cameraPrnuEstimateNpArray = np.array(imagesPrnuEstimateNpArray).mean(axis = 0)
rms = rmsDiffNumpy(cameraPrnuEstimateNpArray, prnuNpArray, True)
showImageWithMatplotlib(cameraPrnuEstimateNpArray, f'Camera PRNU estimate\nRMS with actual one: {rmsDiffNumpy(cameraPrnuEstimateNpArray, prnuNpArray):.4f} (normalized RMS: {rmsDiffNumpy(cameraPrnuEstimateNpArray, prnuNpArray, True):.4f})')
title = f'Camera PRNU estimate\nRMS with actual one: {rmsDiffNumpy(cameraPrnuEstimateNpArray, prnuNpArray):.4f} (normalized RMS: {rmsDiffNumpy(cameraPrnuEstimateNpArray, prnuNpArray, True):.4f})'
showImageWithMatplotlib(cameraPrnuEstimateNpArray, title)
_256RangeCameraPrnuEstimateNpArray = cameraPrnuEstimateNpArray - cameraPrnuEstimateNpArray.min()
_256RangeCameraPrnuEstimateNpArray *= 255 / _256RangeCameraPrnuEstimateNpArray.max()
#showImageWithMatplotlib(_256RangeCameraPrnuEstimateNpArray, title, 'gray')
plt.imshow(_256RangeCameraPrnuEstimateNpArray, cmap = 'gray', vmin = 0, vmax = 255)
plt.show()