diff --git a/datasets/raise/extract_noise.py b/datasets/raise/extract_noise.py index ad6aad2..3ab80aa 100755 --- a/datasets/raise/extract_noise.py +++ b/datasets/raise/extract_noise.py @@ -58,7 +58,7 @@ def getImageFilePath(imageFileName): def treatImage(imageFileName, computeExtremes = False, color = None): global estimatedPrnuIterativeMean imageFilePath = getImageFilePath(imageFileName) - imageNpArray = getImageNpArray(imageFilePath, computeExtremes, color) + imageNpArray = getImageNpArray(imageFilePath, computeExtremes, color, DENOISER) if imageNpArray is None: return if DENOISER != 'mean': @@ -80,7 +80,7 @@ if (minColor is None or maxColor is None) and DENOISER != 'mean': print(f'{maxColor=}') if DENOISER == 'mean': - colorMeans = getColorMeans(imagesFileNames, COLORS) + colorMeans = getColorMeans(imagesFileNames, COLORS, DENOISER) for color in Color: colorMeans[color] = colorMeans[color] fileName = f'mean_{imagesFolderPathFileName}_{color}' diff --git a/datasets/raise/utils.py b/datasets/raise/utils.py index 4b33340..4121024 100644 --- a/datasets/raise/utils.py +++ b/datasets/raise/utils.py @@ -132,18 +132,18 @@ def updateExtremes(imageNpArray, minColor, maxColor): def print(*toPrint): __builtin__.print(datetime.now(), *toPrint) -def getColorMeans(imagesFileNames, colors = Color): +def getColorMeans(imagesFileNames, colors, denoiser): colorMeans = {} for color in colors: colorIterativeMean = iterativeMean() for imageFileName in tqdm(imagesFileNames, f'Computing mean of {color} colored images'): - imageNpArray = getImageNpArray(imageFileName, False, color) + imageNpArray = getImageNpArray(imageFileName, False, color, denoiser) imageNpArray = gaussian_filter(imageNpArray, sigma = 5) colorIterativeMean.add(imageNpArray) colorMeans[color] = colorIterativeMean.mean return colorMeans -def getImageNpArray(imageFilePath, computeExtremes, color): +def getImageNpArray(imageFilePath, computeExtremes, color, denoiser): global minColor, maxColor imageNpArray = getColorChannel(imageFilePath, color)