diff --git a/datasets/raise/extract_noise.py b/datasets/raise/extract_noise.py
index 4e12825..5a51a80 100755
--- a/datasets/raise/extract_noise.py
+++ b/datasets/raise/extract_noise.py
@@ -9,7 +9,7 @@ from tqdm import tqdm
 import csv
 import rawpy
 
-imagesFolderPath = '/mnt/HDD0/raise'
+imagesFolderPath = '/mnt/HDD0/raise/nef'
 imagesFolderPathFileName = imagesFolderPath.replace('/', '_')
 denoiser = 'wavelet'
 npArrayFilePath = f'mean_{imagesFolderPathFileName}_{denoiser}.npy'
@@ -19,7 +19,9 @@ denoise = getattr(skimage.restoration, f'denoise_{denoiser}')
 mean = None
 numberOfImagesInMean = 0
 
-imagesFileNames = os.listdir(imagesFolderPath + '/png')
+imagesFileNames = os.listdir(imagesFolderPath)
+#print(rawpy.imread(f'{imagesFolderPath}/{imagesFileNames[0]}').sizes.raw_height)
+#exit(1)
 
 requiresRaiseFiltering = True
 if requiresRaiseFiltering:
@@ -28,10 +30,10 @@ if requiresRaiseFiltering:
     with open('RAISE_all.csv') as csvfile:
         reader = csv.DictReader(csvfile)
         for row in tqdm(list(reader), 'CSV parsing'):
-            file = row['File'] + '.png'
+            file = row['File'] + '.NEF'
             files[file] = row
 
-    imagesFileNames = [imageFileName for imageFileName in tqdm(imagesFileNames, 'Filtering images') if files[imageFileName]['Device'] == 'Nikon D7000' and Image.open(f'{imagesFolderPath}/png/{imageFileName}').size == (4946, 3278)]
+    imagesFileNames = [imageFileName for imageFileName in tqdm(imagesFileNames, 'Filtering images') if files[imageFileName]['Device'] == 'Nikon D7000' and [getattr(rawpy.imread(f'{imagesFolderPath}/{imageFileName}').sizes, dimension) for dimension in ['width', 'height']] == [4992, 3280]]
 #imagesFileNames = [f'DSC0{imageIndex}.ARW' for imageIndex in range(2807, 2911)]
 
 minColor = None