WIP: Add .nef support

datasets/raise/extract_noise.py

@@ -7,10 +7,12 @@ from PIL import Image
 import os
 from tqdm import tqdm
 import csv
+import rawpy
 
-imagesFolderPath = 'raise_nef_png'
+imagesFolderPath = 'flat-field/nef'
+imagesFolderPathFileName = imagesFolderPath.replace('/', '_')
 denoiser = 'wavelet'
-npArrayFilePath = f'mean_{imagesFolderPath}_{denoiser}.npy'
+npArrayFilePath = f'mean_{imagesFolderPathFileName}_{denoiser}.npy'
 
 denoise = getattr(skimage.restoration, f'denoise_{denoiser}')
 
@@ -34,8 +36,28 @@ if requiresRaiseFiltering:
 def treatImage(imageFileName):
     global mean, numberOfImagesInMean
     imageFilePath = f'{imagesFolderPath}/{imageFileName}'
-    imagePil = Image.open(imageFilePath)
-    imageNpArray = img_as_float(np.array(imagePil))
+    if imageFileName.endswith('.NEF'):
+        imageFileName = 'r01b6aed6t.NEF'
+        imageFilePath = f'{imagesFolderPath}/{imageFileName}'
+        with rawpy.imread(imageFilePath) as raw:
+            colorDesc = raw.color_desc.decode('ascii')
+            assert colorDesc == 'RGBG'
+            rawImageVisible = raw.raw_image_visible.copy()
+            centerY = 628
+            centerX = 3_014
+            RANGE = 5
+            rawImageVisible = rawImageVisible.astype(np.float64)
+            rawImageVisibleShape = rawImageVisible.shape
+            for y in range(0, rawImageVisibleShape[0], 2):
+                for x in range(0, rawImageVisibleShape[1], 2):
+                    rawImageVisible[y, x] *= -1
+            print(rawImageVisible[centerY - RANGE:centerY + RANGE, centerX - RANGE:centerX + RANGE])
+            #greenRawImageVisible = raw.rawImageVisible
+            # Pay attention to range of values expected by the denoiser.
+            exit(1)
+    else:
+        imagePil = Image.open(imageFilePath)
+        imageNpArray = img_as_float(np.array(imagePil))
     # As the arguments differ from a denoiser to the other should use a match instead.
     imageDenoisedNpArray = denoise(imageNpArray, channel_axis=-1, convert2ycbcr=True, rescale_sigma=True)
     imageNoiseNpArray = imageNpArray - imageDenoisedNpArray