First iteration of fake dataset generation

datasets/fake/generate_dataset.py

@@ -1,13 +1,24 @@
-from PIL import Image
-import numpy
+import numpy as np
+from matplotlib import pyplot as plt
+import sys
+
+sys.path.insert(0, '../../algorithms/distance/')
+
+from rmsdiff import rmsdiff
 
 IMAGE_SIZE = 64
-MODE = 'L'
 
-IImage = Image.new(MODE, (IMAGE_SIZE, IMAGE_SIZE))
-I = IImage.load()
-for y in range(IMAGE_SIZE):
-    for x in range(IMAGE_SIZE):
-        I[y, x] = numpy.random.normal(loc = 0, scale = 1, size = 1)
+def randomImage(scale):
+    # Is `np.clip` necessary?
+    return np.round(np.random.normal(loc = 0, scale = scale, size = (IMAGE_SIZE, IMAGE_SIZE)))
 
-I.show()
+prnu = randomImage(scale = 1)
+
+plt.imshow(prnu)
+plt.show()
+
+images = [randomImage(scale = 10) + prnu for _ in range(10)]
+
+for image in images:
+    print(rmsdiff(image, prnu))
+    print(rmsdiff(contextAdaptiveInterpolator(image), prnu))