Update Scripts/image_processing.py

Scripts/image_processing.py

@@ -1,27 +1,26 @@
-
-import cv2
-import numpy as np
-
-def modulo(x, L):
-    positive = x > 0
-    x = x % L
-    x = np.where( ( x == 0) &  positive, L, x)
-    return x
-
-def apply_blur(image, kernel_size):
-    """Aplica desenfoque gaussiano a la imagen."""
-    return cv2.GaussianBlur(image, (kernel_size, kernel_size), 0)
-
-def clip_image(image, correction, sat_factor):
-    """Clips image with saturation factor and correction."""
-    processed_image = np.power(image, correction) * sat_factor
-    clipped_image = np.clip(processed_image, 0, 1)
-    return clipped_image
-
-def wrap_image(image, correction, sat_factor):
-    """Wraps image with saturation factor and correction."""
-    processed_image = np.power(image, 1.0) * sat_factor
-    wrapped_image =  modulo(processed_image, 1.0)
-    return wrapped_image
-
-
+import cv2
+import numpy as np
+
+def modulo(x, L):
+    positive = x > 0
+    x = x % L
+    x = np.where( ( x == 0) &  positive, L, x)
+    return x
+
+def apply_blur(image, kernel_size):
+    """Aplica desenfoque gaussiano a la imagen."""
+    return cv2.GaussianBlur(image, (kernel_size, kernel_size), 0)
+
+def clip_image(image, correction, sat_factor):
+    """Clips image with saturation factor and correction."""
+    processed_image = np.power(image, correction) * sat_factor
+    clipped_image = np.clip(processed_image, 0, 1)
+    return clipped_image
+
+def wrap_image(image, correction, sat_factor):
+    """Wraps image with saturation factor and correction."""
+    processed_image = np.power(image, 1.0) * sat_factor
+    wrapped_image =  modulo(processed_image, 1.0)
+    return wrapped_image
+
+