imagelib : apply_random_sharpen

core/imagelib/__init__.py

@@ -22,6 +22,7 @@ from .blursharpen import LinearMotionBlur, blursharpen
 
 from .filters import apply_random_rgb_levels, \
                      apply_random_hsv_shift, \
+                     apply_random_sharpen, \
                      apply_random_motion_blur, \
                      apply_random_gaussian_blur, \
                      apply_random_nearest_resize, \

core/imagelib/filters.py

@@ -1,5 +1,5 @@
 import numpy as np
-from .blursharpen import LinearMotionBlur
+from .blursharpen import LinearMotionBlur, blursharpen
 import cv2
 
 def apply_random_rgb_levels(img, mask=None, rnd_state=None):
@@ -38,6 +38,24 @@ def apply_random_hsv_shift(img, mask=None, rnd_state=None):
 
     return result
 
+def apply_random_sharpen( img, chance, kernel_max_size, mask=None, rnd_state=None ):
+    if rnd_state is None:
+        rnd_state = np.random
+
+    sharp_rnd_kernel = rnd_state.randint(kernel_max_size)+1
+
+    result = img
+    if rnd_state.randint(100) < np.clip(chance, 0, 100):
+        if rnd_state.randint(2) == 0:
+            result = blursharpen(result, 1, sharp_rnd_kernel, rnd_state.randint(10) )
+        else:
+            result = blursharpen(result, 2, sharp_rnd_kernel, rnd_state.randint(50) )
+                
+        if mask is not None:
+            result = img*(1-mask) + result*mask
+
+    return result
+
 def apply_random_motion_blur( img, chance, mb_max_size, mask=None, rnd_state=None ):
     if rnd_state is None:
         rnd_state = np.random