add xlib.avecl

xlib/avecl/_internal/op/binary_morph.py

@@ -0,0 +1,43 @@
+from ..Tensor import Tensor
+from .binary_dilate_circle import binary_dilate_circle
+from .binary_erode_circle import binary_erode_circle
+from .gaussian_blur import gaussian_blur
+from .pad import pad
+
+
+def binary_morph(input_t : Tensor, erode_dilate : int, blur : float, fade_to_border : bool = False, dtype=None) -> Tensor:
+    """
+    Apply optional binary erode/dilate and optional blur.
+
+        input_t    (...,H,W) tensor. Non zero values will be treated as 1.
+
+        erode_dilate    int     >= 0    amount of pixels to dilate
+
+        blur            float   >= 0    amount of pixels to blur
+
+        fade_to_border(False)   clip the image in order
+                                to fade smoothly to the border with specified blur amount
+    """
+    x = input_t
+
+    H,W = input_t.shape[-2:]
+
+    x = pad(x, (...,(H,H),(W,W)), mode='constant', constant_value=0)
+
+    if erode_dilate > 0:
+        x = binary_erode_circle(x, radius=1, iterations=max(1,erode_dilate//2))
+    elif erode_dilate < 0:
+        x = binary_dilate_circle(x, radius=1, iterations=max(1,-erode_dilate//2) )
+
+    if fade_to_border:
+        h_clip_size = H + blur // 2
+        w_clip_size = W + blur // 2
+        x[...,:h_clip_size,:] = 0
+        x[...,-h_clip_size:,:] = 0
+        x[...,:,:w_clip_size] = 0
+        x[...,:,-w_clip_size:] = 0
+
+    if blur > 0:
+        x = gaussian_blur(x, blur * 0.250, dtype=dtype)
+
+    return x[...,H:-H,W:-W]