Automatic page splitting

copienator/paper_ruling.py

@@ -93,7 +93,6 @@ def ruling_suppression(rgb: np.ndarray, dpi: float):
     matrix[:,2] -= origin
     image = cv2.warpAffine(rgb, matrix, tuple(size), borderValue=(255,255,255))
     dark = 255-image
-    dark16 = dark.astype(np.int16)
     darkness = _maximum(dark)
     binary = cv2.adaptiveThreshold(_minimum(image), 255,
         cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY_INV,
@@ -119,7 +118,7 @@ def ruling_suppression(rgb: np.ndarray, dpi: float):
         support = _maximum(model) > 9
         if count:
             support &= bands > 0
-        close = _maximum(np.abs(dark16-model.astype(np.int16))) < 40
+        close = _maximum(cv2.absdiff(dark,model)) < 40
         sample = support & (darkness > 9) & close & ~thick
         # Neutral, red, green and blue line families are modelled separately so
         # a red margin rule cannot be mistaken for unusually dark blue writing.
@@ -128,7 +127,10 @@ def ruling_suppression(rgb: np.ndarray, dpi: float):
         classes[second <= third] = 1
         classes[(first <= second) & (first <= third)] = 0
         classes[cv2.subtract(_maximum(model),_minimum(model)) < 25] = 3
-        credible = np.zeros(binary.shape, bool)
+        # Rejected classes have ceiling -1, below every uint8 darkness value.
+        # Compute each class ceiling once, then test pixels by lookup instead
+        # of subtracting and splitting full RGB images for every colour class.
+        ceilings = np.full((4,3),-1,np.int16)
         for colour in range(4):
             selected = sample & (classes == colour)
             if selected.sum() < 100:
@@ -143,9 +145,10 @@ def ruling_suppression(rgb: np.ndarray, dpi: float):
             # An isolated long fraction bar must not define its own paper colour.
             # The upper quantile admits darker major rules within an established
             # family while rejecting excess ink on most of its pixels.
-            ceiling = np.floor(np.quantile(dark[selected],.99,axis=0)+25).astype(np.int16)
-            credible |= ((classes == colour)
-                         & (_maximum(dark16-ceiling) <= 0))
+            ceilings[colour] = np.floor(np.quantile(dark[selected],.99,axis=0)+25).astype(np.int16)
+        credible = ((dark[:,:,0] <= ceilings[classes,0])
+                    & (dark[:,:,1] <= ceilings[classes,1])
+                    & (dark[:,:,2] <= ceilings[classes,2]))
         match = close & credible & (darkness > 9) & ~thick
         removed |= support & match
         protected |= support & ~match & (binary > 0)