replace patches string comparison with use_patches boolean

sbb_binarize/ocrd_cli.py

@@ -50,7 +50,7 @@ class SbbBinarizeProcessor(Processor):
         oplevel = self.parameter['operation_level']
         use_patches = self.parameter['patches'] # pylint: disable=attribute-defined-outside-init
         model_path = self.parameter['model'] # pylint: disable=attribute-defined-outside-init
-        binarizer = SbbBinarizer(model_dir=self.model_path)
+        binarizer = SbbBinarizer(model_dir=model_path)
 
         for n, input_file in enumerate(self.input_files):
             file_id = make_file_id(input_file, self.output_file_grp)
@@ -64,7 +64,7 @@ class SbbBinarizeProcessor(Processor):
             if oplevel == 'page':
                 LOG.info("Binarizing on 'page' level in page '%s'", page_id)
                 page_image, page_xywh, _ = self.workspace.image_from_page(page, page_id, feature_filter='binarized')
-                bin_image = cv2pil(binarizer.run(image=pil2cv(page_image), patches=use_patches))
+                bin_image = cv2pil(binarizer.run(image=pil2cv(page_image), use_patches=use_patches))
                 # update METS (add the image file):
                 bin_image_path = self.workspace.save_image_file(bin_image,
                         file_id + '.IMG-BIN',
@@ -78,7 +78,7 @@ class SbbBinarizeProcessor(Processor):
                     LOG.warning("Page '%s' contains no text/table regions", page_id)
                 for region in regions:
                     region_image, region_xywh = self.workspace.image_from_segment(region, page_image, page_xywh, feature_filter='binarized')
-                    region_image_bin = cv2pil(binarizer.run(image=pil2cv(region_image), patches=use_patches))
+                    region_image_bin = cv2pil(binarizer.run(image=pil2cv(region_image), use_patches=use_patches))
                     region_image_bin_path = self.workspace.save_image_file(
                             region_image_bin,
                             "%s_%s.IMG-BIN" % (file_id, region.id),
@@ -93,7 +93,7 @@ class SbbBinarizeProcessor(Processor):
                     LOG.warning("Page '%s' contains no text lines", page_id)
                 for region_id, line in region_line_tuples:
                     line_image, line_xywh = self.workspace.image_from_segment(line, page_image, page_xywh, feature_filter='binarized')
-                    line_image_bin = cv2pil(binarizer.run(image=pil2cv(line_image), patches=use_patches))
+                    line_image_bin = cv2pil(binarizer.run(image=pil2cv(line_image), use_patches=use_patches))
                     line_image_bin_path = self.workspace.save_image_file(
                             line_image_bin,
                             "%s_%s_%s.IMG-BIN" % (file_id, region_id, line.id),

sbb_binarize/sbb_binarize.py

@@ -42,10 +42,10 @@ class SbbBinarizer:
         n_classes = model.layers[len(model.layers)-1].output_shape[3]
         return model, model_height, model_width, n_classes
 
-    def predict(self, model_name, img, patches):
+    def predict(self, model_name, img, use_patches):
         model, model_height, model_width, n_classes = self.load_model(model_name)
 
-        if patches in ('true', 'True'):
+        if use_patches:
 
             margin = int(0.1 * model_width)
 
@@ -184,8 +184,7 @@ class SbbBinarizer:
             prediction_true = prediction_true.astype(np.uint8)
         return prediction_true[:,:,0]
 
-    # TODO use True/False for patches
+    def run(self, image=None, image_path=None, save=None, use_patches=False):
-    def run(self, image=None, image_path=None, save=None, patches='false'):
         if (image is not None and image_path is not None) or \
                (image is None and image_path is None):
             raise ValueError("Must pass either a opencv2 image or an image_path")
@@ -196,7 +195,7 @@ class SbbBinarizer:
         img_last = 0
         for model_in in list_of_model_files:
 
-            res = self.predict(model_in, image, patches)
+            res = self.predict(model_in, image, use_patches)
 
             img_fin = np.zeros((res.shape[0], res.shape[1], 3))
             res[:, :][res[:, :] == 0] = 2