From 8d260488b424959bca055ff7344ebe0c5202e619 Mon Sep 17 00:00:00 2001
From: Luis Salamanca <luis.salamanca@sdsc.ethz.ch>
Date: Sun, 9 Dec 2018 09:59:30 +0000
Subject: [PATCH] Possibility of only plotting lines or text boxes

---
 notebooks/RunningClasses.ipynb | 18 +++++++++++++++---
 src/python/def_classes.py      |  6 +++---
 src/python/plot_tools.py       | 13 ++++++++-----
 3 files changed, 26 insertions(+), 11 deletions(-)

diff --git a/notebooks/RunningClasses.ipynb b/notebooks/RunningClasses.ipynb
index 69544230..c309d00b 100755
--- a/notebooks/RunningClasses.ipynb
+++ b/notebooks/RunningClasses.ipynb
@@ -413,9 +413,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 178,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 576x720 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "d1.plot_margins_doc(range_pages = [0], suffix_xml = '_data', flag_plot = 1, flag_save_figs = 0)"
    ]
@@ -498,7 +509,8 @@
     }
    ],
    "source": [
-    "d1.plot_XMLcorrect(range_pages = [0,1], suffix_xml = '_data', flag_plot = 1, flag_save_figs = 0, flag_compute = 0)"
+    "d1.plot_XMLcorrect(range_pages = [0,1], suffix_xml = '_data', flag_plot = 1, \n",
+    "                   flag_save_figs = 0, flag_compute = 0, flag_lines_textl = 1)"
    ]
   },
   {
diff --git a/src/python/def_classes.py b/src/python/def_classes.py
index 34724e00..d3f3962f 100644
--- a/src/python/def_classes.py
+++ b/src/python/def_classes.py
@@ -583,8 +583,8 @@ class Document:
                 
     def plot_XMLcorrect(self, range_pages = range(1), suffix_xml = '_data', 
                         flag_plot = 1, flag_save_figs = 0, name_outxml = '02_extractedxml',
-                        name_outcorrxml = '04_correctedxml', flag_compute = 0):
-        
+                        name_outcorrxml = '04_correctedxml', flag_compute = 0, flag_lines_textl = 1):
+        # flag_lines_textl, if 1, plots lines and textboxes, if 2, only lines, if 3, only textboxes
         if 'name_outxml' not in self.__dict__.keys():
             self.name_outxml = name_outxml
         if 'name_outcorrxml' not in self.__dict__.keys():
@@ -603,7 +603,7 @@ class Document:
             if flag_error:
                 print(str(ind_page) + ': non existing page!')
             else:            
-                im_met = plot_tools.plot_correctedXML(imarray, XML_enrich, bbox_page)
+                im_met = plot_tools.plot_correctedXML(imarray, XML_enrich, bbox_page, flag_lines_textl)
 
                 self._plot_save(im_met, 'XML corrected', 'XMLcorrect', ind_page, self.path_file,
                        flag_plot, flag_save_figs)
diff --git a/src/python/plot_tools.py b/src/python/plot_tools.py
index 5fc8c1a3..878f065f 100644
--- a/src/python/plot_tools.py
+++ b/src/python/plot_tools.py
@@ -226,7 +226,8 @@ def plot_horzvertlines(img, coord_horz, coord_vert_def):
     
     return img_lines
 
-def plot_correctedXML(img, XML_enrich, bbox_page):
+def plot_correctedXML(img, XML_enrich, bbox_page, flag_lines_textl = 1):
+    # flag_lines_textl, if 1, plots lines and textboxes, if 2, only lines, if 3, only textboxes
     # Essentially plotting the corrected textboxes and the lines from the
     # final xml
     img_xml = np.copy(img)
@@ -234,10 +235,12 @@ def plot_correctedXML(img, XML_enrich, bbox_page):
         if XML_enrich[0][ind_el].tag == 'textbox':
             if 'bbox' in XML_enrich[0][ind_el].attrib:
                 coord_textbox = np.array(XML_enrich[0][ind_el].attrib['bbox'].split(',')).astype(np.float64)
-                if XML_enrich[0][ind_el].attrib['type_textbox'] == 'line':
-                    img_xml = highlight_text(img_xml, coord_textbox, bbox_page, color_vec = 'blue', alpha = True, filled = False, thick_line = 6) 
-                if XML_enrich[0][ind_el].attrib['type_textbox'] == 'text':
-                    img_xml = highlight_text(img_xml, coord_textbox, bbox_page, color_vec = 'red', alpha = True, filled = False, thick_line = 6) 
+                if flag_lines_textl < 3:
+                    if XML_enrich[0][ind_el].attrib['type_textbox'] == 'line':
+                        img_xml = highlight_text(img_xml, coord_textbox, bbox_page, color_vec = 'blue', alpha = True, filled = False, thick_line = 6)
+                if (flag_lines_textl == 1) or (flag_lines_textl == 3):
+                    if XML_enrich[0][ind_el].attrib['type_textbox'] == 'text':
+                        img_xml = highlight_text(img_xml, coord_textbox, bbox_page, color_vec = 'red', alpha = True, filled = False, thick_line = 6) 
     return img_xml
 
 def plot_save_parallel(folder_pickles):
-- 
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