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gt_gen_utils.py
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import click
import sys
import os
import numpy as np
import warnings
import xml.etree.ElementTree as ET
from tqdm import tqdm
import cv2
from shapely import geometry
from pathlib import Path
import matplotlib.pyplot as plt
KERNEL = np.ones((5, 5), np.uint8)
with warnings.catch_warnings():
warnings.simplefilter("ignore")
def get_content_of_dir(dir_in):
"""
Listing all ground truth page xml files. All files are needed to have xml format.
"""
gt_all=os.listdir(dir_in)
gt_list=[file for file in gt_all if file.split('.')[ len(file.split('.'))-1 ]=='xml' ]
return gt_list
def return_parent_contours(contours, hierarchy):
contours_parent = [contours[i] for i in range(len(contours)) if hierarchy[0][i][3] == -1]
return contours_parent
def filter_contours_area_of_image_tables(image, contours, hierarchy, max_area, min_area):
found_polygons_early = list()
jv = 0
for c in contours:
if len(np.shape(c)) == 3:
c = c[0]
elif len(np.shape(c)) == 2:
pass
#c = c[0]
if len(c) < 3: # A polygon cannot have less than 3 points
continue
c_e = [point for point in c]
polygon = geometry.Polygon(c_e)
# area = cv2.contourArea(c)
area = polygon.area
# Check that polygon has area greater than minimal area
if area >= min_area * np.prod(image.shape[:2]) and area <= max_area * np.prod(image.shape[:2]): # and hierarchy[0][jv][3]==-1 :
found_polygons_early.append(np.array([[point] for point in polygon.exterior.coords], dtype=np.int32))
jv += 1
return found_polygons_early
def filter_contours_area_of_image(image, contours, order_index, max_area, min_area):
found_polygons_early = list()
order_index_filtered = list()
#jv = 0
for jv, c in enumerate(contours):
if len(np.shape(c)) == 3:
c = c[0]
elif len(np.shape(c)) == 2:
pass
if len(c) < 3: # A polygon cannot have less than 3 points
continue
c_e = [point for point in c]
polygon = geometry.Polygon(c_e)
area = polygon.area
if area >= min_area * np.prod(image.shape[:2]) and area <= max_area * np.prod(image.shape[:2]): # and hierarchy[0][jv][3]==-1 :
found_polygons_early.append(np.array([[point] for point in polygon.exterior.coords], dtype=np.uint))
order_index_filtered.append(order_index[jv])
#jv += 1
return found_polygons_early, order_index_filtered
def return_contours_of_interested_region(region_pre_p, pixel, min_area=0.0002):
# pixels of images are identified by 5
if len(region_pre_p.shape) == 3:
cnts_images = (region_pre_p[:, :, 0] == pixel) * 1
else:
cnts_images = (region_pre_p[:, :] == pixel) * 1
cnts_images = cnts_images.astype(np.uint8)
cnts_images = np.repeat(cnts_images[:, :, np.newaxis], 3, axis=2)
imgray = cv2.cvtColor(cnts_images, cv2.COLOR_BGR2GRAY)
ret, thresh = cv2.threshold(imgray, 0, 255, 0)
contours_imgs, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
#print(len(contours_imgs), hierarchy)
contours_imgs = return_parent_contours(contours_imgs, hierarchy)
#print(len(contours_imgs), "iki")
#contours_imgs = filter_contours_area_of_image_tables(thresh, contours_imgs, hierarchy, max_area=1, min_area=min_area)
return contours_imgs
def update_region_contours(co_text, img_boundary, erosion_rate, dilation_rate, y_len, x_len, dilation_early=None, erosion_early=None):
co_text_eroded = []
for con in co_text:
img_boundary_in = np.zeros( (y_len,x_len) )
img_boundary_in = cv2.fillPoly(img_boundary_in, pts=[con], color=(1, 1, 1))
if dilation_early:
img_boundary_in = cv2.dilate(img_boundary_in[:,:], KERNEL, iterations=dilation_early)
if erosion_early:
img_boundary_in = cv2.erode(img_boundary_in[:,:], KERNEL, iterations=erosion_early)
#img_boundary_in = cv2.erode(img_boundary_in[:,:], KERNEL, iterations=7)#asiatica
if erosion_rate > 0:
img_boundary_in = cv2.erode(img_boundary_in[:,:], KERNEL, iterations=erosion_rate)
pixel = 1
min_size = 0
img_boundary_in = img_boundary_in.astype("uint8")
con_eroded = return_contours_of_interested_region(img_boundary_in,pixel, min_size )
try:
co_text_eroded.append(con_eroded[0])
except:
co_text_eroded.append(con)
img_boundary_in_dilated = cv2.dilate(img_boundary_in[:,:], KERNEL, iterations=dilation_rate)
#img_boundary_in_dilated = cv2.dilate(img_boundary_in[:,:], KERNEL, iterations=5)
boundary = img_boundary_in_dilated[:,:] - img_boundary_in[:,:]
img_boundary[:,:][boundary[:,:]==1] =1
return co_text_eroded, img_boundary
def get_images_of_ground_truth(gt_list, dir_in, output_dir, output_type, config_file, config_params, printspace, dir_images, dir_out_images):
"""
Reading the page xml files and write the ground truth images into given output directory.
"""
## to do: add footnote to text regions
if dir_images:
ls_org_imgs = os.listdir(dir_images)
ls_org_imgs_stem = [item.split('.')[0] for item in ls_org_imgs]
for index in tqdm(range(len(gt_list))):
#try:
print(gt_list[index])
tree1 = ET.parse(dir_in+'/'+gt_list[index], parser = ET.XMLParser(encoding = 'iso-8859-5'))
root1=tree1.getroot()
alltags=[elem.tag for elem in root1.iter()]
link=alltags[0].split('}')[0]+'}'
for jj in root1.iter(link+'Page'):
y_len=int(jj.attrib['imageHeight'])
x_len=int(jj.attrib['imageWidth'])
if 'columns_width' in list(config_params.keys()):
columns_width_dict = config_params['columns_width']
metadata_element = root1.find(link+'Metadata')
comment_is_sub_element = False
for child in metadata_element:
tag2 = child.tag
if tag2.endswith('}Comments') or tag2.endswith('}comments'):
text_comments = child.text
num_col = int(text_comments.split('num_col')[1])
comment_is_sub_element = True
if not comment_is_sub_element:
num_col = None
if num_col:
x_new = columns_width_dict[str(num_col)]
y_new = int ( x_new * (y_len / float(x_len)) )
if printspace or "printspace_as_class_in_layout" in list(config_params.keys()):
region_tags = np.unique([x for x in alltags if x.endswith('PrintSpace') or x.endswith('Border')])
co_use_case = []
for tag in region_tags:
tag_endings = ['}PrintSpace','}Border']
if tag.endswith(tag_endings[0]) or tag.endswith(tag_endings[1]):
for nn in root1.iter(tag):
c_t_in = []
sumi = 0
for vv in nn.iter():
# check the format of coords
if vv.tag == link + 'Coords':
coords = bool(vv.attrib)
if coords:
p_h = vv.attrib['points'].split(' ')
c_t_in.append(
np.array([[int(x.split(',')[0]), int(x.split(',')[1])] for x in p_h]))
break
else:
pass
if vv.tag == link + 'Point':
c_t_in.append([int(float(vv.attrib['x'])), int(float(vv.attrib['y']))])
sumi += 1
elif vv.tag != link + 'Point' and sumi >= 1:
break
co_use_case.append(np.array(c_t_in))
img = np.zeros((y_len, x_len, 3))
img_poly = cv2.fillPoly(img, pts=co_use_case, color=(1, 1, 1))
img_poly = img_poly.astype(np.uint8)
imgray = cv2.cvtColor(img_poly, cv2.COLOR_BGR2GRAY)
_, thresh = cv2.threshold(imgray, 0, 255, 0)
contours, _ = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
cnt_size = np.array([cv2.contourArea(contours[j]) for j in range(len(contours))])
cnt = contours[np.argmax(cnt_size)]
x, y, w, h = cv2.boundingRect(cnt)
bb_xywh = [x, y, w, h]
if config_file and (config_params['use_case']=='textline' or config_params['use_case']=='word' or config_params['use_case']=='glyph' or config_params['use_case']=='printspace'):
keys = list(config_params.keys())
if "artificial_class_label" in keys:
artificial_class_rgb_color = (255,255,0)
artificial_class_label = config_params['artificial_class_label']
textline_rgb_color = (255, 0, 0)
if config_params['use_case']=='textline':
region_tags = np.unique([x for x in alltags if x.endswith('TextLine')])
elif config_params['use_case']=='word':
region_tags = np.unique([x for x in alltags if x.endswith('Word')])
elif config_params['use_case']=='glyph':
region_tags = np.unique([x for x in alltags if x.endswith('Glyph')])
elif config_params['use_case']=='printspace':
region_tags = np.unique([x for x in alltags if x.endswith('PrintSpace')])
co_use_case = []
for tag in region_tags:
if config_params['use_case']=='textline':
tag_endings = ['}TextLine','}textline']
elif config_params['use_case']=='word':
tag_endings = ['}Word','}word']
elif config_params['use_case']=='glyph':
tag_endings = ['}Glyph','}glyph']
elif config_params['use_case']=='printspace':
tag_endings = ['}PrintSpace','}printspace']
if tag.endswith(tag_endings[0]) or tag.endswith(tag_endings[1]):
for nn in root1.iter(tag):
c_t_in = []
sumi = 0
for vv in nn.iter():
# check the format of coords
if vv.tag == link + 'Coords':
coords = bool(vv.attrib)
if coords:
p_h = vv.attrib['points'].split(' ')
c_t_in.append(
np.array([[int(x.split(',')[0]), int(x.split(',')[1])] for x in p_h]))
break
else:
pass
if vv.tag == link + 'Point':
c_t_in.append([int(float(vv.attrib['x'])), int(float(vv.attrib['y']))])
sumi += 1
elif vv.tag != link + 'Point' and sumi >= 1:
break
co_use_case.append(np.array(c_t_in))
if "artificial_class_label" in keys:
img_boundary = np.zeros((y_len, x_len))
erosion_rate = 0#1
dilation_rate = 2
dilation_early = 0
erosion_early = 2
co_use_case, img_boundary = update_region_contours(co_use_case, img_boundary, erosion_rate, dilation_rate, y_len, x_len, dilation_early=dilation_early, erosion_early=erosion_early)
img = np.zeros((y_len, x_len, 3))
if output_type == '2d':
img_poly = cv2.fillPoly(img, pts=co_use_case, color=(1, 1, 1))
if "artificial_class_label" in keys:
img_mask = np.copy(img_poly)
##img_poly[:,:][(img_boundary[:,:]==1) & (img_mask[:,:,0]!=1)] = artificial_class_label
img_poly[:,:][img_boundary[:,:]==1] = artificial_class_label
elif output_type == '3d':
img_poly = cv2.fillPoly(img, pts=co_use_case, color=textline_rgb_color)
if "artificial_class_label" in keys:
img_mask = np.copy(img_poly)
img_poly[:,:,0][(img_boundary[:,:]==1) & (img_mask[:,:,0]!=255)] = artificial_class_rgb_color[0]
img_poly[:,:,1][(img_boundary[:,:]==1) & (img_mask[:,:,0]!=255)] = artificial_class_rgb_color[1]
img_poly[:,:,2][(img_boundary[:,:]==1) & (img_mask[:,:,0]!=255)] = artificial_class_rgb_color[2]
if printspace and config_params['use_case']!='printspace':
img_poly = img_poly[bb_xywh[1]:bb_xywh[1]+bb_xywh[3], bb_xywh[0]:bb_xywh[0]+bb_xywh[2], :]
if 'columns_width' in list(config_params.keys()) and num_col and config_params['use_case']!='printspace':
img_poly = resize_image(img_poly, y_new, x_new)
try:
xml_file_stem = gt_list[index].split('-')[1].split('.')[0]
cv2.imwrite(os.path.join(output_dir, xml_file_stem + '.png'), img_poly)
except:
xml_file_stem = gt_list[index].split('.')[0]
cv2.imwrite(os.path.join(output_dir, xml_file_stem + '.png'), img_poly)
if dir_images:
org_image_name = ls_org_imgs[ls_org_imgs_stem.index(xml_file_stem)]
img_org = cv2.imread(os.path.join(dir_images, org_image_name))
if printspace and config_params['use_case']!='printspace':
img_org = img_org[bb_xywh[1]:bb_xywh[1]+bb_xywh[3], bb_xywh[0]:bb_xywh[0]+bb_xywh[2], :]
if 'columns_width' in list(config_params.keys()) and num_col and config_params['use_case']!='printspace':
img_org = resize_image(img_org, y_new, x_new)
cv2.imwrite(os.path.join(dir_out_images, org_image_name), img_org)
if config_file and config_params['use_case']=='layout':
keys = list(config_params.keys())
if "artificial_class_on_boundary" in keys:
elements_with_artificial_class = list(config_params['artificial_class_on_boundary'])
artificial_class_rgb_color = (255,255,0)
artificial_class_label = config_params['artificial_class_label']
#values = config_params.values()
if "printspace_as_class_in_layout" in list(config_params.keys()):
printspace_class_rgb_color = (125,125,255)
printspace_class_label = config_params['printspace_as_class_in_layout']
if 'textregions' in keys:
types_text_dict = config_params['textregions']
types_text = list(types_text_dict.keys())
types_text_label = list(types_text_dict.values())
if 'graphicregions' in keys:
types_graphic_dict = config_params['graphicregions']
types_graphic = list(types_graphic_dict.keys())
types_graphic_label = list(types_graphic_dict.values())
labels_rgb_color = [ (0,0,0), (255,0,0), (255,125,0), (255,0,125), (125,255,125), (125,125,0), (0,125,255), (0,125,0), (125,125,125), (255,0,255), (125,0,125), (0,255,0),(0,0,255), (0,255,255), (255,125,125), (0,125,125), (0,255,125), (255,125,255), (125,255,0)]
region_tags=np.unique([x for x in alltags if x.endswith('Region')])
co_text = {'drop-capital':[], "footnote":[], "footnote-continued":[], "heading":[], "signature-mark":[], "header":[], "catch-word":[], "page-number":[], "marginalia":[], "paragraph":[]}
all_defined_textregion_types = list(co_text.keys())
co_graphic = {"handwritten-annotation":[], "decoration":[], "stamp":[], "signature":[]}
all_defined_graphic_types = list(co_graphic.keys())
co_sep=[]
co_img=[]
co_table=[]
co_noise=[]
for tag in region_tags:
if 'textregions' in keys:
if tag.endswith('}TextRegion') or tag.endswith('}Textregion'):
for nn in root1.iter(tag):
c_t_in = {'drop-capital':[], "footnote":[], "footnote-continued":[], "heading":[], "signature-mark":[], "header":[], "catch-word":[], "page-number":[], "marginalia":[], "paragraph":[]}
sumi=0
for vv in nn.iter():
# check the format of coords
if vv.tag==link+'Coords':
coords=bool(vv.attrib)
if coords:
p_h=vv.attrib['points'].split(' ')
if "rest_as_paragraph" in types_text:
types_text_without_paragraph = [element for element in types_text if element!='rest_as_paragraph' and element!='paragraph']
if len(types_text_without_paragraph) == 0:
if "type" in nn.attrib:
c_t_in['paragraph'].append( np.array( [ [ int(x.split(',')[0]) , int(x.split(',')[1]) ] for x in p_h] ) )
elif len(types_text_without_paragraph) >= 1:
if "type" in nn.attrib:
if nn.attrib['type'] in types_text_without_paragraph:
c_t_in[nn.attrib['type']].append( np.array( [ [ int(x.split(',')[0]) , int(x.split(',')[1]) ] for x in p_h] ) )
else:
c_t_in['paragraph'].append( np.array( [ [ int(x.split(',')[0]) , int(x.split(',')[1]) ] for x in p_h] ) )
else:
if "type" in nn.attrib:
if nn.attrib['type'] in all_defined_textregion_types:
c_t_in[nn.attrib['type']].append( np.array( [ [ int(x.split(',')[0]) , int(x.split(',')[1]) ] for x in p_h] ) )
break
else:
pass
if vv.tag==link+'Point':
if "rest_as_paragraph" in types_text:
types_text_without_paragraph = [element for element in types_text if element!='rest_as_paragraph' and element!='paragraph']
if len(types_text_without_paragraph) == 0:
if "type" in nn.attrib:
c_t_in['paragraph'].append( [ int(float(vv.attrib['x'])) , int(float(vv.attrib['y'])) ] )
sumi+=1
elif len(types_text_without_paragraph) >= 1:
if "type" in nn.attrib:
if nn.attrib['type'] in types_text_without_paragraph:
c_t_in[nn.attrib['type']].append( [ int(float(vv.attrib['x'])) , int(float(vv.attrib['y'])) ] )
sumi+=1
else:
c_t_in['paragraph'].append( [ int(float(vv.attrib['x'])) , int(float(vv.attrib['y'])) ] )
sumi+=1
else:
if "type" in nn.attrib:
if nn.attrib['type'] in all_defined_textregion_types:
c_t_in[nn.attrib['type']].append( [ int(float(vv.attrib['x'])) , int(float(vv.attrib['y'])) ] )
sumi+=1
elif vv.tag!=link+'Point' and sumi>=1:
break
for element_text in list(c_t_in.keys()):
if len(c_t_in[element_text])>0:
co_text[element_text].append(np.array(c_t_in[element_text]))
if 'graphicregions' in keys:
if tag.endswith('}GraphicRegion') or tag.endswith('}graphicregion'):
#print('sth')
for nn in root1.iter(tag):
c_t_in_graphic = {"handwritten-annotation":[], "decoration":[], "stamp":[], "signature":[]}
sumi=0
for vv in nn.iter():
# check the format of coords
if vv.tag==link+'Coords':
coords=bool(vv.attrib)
if coords:
p_h=vv.attrib['points'].split(' ')
if "rest_as_decoration" in types_graphic:
types_graphic_without_decoration = [element for element in types_graphic if element!='rest_as_decoration' and element!='decoration']
if len(types_graphic_without_decoration) == 0:
if "type" in nn.attrib:
c_t_in_graphic['decoration'].append( np.array( [ [ int(x.split(',')[0]) , int(x.split(',')[1]) ] for x in p_h] ) )
elif len(types_graphic_without_decoration) >= 1:
if "type" in nn.attrib:
if nn.attrib['type'] in types_graphic_without_decoration:
c_t_in_graphic[nn.attrib['type']].append( np.array( [ [ int(x.split(',')[0]) , int(x.split(',')[1]) ] for x in p_h] ) )
else:
c_t_in_graphic['decoration'].append( np.array( [ [ int(x.split(',')[0]) , int(x.split(',')[1]) ] for x in p_h] ) )
else:
if "type" in nn.attrib:
if nn.attrib['type'] in all_defined_graphic_types:
c_t_in_graphic[nn.attrib['type']].append( np.array( [ [ int(x.split(',')[0]) , int(x.split(',')[1]) ] for x in p_h] ) )
break
else:
pass
if vv.tag==link+'Point':
if "rest_as_decoration" in types_graphic:
types_graphic_without_decoration = [element for element in types_graphic if element!='rest_as_decoration' and element!='decoration']
if len(types_graphic_without_decoration) == 0:
if "type" in nn.attrib:
c_t_in_graphic['decoration'].append( [ int(float(vv.attrib['x'])) , int(float(vv.attrib['y'])) ] )
sumi+=1
elif len(types_graphic_without_decoration) >= 1:
if "type" in nn.attrib:
if nn.attrib['type'] in types_graphic_without_decoration:
c_t_in_graphic[nn.attrib['type']].append( [ int(float(vv.attrib['x'])) , int(float(vv.attrib['y'])) ] )
sumi+=1
else:
c_t_in_graphic['decoration'].append( [ int(float(vv.attrib['x'])) , int(float(vv.attrib['y'])) ] )
sumi+=1
else:
if "type" in nn.attrib:
if nn.attrib['type'] in all_defined_graphic_types:
c_t_in_graphic[nn.attrib['type']].append( [ int(float(vv.attrib['x'])) , int(float(vv.attrib['y'])) ] )
sumi+=1
elif vv.tag!=link+'Point' and sumi>=1:
break
for element_graphic in list(c_t_in_graphic.keys()):
if len(c_t_in_graphic[element_graphic])>0:
co_graphic[element_graphic].append(np.array(c_t_in_graphic[element_graphic]))
if 'imageregion' in keys:
if tag.endswith('}ImageRegion') or tag.endswith('}imageregion'):
for nn in root1.iter(tag):
c_t_in=[]
sumi=0
for vv in nn.iter():
if vv.tag==link+'Coords':
coords=bool(vv.attrib)
if coords:
p_h=vv.attrib['points'].split(' ')
c_t_in.append( np.array( [ [ int(x.split(',')[0]) , int(x.split(',')[1]) ] for x in p_h] ) )
break
else:
pass
if vv.tag==link+'Point':
c_t_in.append([ int(float(vv.attrib['x'])) , int(float(vv.attrib['y'])) ])
sumi+=1
elif vv.tag!=link+'Point' and sumi>=1:
break
co_img.append(np.array(c_t_in))
if 'separatorregion' in keys:
if tag.endswith('}SeparatorRegion') or tag.endswith('}separatorregion'):
for nn in root1.iter(tag):
c_t_in=[]
sumi=0
for vv in nn.iter():
# check the format of coords
if vv.tag==link+'Coords':
coords=bool(vv.attrib)
if coords:
p_h=vv.attrib['points'].split(' ')
c_t_in.append( np.array( [ [ int(x.split(',')[0]) , int(x.split(',')[1]) ] for x in p_h] ) )
break
else:
pass
if vv.tag==link+'Point':
c_t_in.append([ int(float(vv.attrib['x'])) , int(float(vv.attrib['y'])) ])
sumi+=1
elif vv.tag!=link+'Point' and sumi>=1:
break
co_sep.append(np.array(c_t_in))
if 'tableregion' in keys:
if tag.endswith('}TableRegion') or tag.endswith('}tableregion'):
#print('sth')
for nn in root1.iter(tag):
c_t_in=[]
sumi=0
for vv in nn.iter():
# check the format of coords
if vv.tag==link+'Coords':
coords=bool(vv.attrib)
if coords:
p_h=vv.attrib['points'].split(' ')
c_t_in.append( np.array( [ [ int(x.split(',')[0]) , int(x.split(',')[1]) ] for x in p_h] ) )
break
else:
pass
if vv.tag==link+'Point':
c_t_in.append([ int(float(vv.attrib['x'])) , int(float(vv.attrib['y'])) ])
sumi+=1
#print(vv.tag,'in')
elif vv.tag!=link+'Point' and sumi>=1:
break
co_table.append(np.array(c_t_in))
if 'noiseregion' in keys:
if tag.endswith('}NoiseRegion') or tag.endswith('}noiseregion'):
#print('sth')
for nn in root1.iter(tag):
c_t_in=[]
sumi=0
for vv in nn.iter():
# check the format of coords
if vv.tag==link+'Coords':
coords=bool(vv.attrib)
if coords:
p_h=vv.attrib['points'].split(' ')
c_t_in.append( np.array( [ [ int(x.split(',')[0]) , int(x.split(',')[1]) ] for x in p_h] ) )
break
else:
pass
if vv.tag==link+'Point':
c_t_in.append([ int(float(vv.attrib['x'])) , int(float(vv.attrib['y'])) ])
sumi+=1
#print(vv.tag,'in')
elif vv.tag!=link+'Point' and sumi>=1:
break
co_noise.append(np.array(c_t_in))
if "artificial_class_on_boundary" in keys:
img_boundary = np.zeros( (y_len,x_len) )
if "paragraph" in elements_with_artificial_class:
erosion_rate = 2
dilation_rate = 4
co_text['paragraph'], img_boundary = update_region_contours(co_text['paragraph'], img_boundary, erosion_rate, dilation_rate, y_len, x_len )
if "drop-capital" in elements_with_artificial_class:
erosion_rate = 1
dilation_rate = 3
co_text["drop-capital"], img_boundary = update_region_contours(co_text["drop-capital"], img_boundary, erosion_rate, dilation_rate, y_len, x_len )
if "catch-word" in elements_with_artificial_class:
erosion_rate = 0
dilation_rate = 3#4
co_text["catch-word"], img_boundary = update_region_contours(co_text["catch-word"], img_boundary, erosion_rate, dilation_rate, y_len, x_len )
if "page-number" in elements_with_artificial_class:
erosion_rate = 0
dilation_rate = 3#4
co_text["page-number"], img_boundary = update_region_contours(co_text["page-number"], img_boundary, erosion_rate, dilation_rate, y_len, x_len )
if "header" in elements_with_artificial_class:
erosion_rate = 1
dilation_rate = 4
co_text["header"], img_boundary = update_region_contours(co_text["header"], img_boundary, erosion_rate, dilation_rate, y_len, x_len )
if "heading" in elements_with_artificial_class:
erosion_rate = 1
dilation_rate = 4
co_text["heading"], img_boundary = update_region_contours(co_text["heading"], img_boundary, erosion_rate, dilation_rate, y_len, x_len )
if "signature-mark" in elements_with_artificial_class:
erosion_rate = 1
dilation_rate = 4
co_text["signature-mark"], img_boundary = update_region_contours(co_text["signature-mark"], img_boundary, erosion_rate, dilation_rate, y_len, x_len )
if "marginalia" in elements_with_artificial_class:
erosion_rate = 2
dilation_rate = 4
co_text["marginalia"], img_boundary = update_region_contours(co_text["marginalia"], img_boundary, erosion_rate, dilation_rate, y_len, x_len )
if "footnote" in elements_with_artificial_class:
erosion_rate = 0#2
dilation_rate = 2#4
co_text["footnote"], img_boundary = update_region_contours(co_text["footnote"], img_boundary, erosion_rate, dilation_rate, y_len, x_len )
if "footnote-continued" in elements_with_artificial_class:
erosion_rate = 0#2
dilation_rate = 2#4
co_text["footnote-continued"], img_boundary = update_region_contours(co_text["footnote-continued"], img_boundary, erosion_rate, dilation_rate, y_len, x_len )
if "tableregion" in elements_with_artificial_class:
erosion_rate = 0#2
dilation_rate = 3#4
co_table, img_boundary = update_region_contours(co_table, img_boundary, erosion_rate, dilation_rate, y_len, x_len )
img = np.zeros( (y_len,x_len,3) )
if output_type == '3d':
if 'graphicregions' in keys:
if 'rest_as_decoration' in types_graphic:
types_graphic[types_graphic=='rest_as_decoration'] = 'decoration'
for element_graphic in types_graphic:
if element_graphic == 'decoration':
color_label = labels_rgb_color[ config_params['graphicregions']['rest_as_decoration']]
else:
color_label = labels_rgb_color[ config_params['graphicregions'][element_graphic]]
img_poly=cv2.fillPoly(img, pts =co_graphic[element_graphic], color=color_label)
else:
for element_graphic in types_graphic:
color_label = labels_rgb_color[ config_params['graphicregions'][element_graphic]]
img_poly=cv2.fillPoly(img, pts =co_graphic[element_graphic], color=color_label)
if 'imageregion' in keys:
img_poly=cv2.fillPoly(img, pts =co_img, color=labels_rgb_color[ config_params['imageregion']])
if 'tableregion' in keys:
img_poly=cv2.fillPoly(img, pts =co_table, color=labels_rgb_color[ config_params['tableregion']])
if 'noiseregion' in keys:
img_poly=cv2.fillPoly(img, pts =co_noise, color=labels_rgb_color[ config_params['noiseregion']])
if 'textregions' in keys:
if 'rest_as_paragraph' in types_text:
types_text = ['paragraph'if ttind=='rest_as_paragraph' else ttind for ttind in types_text]
for element_text in types_text:
if element_text == 'paragraph':
color_label = labels_rgb_color[ config_params['textregions']['rest_as_paragraph']]
else:
color_label = labels_rgb_color[ config_params['textregions'][element_text]]
img_poly=cv2.fillPoly(img, pts =co_text[element_text], color=color_label)
else:
for element_text in types_text:
color_label = labels_rgb_color[ config_params['textregions'][element_text]]
img_poly=cv2.fillPoly(img, pts =co_text[element_text], color=color_label)
if "artificial_class_on_boundary" in keys:
img_poly[:,:,0][img_boundary[:,:]==1] = artificial_class_rgb_color[0]
img_poly[:,:,1][img_boundary[:,:]==1] = artificial_class_rgb_color[1]
img_poly[:,:,2][img_boundary[:,:]==1] = artificial_class_rgb_color[2]
if 'separatorregion' in keys:
img_poly=cv2.fillPoly(img, pts =co_sep, color=labels_rgb_color[ config_params['separatorregion']])
if "printspace_as_class_in_layout" in list(config_params.keys()):
printspace_mask = np.zeros((img_poly.shape[0], img_poly.shape[1]))
printspace_mask[bb_xywh[1]:bb_xywh[1]+bb_xywh[3], bb_xywh[0]:bb_xywh[0]+bb_xywh[2]] = 1
img_poly[:,:,0][printspace_mask[:,:] == 0] = printspace_class_rgb_color[0]
img_poly[:,:,1][printspace_mask[:,:] == 0] = printspace_class_rgb_color[1]
img_poly[:,:,2][printspace_mask[:,:] == 0] = printspace_class_rgb_color[2]
elif output_type == '2d':
if 'graphicregions' in keys:
if 'rest_as_decoration' in types_graphic:
types_graphic[types_graphic=='rest_as_decoration'] = 'decoration'
for element_graphic in types_graphic:
if element_graphic == 'decoration':
color_label = config_params['graphicregions']['rest_as_decoration']
else:
color_label = config_params['graphicregions'][element_graphic]
img_poly=cv2.fillPoly(img, pts =co_graphic[element_graphic], color=color_label)
else:
for element_graphic in types_graphic:
color_label = config_params['graphicregions'][element_graphic]
img_poly=cv2.fillPoly(img, pts =co_graphic[element_graphic], color=color_label)
if 'imageregion' in keys:
color_label = config_params['imageregion']
img_poly=cv2.fillPoly(img, pts =co_img, color=(color_label,color_label,color_label))
if 'tableregion' in keys:
color_label = config_params['tableregion']
img_poly=cv2.fillPoly(img, pts =co_table, color=(color_label,color_label,color_label))
if 'noiseregion' in keys:
color_label = config_params['noiseregion']
img_poly=cv2.fillPoly(img, pts =co_noise, color=(color_label,color_label,color_label))
if 'textregions' in keys:
if 'rest_as_paragraph' in types_text:
types_text = ['paragraph'if ttind=='rest_as_paragraph' else ttind for ttind in types_text]
for element_text in types_text:
if element_text == 'paragraph':
color_label = config_params['textregions']['rest_as_paragraph']
else:
color_label = config_params['textregions'][element_text]
img_poly=cv2.fillPoly(img, pts =co_text[element_text], color=color_label)
else:
for element_text in types_text:
color_label = config_params['textregions'][element_text]
img_poly=cv2.fillPoly(img, pts =co_text[element_text], color=color_label)
if "artificial_class_on_boundary" in keys:
img_poly[:,:][img_boundary[:,:]==1] = artificial_class_label
if 'separatorregion' in keys:
color_label = config_params['separatorregion']
img_poly=cv2.fillPoly(img, pts =co_sep, color=(color_label,color_label,color_label))
if "printspace_as_class_in_layout" in list(config_params.keys()):
printspace_mask = np.zeros((img_poly.shape[0], img_poly.shape[1]))
printspace_mask[bb_xywh[1]:bb_xywh[1]+bb_xywh[3], bb_xywh[0]:bb_xywh[0]+bb_xywh[2]] = 1
img_poly[:,:,0][printspace_mask[:,:] == 0] = printspace_class_label
img_poly[:,:,1][printspace_mask[:,:] == 0] = printspace_class_label
img_poly[:,:,2][printspace_mask[:,:] == 0] = printspace_class_label
if printspace:
img_poly = img_poly[bb_xywh[1]:bb_xywh[1]+bb_xywh[3], bb_xywh[0]:bb_xywh[0]+bb_xywh[2], :]
if 'columns_width' in list(config_params.keys()) and num_col:
img_poly = resize_image(img_poly, y_new, x_new)
try:
xml_file_stem = gt_list[index].split('-')[1].split('.')[0]
cv2.imwrite(os.path.join(output_dir, xml_file_stem + '.png'), img_poly)
except:
xml_file_stem = gt_list[index].split('.')[0]
cv2.imwrite(os.path.join(output_dir, xml_file_stem + '.png'), img_poly)
if dir_images:
org_image_name = ls_org_imgs[ls_org_imgs_stem.index(xml_file_stem)]
img_org = cv2.imread(os.path.join(dir_images, org_image_name))
if printspace:
img_org = img_org[bb_xywh[1]:bb_xywh[1]+bb_xywh[3], bb_xywh[0]:bb_xywh[0]+bb_xywh[2], :]
if 'columns_width' in list(config_params.keys()) and num_col:
img_org = resize_image(img_org, y_new, x_new)
cv2.imwrite(os.path.join(dir_out_images, org_image_name), img_org)
def find_new_features_of_contours(contours_main):
areas_main = np.array([cv2.contourArea(contours_main[j]) for j in range(len(contours_main))])
M_main = [cv2.moments(contours_main[j]) for j in range(len(contours_main))]
cx_main = [(M_main[j]["m10"] / (M_main[j]["m00"] + 1e-32)) for j in range(len(M_main))]
cy_main = [(M_main[j]["m01"] / (M_main[j]["m00"] + 1e-32)) for j in range(len(M_main))]
try:
x_min_main = np.array([np.min(contours_main[j][0][:, 0]) for j in range(len(contours_main))])
argmin_x_main = np.array([np.argmin(contours_main[j][0][:, 0]) for j in range(len(contours_main))])
x_min_from_argmin = np.array([contours_main[j][0][argmin_x_main[j], 0] for j in range(len(contours_main))])
y_corr_x_min_from_argmin = np.array([contours_main[j][0][argmin_x_main[j], 1] for j in range(len(contours_main))])
x_max_main = np.array([np.max(contours_main[j][0][:, 0]) for j in range(len(contours_main))])
y_min_main = np.array([np.min(contours_main[j][0][:, 1]) for j in range(len(contours_main))])
y_max_main = np.array([np.max(contours_main[j][0][:, 1]) for j in range(len(contours_main))])
except:
x_min_main = np.array([np.min(contours_main[j][:, 0]) for j in range(len(contours_main))])
argmin_x_main = np.array([np.argmin(contours_main[j][:, 0]) for j in range(len(contours_main))])
x_min_from_argmin = np.array([contours_main[j][argmin_x_main[j], 0] for j in range(len(contours_main))])
y_corr_x_min_from_argmin = np.array([contours_main[j][argmin_x_main[j], 1] for j in range(len(contours_main))])
x_max_main = np.array([np.max(contours_main[j][:, 0]) for j in range(len(contours_main))])
y_min_main = np.array([np.min(contours_main[j][:, 1]) for j in range(len(contours_main))])
y_max_main = np.array([np.max(contours_main[j][:, 1]) for j in range(len(contours_main))])
return cx_main, cy_main, x_min_main, x_max_main, y_min_main, y_max_main, y_corr_x_min_from_argmin
def read_xml(xml_file):
file_name = Path(xml_file).stem
tree1 = ET.parse(xml_file, parser = ET.XMLParser(encoding = 'iso-8859-5'))
root1=tree1.getroot()
alltags=[elem.tag for elem in root1.iter()]
link=alltags[0].split('}')[0]+'}'
index_tot_regions = []
tot_region_ref = []
for jj in root1.iter(link+'Page'):
y_len=int(jj.attrib['imageHeight'])
x_len=int(jj.attrib['imageWidth'])
for jj in root1.iter(link+'RegionRefIndexed'):
index_tot_regions.append(jj.attrib['index'])
tot_region_ref.append(jj.attrib['regionRef'])
if (link+'PrintSpace' in alltags) or (link+'Border' in alltags):
co_printspace = []
if link+'PrintSpace' in alltags:
region_tags_printspace = np.unique([x for x in alltags if x.endswith('PrintSpace')])
elif link+'Border' in alltags:
region_tags_printspace = np.unique([x for x in alltags if x.endswith('Border')])
for tag in region_tags_printspace:
if link+'PrintSpace' in alltags:
tag_endings_printspace = ['}PrintSpace','}printspace']
elif link+'Border' in alltags:
tag_endings_printspace = ['}Border','}border']
if tag.endswith(tag_endings_printspace[0]) or tag.endswith(tag_endings_printspace[1]):
for nn in root1.iter(tag):
c_t_in = []
sumi = 0
for vv in nn.iter():
# check the format of coords
if vv.tag == link + 'Coords':
coords = bool(vv.attrib)
if coords:
p_h = vv.attrib['points'].split(' ')
c_t_in.append(
np.array([[int(x.split(',')[0]), int(x.split(',')[1])] for x in p_h]))
break
else:
pass
if vv.tag == link + 'Point':
c_t_in.append([int(float(vv.attrib['x'])), int(float(vv.attrib['y']))])
sumi += 1
elif vv.tag != link + 'Point' and sumi >= 1:
break
co_printspace.append(np.array(c_t_in))
img_printspace = np.zeros( (y_len,x_len,3) )
img_printspace=cv2.fillPoly(img_printspace, pts =co_printspace, color=(1,1,1))
img_printspace = img_printspace.astype(np.uint8)
imgray = cv2.cvtColor(img_printspace, cv2.COLOR_BGR2GRAY)
_, thresh = cv2.threshold(imgray, 0, 255, 0)
contours, _ = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
cnt_size = np.array([cv2.contourArea(contours[j]) for j in range(len(contours))])
cnt = contours[np.argmax(cnt_size)]
x, y, w, h = cv2.boundingRect(cnt)
bb_coord_printspace = [x, y, w, h]
else:
bb_coord_printspace = None
region_tags=np.unique([x for x in alltags if x.endswith('Region')])
co_text_paragraph=[]
co_text_drop=[]
co_text_heading=[]
co_text_header=[]
co_text_marginalia=[]
co_text_catch=[]
co_text_page_number=[]
co_text_signature_mark=[]
co_sep=[]
co_img=[]
co_table=[]
co_graphic=[]
co_graphic_text_annotation=[]
co_graphic_decoration=[]
co_noise=[]
co_text_paragraph_text=[]
co_text_drop_text=[]
co_text_heading_text=[]
co_text_header_text=[]
co_text_marginalia_text=[]
co_text_catch_text=[]
co_text_page_number_text=[]
co_text_signature_mark_text=[]
co_sep_text=[]
co_img_text=[]
co_table_text=[]
co_graphic_text=[]
co_graphic_text_annotation_text=[]
co_graphic_decoration_text=[]
co_noise_text=[]
id_paragraph = []
id_header = []
id_heading = []
id_marginalia = []
for tag in region_tags:
if tag.endswith('}TextRegion') or tag.endswith('}Textregion'):
for nn in root1.iter(tag):
for child2 in nn:
tag2 = child2.tag
if tag2.endswith('}TextEquiv') or tag2.endswith('}TextEquiv'):
for childtext2 in child2:
if childtext2.tag.endswith('}Unicode') or childtext2.tag.endswith('}Unicode'):
if "type" in nn.attrib and nn.attrib['type']=='drop-capital':
co_text_drop_text.append(childtext2.text)
elif "type" in nn.attrib and nn.attrib['type']=='heading':
co_text_heading_text.append(childtext2.text)
elif "type" in nn.attrib and nn.attrib['type']=='signature-mark':
co_text_signature_mark_text.append(childtext2.text)
elif "type" in nn.attrib and nn.attrib['type']=='header':
co_text_header_text.append(childtext2.text)
###elif "type" in nn.attrib and nn.attrib['type']=='catch-word':
###co_text_catch_text.append(childtext2.text)
###elif "type" in nn.attrib and nn.attrib['type']=='page-number':
###co_text_page_number_text.append(childtext2.text)
elif "type" in nn.attrib and nn.attrib['type']=='marginalia':
co_text_marginalia_text.append(childtext2.text)
else:
co_text_paragraph_text.append(childtext2.text)
c_t_in_drop=[]
c_t_in_paragraph=[]
c_t_in_heading=[]
c_t_in_header=[]
c_t_in_page_number=[]
c_t_in_signature_mark=[]
c_t_in_catch=[]
c_t_in_marginalia=[]
sumi=0
for vv in nn.iter():
# check the format of coords
if vv.tag==link+'Coords':
coords=bool(vv.attrib)
if coords:
#print('birda1')
p_h=vv.attrib['points'].split(' ')
if "type" in nn.attrib and nn.attrib['type']=='drop-capital':
c_t_in_drop.append( np.array( [ [ int(x.split(',')[0]) , int(x.split(',')[1]) ] for x in p_h] ) )
elif "type" in nn.attrib and nn.attrib['type']=='heading':
##id_heading.append(nn.attrib['id'])
c_t_in_heading.append( np.array( [ [ int(x.split(',')[0]) , int(x.split(',')[1]) ] for x in p_h] ) )
elif "type" in nn.attrib and nn.attrib['type']=='signature-mark':
c_t_in_signature_mark.append( np.array( [ [ int(x.split(',')[0]) , int(x.split(',')[1]) ] for x in p_h] ) )
#print(c_t_in_paragraph)
elif "type" in nn.attrib and nn.attrib['type']=='header':
#id_header.append(nn.attrib['id'])
c_t_in_header.append( np.array( [ [ int(x.split(',')[0]) , int(x.split(',')[1]) ] for x in p_h] ) )
###elif "type" in nn.attrib and nn.attrib['type']=='catch-word':
###c_t_in_catch.append( np.array( [ [ int(x.split(',')[0]) , int(x.split(',')[1]) ] for x in p_h] ) )
###elif "type" in nn.attrib and nn.attrib['type']=='page-number':