mirror of
https://github.com/qurator-spk/sbb_pixelwise_segmentation.git
synced 2025-06-13 22:00:06 +02:00
visulizing textline detection from eynollah page-xml output
This commit is contained in:
parent
d554d26739
commit
fc75770b73
2 changed files with 136 additions and 0 deletions
|
@ -2,6 +2,7 @@ import click
|
|||
import json
|
||||
from gt_gen_utils import *
|
||||
from tqdm import tqdm
|
||||
from pathlib import Path
|
||||
|
||||
@click.group()
|
||||
def main():
|
||||
|
@ -331,6 +332,53 @@ def visualize_reading_order(dir_xml, dir_out, dir_imgs):
|
|||
cv2.imwrite(os.path.join(dir_out, f_name+'.png'), img)
|
||||
|
||||
|
||||
@main.command()
|
||||
@click.option(
|
||||
"--dir_xml",
|
||||
"-dx",
|
||||
help="directory of GT page-xml files",
|
||||
type=click.Path(exists=True, file_okay=False),
|
||||
)
|
||||
|
||||
@click.option(
|
||||
"--dir_out",
|
||||
"-do",
|
||||
help="directory where plots will be written",
|
||||
type=click.Path(exists=True, file_okay=False),
|
||||
)
|
||||
|
||||
@click.option(
|
||||
"--dir_imgs",
|
||||
"-dimg",
|
||||
help="directory of images where textline segmentation will be overlayed", )
|
||||
|
||||
def visualize_textline_segmentation(dir_xml, dir_out, dir_imgs):
|
||||
xml_files_ind = os.listdir(dir_xml)
|
||||
for ind_xml in tqdm(xml_files_ind):
|
||||
indexer = 0
|
||||
#print(ind_xml)
|
||||
#print('########################')
|
||||
xml_file = os.path.join(dir_xml,ind_xml )
|
||||
f_name = Path(ind_xml).stem
|
||||
|
||||
img_file_name_with_format = find_format_of_given_filename_in_dir(dir_imgs, f_name)
|
||||
img = cv2.imread(os.path.join(dir_imgs, img_file_name_with_format))
|
||||
|
||||
co_tetxlines, y_len, x_len = get_textline_contours_for_visualization(xml_file)
|
||||
|
||||
img_total = np.zeros((y_len, x_len, 3))
|
||||
for cont in co_tetxlines:
|
||||
img_in = np.zeros((y_len, x_len, 3))
|
||||
img_in = cv2.fillPoly(img_in, pts =[cont], color=(1,1,1))
|
||||
|
||||
img_total = img_total + img_in
|
||||
|
||||
img_total[:,:, 0][img_total[:,:, 0]>2] = 2
|
||||
|
||||
img_out, _ = visualize_model_output(img_total, img, task="textline")
|
||||
|
||||
cv2.imwrite(os.path.join(dir_out, f_name+'.png'), img_out)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
|
|
|
@ -16,6 +16,52 @@ KERNEL = np.ones((5, 5), np.uint8)
|
|||
with warnings.catch_warnings():
|
||||
warnings.simplefilter("ignore")
|
||||
|
||||
def visualize_model_output(prediction, img, task):
|
||||
if task == "binarization":
|
||||
prediction = prediction * -1
|
||||
prediction = prediction + 1
|
||||
added_image = prediction * 255
|
||||
layout_only = None
|
||||
else:
|
||||
unique_classes = np.unique(prediction[:,:,0])
|
||||
rgb_colors = {'0' : [255, 255, 255],
|
||||
'1' : [255, 0, 0],
|
||||
'2' : [255, 125, 0],
|
||||
'3' : [255, 0, 125],
|
||||
'4' : [125, 125, 125],
|
||||
'5' : [125, 125, 0],
|
||||
'6' : [0, 125, 255],
|
||||
'7' : [0, 125, 0],
|
||||
'8' : [125, 125, 125],
|
||||
'9' : [0, 125, 255],
|
||||
'10' : [125, 0, 125],
|
||||
'11' : [0, 255, 0],
|
||||
'12' : [0, 0, 255],
|
||||
'13' : [0, 255, 255],
|
||||
'14' : [255, 125, 125],
|
||||
'15' : [255, 0, 255]}
|
||||
|
||||
layout_only = np.zeros(prediction.shape)
|
||||
|
||||
for unq_class in unique_classes:
|
||||
rgb_class_unique = rgb_colors[str(int(unq_class))]
|
||||
layout_only[:,:,0][prediction[:,:,0]==unq_class] = rgb_class_unique[0]
|
||||
layout_only[:,:,1][prediction[:,:,0]==unq_class] = rgb_class_unique[1]
|
||||
layout_only[:,:,2][prediction[:,:,0]==unq_class] = rgb_class_unique[2]
|
||||
|
||||
|
||||
|
||||
img = resize_image(img, layout_only.shape[0], layout_only.shape[1])
|
||||
|
||||
layout_only = layout_only.astype(np.int32)
|
||||
img = img.astype(np.int32)
|
||||
|
||||
|
||||
|
||||
added_image = cv2.addWeighted(img,0.5,layout_only,0.1,0)
|
||||
|
||||
return added_image, layout_only
|
||||
|
||||
def get_content_of_dir(dir_in):
|
||||
"""
|
||||
Listing all ground truth page xml files. All files are needed to have xml format.
|
||||
|
@ -138,6 +184,48 @@ def update_region_contours(co_text, img_boundary, erosion_rate, dilation_rate, y
|
|||
|
||||
img_boundary[:,:][boundary[:,:]==1] =1
|
||||
return co_text_eroded, img_boundary
|
||||
|
||||
def get_textline_contours_for_visualization(xml_file):
|
||||
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]+'}'
|
||||
|
||||
|
||||
|
||||
for jj in root1.iter(link+'Page'):
|
||||
y_len=int(jj.attrib['imageHeight'])
|
||||
x_len=int(jj.attrib['imageWidth'])
|
||||
|
||||
region_tags = np.unique([x for x in alltags if x.endswith('TextLine')])
|
||||
tag_endings = ['}TextLine','}textline']
|
||||
co_use_case = []
|
||||
|
||||
for tag in region_tags:
|
||||
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():
|
||||
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))
|
||||
return co_use_case, y_len, x_len
|
||||
|
||||
|
||||
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.
|
||||
|
|
Loading…
Add table
Add a link
Reference in a new issue