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training.gt_gen_utils: fix+simplify cropping…
when parsing `PrintSpace` or `Border` from PAGE-XML, - use `lxml` XPath instead of nested loops - convert points to polygons directly (instead of painting on canvas and retrieving contours) - pass result bbox in slice notation (instead of xywh)
This commit is contained in:
Robert Sachunsky
parent
acda9c84ee
commit
0372fd7a1e
2 changed files with 51 additions and 118 deletions
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@ -1,15 +1,18 @@
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import os
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import numpy as np
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import warnings
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import xml.etree.ElementTree as ET
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from lxml import etree as ET
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from tqdm import tqdm
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import cv2
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from shapely import geometry
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from pathlib import Path
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from PIL import ImageFont
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from ocrd_utils import bbox_from_points
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KERNEL = np.ones((5, 5), np.uint8)
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NS = { 'pc': 'http://schema.primaresearch.org/PAGE/gts/pagecontent/2019-07-15'
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}
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with warnings.catch_warnings():
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warnings.simplefilter("ignore")
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@ -664,52 +667,13 @@ def get_images_of_ground_truth(gt_list, dir_in, output_dir, output_type, config_
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y_new = int ( x_new * (y_len / float(x_len)) )
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if printspace or "printspace_as_class_in_layout" in list(config_params.keys()):
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region_tags = np.unique([x for x in alltags if x.endswith('PrintSpace') or x.endswith('Border')])
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co_use_case = []
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for tag in region_tags:
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tag_endings = ['}PrintSpace','}Border']
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if tag.endswith(tag_endings[0]) or tag.endswith(tag_endings[1]):
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for nn in root1.iter(tag):
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c_t_in = []
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sumi = 0
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for vv in nn.iter():
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# check the format of coords
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if vv.tag == link + 'Coords':
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coords = bool(vv.attrib)
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if coords:
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p_h = vv.attrib['points'].split(' ')
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c_t_in.append(
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np.array([[int(x.split(',')[0]), int(x.split(',')[1])] for x in p_h]))
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break
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ps = (root1.xpath('/pc:PcGts/pc:Page/pc:Border', namespaces=NS) +
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root1.xpath('/pc:PcGts/pc:Page/pc:PrintSpace', namespaces=NS))
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if len(ps):
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points = ps[0].find('pc:Coords', NS).get('points')
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ps_bbox = bbox_from_points(points)
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else:
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pass
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if vv.tag == link + 'Point':
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c_t_in.append([int(float(vv.attrib['x'])), int(float(vv.attrib['y']))])
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sumi += 1
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elif vv.tag != link + 'Point' and sumi >= 1:
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break
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co_use_case.append(np.array(c_t_in))
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img = np.zeros((y_len, x_len, 3))
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img_poly = cv2.fillPoly(img, pts=co_use_case, color=(1, 1, 1))
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img_poly = img_poly.astype(np.uint8)
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imgray = cv2.cvtColor(img_poly, cv2.COLOR_BGR2GRAY)
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_, thresh = cv2.threshold(imgray, 0, 255, 0)
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contours, _ = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
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cnt_size = np.array([cv2.contourArea(contours[j]) for j in range(len(contours))])
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cnt = contours[np.argmax(cnt_size)]
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x, y, w, h = cv2.boundingRect(cnt)
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bb_xywh = [x, y, w, h]
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ps_bbox = [0, 0, None, None]
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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'):
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@ -791,7 +755,8 @@ def get_images_of_ground_truth(gt_list, dir_in, output_dir, output_type, config_
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if printspace and config_params['use_case']!='printspace':
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img_poly = img_poly[bb_xywh[1]:bb_xywh[1]+bb_xywh[3], bb_xywh[0]:bb_xywh[0]+bb_xywh[2], :]
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img_poly = img_poly[ps_bbox[1]:ps_bbox[3],
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ps_bbox[0]:ps_bbox[2], :]
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if 'columns_width' in list(config_params.keys()) and num_col and config_params['use_case']!='printspace':
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@ -815,7 +780,8 @@ def get_images_of_ground_truth(gt_list, dir_in, output_dir, output_type, config_
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img_org = cv2.imread(os.path.join(dir_images, org_image_name))
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if printspace and config_params['use_case']!='printspace':
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img_org = img_org[bb_xywh[1]:bb_xywh[1]+bb_xywh[3], bb_xywh[0]:bb_xywh[0]+bb_xywh[2], :]
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img_org = img_org[ps_bbox[1]:ps_bbox[3],
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ps_bbox[0]:ps_bbox[2], :]
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if 'columns_width' in list(config_params.keys()) and num_col and config_params['use_case']!='printspace':
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img_org = resize_image(img_org, y_new, x_new)
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@ -1194,7 +1160,8 @@ def get_images_of_ground_truth(gt_list, dir_in, output_dir, output_type, config_
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if "printspace_as_class_in_layout" in list(config_params.keys()):
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printspace_mask = np.zeros((img_poly.shape[0], img_poly.shape[1]))
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printspace_mask[bb_xywh[1]:bb_xywh[1]+bb_xywh[3], bb_xywh[0]:bb_xywh[0]+bb_xywh[2]] = 1
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printspace_mask[ps_bbox[1]:ps_bbox[3],
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ps_bbox[0]:ps_bbox[2]] = 1
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img_poly[:,:,0][printspace_mask[:,:] == 0] = printspace_class_rgb_color[0]
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img_poly[:,:,1][printspace_mask[:,:] == 0] = printspace_class_rgb_color[1]
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@ -1252,7 +1219,8 @@ def get_images_of_ground_truth(gt_list, dir_in, output_dir, output_type, config_
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if "printspace_as_class_in_layout" in list(config_params.keys()):
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printspace_mask = np.zeros((img_poly.shape[0], img_poly.shape[1]))
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printspace_mask[bb_xywh[1]:bb_xywh[1]+bb_xywh[3], bb_xywh[0]:bb_xywh[0]+bb_xywh[2]] = 1
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printspace_mask[ps_bbox[1]:ps_bbox[3],
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ps_bbox[0]:ps_bbox[2]] = 1
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img_poly[:,:,0][printspace_mask[:,:] == 0] = printspace_class_label
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img_poly[:,:,1][printspace_mask[:,:] == 0] = printspace_class_label
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@ -1261,7 +1229,8 @@ def get_images_of_ground_truth(gt_list, dir_in, output_dir, output_type, config_
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if printspace:
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img_poly = img_poly[bb_xywh[1]:bb_xywh[1]+bb_xywh[3], bb_xywh[0]:bb_xywh[0]+bb_xywh[2], :]
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img_poly = img_poly[ps_bbox[1]:ps_bbox[3],
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ps_bbox[0]:ps_bbox[2], :]
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if 'columns_width' in list(config_params.keys()) and num_col:
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img_poly = resize_image(img_poly, y_new, x_new)
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@ -1285,7 +1254,8 @@ def get_images_of_ground_truth(gt_list, dir_in, output_dir, output_type, config_
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img_org = cv2.imread(os.path.join(dir_images, org_image_name))
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if printspace:
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img_org = img_org[bb_xywh[1]:bb_xywh[1]+bb_xywh[3], bb_xywh[0]:bb_xywh[0]+bb_xywh[2], :]
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img_org = img_org[ps_bbox[1]:ps_bbox[3],
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ps_bbox[0]:ps_bbox[2], :]
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if 'columns_width' in list(config_params.keys()) and num_col:
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img_org = resize_image(img_org, y_new, x_new)
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@ -1326,6 +1296,7 @@ def find_new_features_of_contours(contours_main):
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y_max_main = np.array([np.max(contours_main[j][:, 1]) for j in range(len(contours_main))])
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return cx_main, cy_main, x_min_main, x_max_main, y_min_main, y_max_main, y_corr_x_min_from_argmin
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def read_xml(xml_file):
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file_name = Path(xml_file).stem
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tree1 = ET.parse(xml_file, parser = ET.XMLParser(encoding='utf-8'))
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@ -1344,57 +1315,13 @@ def read_xml(xml_file):
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index_tot_regions.append(jj.attrib['index'])
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tot_region_ref.append(jj.attrib['regionRef'])
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if (link+'PrintSpace' in alltags) or (link+'Border' in alltags):
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co_printspace = []
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if link+'PrintSpace' in alltags:
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region_tags_printspace = np.unique([x for x in alltags if x.endswith('PrintSpace')])
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elif link+'Border' in alltags:
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region_tags_printspace = np.unique([x for x in alltags if x.endswith('Border')])
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for tag in region_tags_printspace:
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if link+'PrintSpace' in alltags:
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tag_endings_printspace = ['}PrintSpace','}printspace']
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elif link+'Border' in alltags:
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tag_endings_printspace = ['}Border','}border']
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if tag.endswith(tag_endings_printspace[0]) or tag.endswith(tag_endings_printspace[1]):
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for nn in root1.iter(tag):
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c_t_in = []
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sumi = 0
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for vv in nn.iter():
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# check the format of coords
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if vv.tag == link + 'Coords':
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coords = bool(vv.attrib)
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if coords:
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p_h = vv.attrib['points'].split(' ')
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c_t_in.append(
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np.array([[int(x.split(',')[0]), int(x.split(',')[1])] for x in p_h]))
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break
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ps = (root1.xpath('/pc:PcGts/pc:Page/pc:Border', namespaces=NS) +
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root1.xpath('/pc:PcGts/pc:Page/pc:PrintSpace', namespaces=NS))
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if len(ps):
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points = ps[0].find('pc:Coords', NS).get('points')
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ps_bbox = bbox_from_points(points)
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else:
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pass
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if vv.tag == link + 'Point':
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c_t_in.append([int(float(vv.attrib['x'])), int(float(vv.attrib['y']))])
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sumi += 1
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elif vv.tag != link + 'Point' and sumi >= 1:
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break
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co_printspace.append(np.array(c_t_in))
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img_printspace = np.zeros( (y_len,x_len,3) )
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img_printspace=cv2.fillPoly(img_printspace, pts =co_printspace, color=(1,1,1))
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img_printspace = img_printspace.astype(np.uint8)
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imgray = cv2.cvtColor(img_printspace, cv2.COLOR_BGR2GRAY)
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_, thresh = cv2.threshold(imgray, 0, 255, 0)
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contours, _ = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
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cnt_size = np.array([cv2.contourArea(contours[j]) for j in range(len(contours))])
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cnt = contours[np.argmax(cnt_size)]
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x, y, w, h = cv2.boundingRect(cnt)
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bb_coord_printspace = [x, y, w, h]
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else:
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bb_coord_printspace = None
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ps_bbox = [0, 0, None, None]
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region_tags=np.unique([x for x in alltags if x.endswith('Region')])
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co_text_paragraph=[]
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@ -1749,11 +1676,19 @@ def read_xml(xml_file):
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img_poly=cv2.fillPoly(img, pts =co_img, color=(4,4,4))
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img_poly=cv2.fillPoly(img, pts =co_sep, color=(5,5,5))
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return tree1, root1, bb_coord_printspace, file_name, id_paragraph, id_header+id_heading, co_text_paragraph, co_text_header+co_text_heading,\
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tot_region_ref,x_len, y_len,index_tot_regions, img_poly
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return (tree1,
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root1,
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ps_bbox,
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file_name,
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id_paragraph,
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id_header + id_heading,
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co_text_paragraph,
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co_text_header + co_text_heading,
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tot_region_ref,
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x_len,
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y_len,
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index_tot_regions,
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img_poly)
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def bounding_box(cnt,color, corr_order_index ):
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x, y, w, h = cv2.boundingRect(cnt)
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@ -196,7 +196,7 @@ class SBBPredict:
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img_height = self.config_params_model['input_height']
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img_width = self.config_params_model['input_width']
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tree_xml, root_xml, bb_coord_printspace, file_name, \
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tree_xml, root_xml, ps_bbox, file_name, \
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id_paragraph, id_header, \
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co_text_paragraph, co_text_header, \
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tot_region_ref, x_len, y_len, index_tot_regions, \
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@ -236,15 +236,13 @@ class SBBPredict:
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img_label=cv2.fillPoly(img_label, pts =[co_text_all[i]], color=(1,1,1))
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labels_con[:,:,i] = img_label[:,:,0]
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if bb_coord_printspace:
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#bb_coord_printspace[x,y,w,h,_,_]
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x = bb_coord_printspace[0]
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y = bb_coord_printspace[1]
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w = bb_coord_printspace[2]
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h = bb_coord_printspace[3]
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labels_con = labels_con[y:y+h, x:x+w, :]
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img_poly = img_poly[y:y+h, x:x+w, :]
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img_header_and_sep = img_header_and_sep[y:y+h, x:x+w]
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if ps_bbox:
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labels_con = labels_con[ps_bbox[1]:ps_bbox[3],
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ps_bbox[0]:ps_bbox[2], :]
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img_poly = img_poly[ps_bbox[1]:ps_bbox[3],
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ps_bbox[0]:ps_bbox[2], :]
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img_header_and_sep = img_header_and_sep[ps_bbox[1]:ps_bbox[3],
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ps_bbox[0]:ps_bbox[2]]
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