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eynollah
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few minor fixes

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code-suggestions
cneud 2 weeks ago
parent b4d168cae3
commit 62e8d78e73
3 changed files with 19 additions and 41 deletions
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9
src/eynollah/sbb_binarize.py
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@ -1,27 +1,22 @@
""" """
Tool to load model and binarize a given image. Load model and binarize a given image.
""" """
import os
import sys import sys
from glob import glob from glob import glob
from os import environ, devnull from os import environ, devnull
from os.path import join from os.path import join
from warnings import catch_warnings, simplefilter from warnings import catch_warnings, simplefilter
import os
import numpy as np import numpy as np
from PIL import Image from PIL import Image
import cv2 import cv2
environ['TF_CPP_MIN_LOG_LEVEL'] = '3' environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
stderr = sys.stderr stderr = sys.stderr
sys.stderr = open(devnull, 'w') sys.stderr = open(devnull, 'w')
import tensorflow as tf import tensorflow as tf
from tensorflow.keras.models import load_model from tensorflow.keras.models import load_model
from tensorflow.python.keras import backend as tensorflow_backend from tensorflow.python.keras import backend as tensorflow_backend
sys.stderr = stderr sys.stderr = stderr
import logging import logging

45
src/eynollah/utils/drop_capitals.py
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@ -112,15 +112,12 @@ def adhere_drop_capital_region_into_corresponding_textline(
# print(arg_min) # print(arg_min)
cnt_nearest = np.copy(all_found_textline_polygons[int(region_final)][arg_min]) cnt_nearest = np.copy(all_found_textline_polygons[int(region_final)][arg_min])
cnt_nearest[:, 0, 0] = all_found_textline_polygons[int(region_final)][arg_min][:, 0, cnt_nearest[:, 0, 0] = all_found_textline_polygons[int(region_final)][arg_min][:, 0, 0] # +all_box_coord[int(region_final)][2]
0] # +all_box_coord[int(region_final)][2] cnt_nearest[:, 0, 1] = all_found_textline_polygons[int(region_final)][arg_min][:, 0, 1] # +all_box_coord[int(region_final)][0]
cnt_nearest[:, 0, 1] = all_found_textline_polygons[int(region_final)][arg_min][:, 0,
1] # +all_box_coord[int(region_final)][0]
img_textlines = np.zeros((text_regions_p.shape[0], text_regions_p.shape[1], 3)) img_textlines = np.zeros((text_regions_p.shape[0], text_regions_p.shape[1], 3))
img_textlines = cv2.fillPoly(img_textlines, pts=[cnt_nearest], color=(255, 255, 255)) img_textlines = cv2.fillPoly(img_textlines, pts=[cnt_nearest], color=(255, 255, 255))
img_textlines = cv2.fillPoly(img_textlines, pts=[polygons_of_drop_capitals[i_drop]], img_textlines = cv2.fillPoly(img_textlines, pts=[polygons_of_drop_capitals[i_drop]], color=(255, 255, 255))
color=(255, 255, 255))
img_textlines = img_textlines.astype(np.uint8) img_textlines = img_textlines.astype(np.uint8)
@ -180,15 +177,12 @@ def adhere_drop_capital_region_into_corresponding_textline(
# print(arg_min) # print(arg_min)
cnt_nearest = np.copy(all_found_textline_polygons[int(region_final)][arg_min]) cnt_nearest = np.copy(all_found_textline_polygons[int(region_final)][arg_min])
cnt_nearest[:, 0, 0] = all_found_textline_polygons[int(region_final)][arg_min][:, 0, cnt_nearest[:, 0, 0] = all_found_textline_polygons[int(region_final)][arg_min][:, 0, 0] # +all_box_coord[int(region_final)][2]
0] # +all_box_coord[int(region_final)][2] cnt_nearest[:, 0, 1] = all_found_textline_polygons[int(region_final)][arg_min][:, 0, 1] # +all_box_coord[int(region_final)][0]
cnt_nearest[:, 0, 1] = all_found_textline_polygons[int(region_final)][arg_min][:, 0,
1] # +all_box_coord[int(region_final)][0]
img_textlines = np.zeros((text_regions_p.shape[0], text_regions_p.shape[1], 3)) img_textlines = np.zeros((text_regions_p.shape[0], text_regions_p.shape[1], 3))
img_textlines = cv2.fillPoly(img_textlines, pts=[cnt_nearest], color=(255, 255, 255)) img_textlines = cv2.fillPoly(img_textlines, pts=[cnt_nearest], color=(255, 255, 255))
img_textlines = cv2.fillPoly(img_textlines, pts=[polygons_of_drop_capitals[i_drop]], img_textlines = cv2.fillPoly(img_textlines, pts=[polygons_of_drop_capitals[i_drop]], color=(255, 255, 255))
color=(255, 255, 255))
img_textlines = img_textlines.astype(np.uint8) img_textlines = img_textlines.astype(np.uint8)
@ -238,15 +232,12 @@ def adhere_drop_capital_region_into_corresponding_textline(
# print(arg_min) # print(arg_min)
cnt_nearest = np.copy(all_found_textline_polygons[int(region_final)][arg_min]) cnt_nearest = np.copy(all_found_textline_polygons[int(region_final)][arg_min])
cnt_nearest[:, 0, 0] = all_found_textline_polygons[int(region_final)][arg_min][:, 0, cnt_nearest[:, 0, 0] = all_found_textline_polygons[int(region_final)][arg_min][:, 0, 0] # +all_box_coord[int(region_final)][2]
0] # +all_box_coord[int(region_final)][2] cnt_nearest[:, 0, 1] = all_found_textline_polygons[int(region_final)][arg_min][:, 0, 1] # +all_box_coord[int(region_final)][0]
cnt_nearest[:, 0, 1] = all_found_textline_polygons[int(region_final)][arg_min][:, 0,
1] # +all_box_coord[int(region_final)][0]
img_textlines = np.zeros((text_regions_p.shape[0], text_regions_p.shape[1], 3)) img_textlines = np.zeros((text_regions_p.shape[0], text_regions_p.shape[1], 3))
img_textlines = cv2.fillPoly(img_textlines, pts=[cnt_nearest], color=(255, 255, 255)) img_textlines = cv2.fillPoly(img_textlines, pts=[cnt_nearest], color=(255, 255, 255))
img_textlines = cv2.fillPoly(img_textlines, pts=[polygons_of_drop_capitals[i_drop]], img_textlines = cv2.fillPoly(img_textlines, pts=[polygons_of_drop_capitals[i_drop]], color=(255, 255, 255))
color=(255, 255, 255))
img_textlines = img_textlines.astype(np.uint8) img_textlines = img_textlines.astype(np.uint8)
contours_combined = return_contours_of_interested_region(img_textlines, 255, 0) contours_combined = return_contours_of_interested_region(img_textlines, 255, 0)
@ -356,15 +347,12 @@ def adhere_drop_capital_region_into_corresponding_textline(
# print(arg_min) # print(arg_min)
cnt_nearest = np.copy(all_found_textline_polygons[int(region_final)][arg_min]) cnt_nearest = np.copy(all_found_textline_polygons[int(region_final)][arg_min])
cnt_nearest[:, 0] = all_found_textline_polygons[int(region_final)][arg_min][:, 0] + \ cnt_nearest[:, 0] = all_found_textline_polygons[int(region_final)][arg_min][:, 0] + all_box_coord[int(region_final)][2]
all_box_coord[int(region_final)][2] cnt_nearest[:, 1] = all_found_textline_polygons[int(region_final)][arg_min][:, 1] + all_box_coord[int(region_final)][0]
cnt_nearest[:, 1] = all_found_textline_polygons[int(region_final)][arg_min][:, 1] + \
all_box_coord[int(region_final)][0]
img_textlines = np.zeros((text_regions_p.shape[0], text_regions_p.shape[1], 3)) img_textlines = np.zeros((text_regions_p.shape[0], text_regions_p.shape[1], 3))
img_textlines = cv2.fillPoly(img_textlines, pts=[cnt_nearest], color=(255, 255, 255)) img_textlines = cv2.fillPoly(img_textlines, pts=[cnt_nearest], color=(255, 255, 255))
img_textlines = cv2.fillPoly(img_textlines, pts=[polygons_of_drop_capitals[i_drop]], img_textlines = cv2.fillPoly(img_textlines, pts=[polygons_of_drop_capitals[i_drop]], color=(255, 255, 255))
color=(255, 255, 255))
img_textlines = img_textlines.astype(np.uint8) img_textlines = img_textlines.astype(np.uint8)
contours_combined = return_contours_of_interested_region(img_textlines, 255, 0) contours_combined = return_contours_of_interested_region(img_textlines, 255, 0)
@ -424,15 +412,12 @@ def adhere_drop_capital_region_into_corresponding_textline(
# print(arg_min) # print(arg_min)
cnt_nearest = np.copy(all_found_textline_polygons[int(region_final)][arg_min]) cnt_nearest = np.copy(all_found_textline_polygons[int(region_final)][arg_min])
cnt_nearest[:, 0] = all_found_textline_polygons[int(region_final)][arg_min][:, 0] + \ cnt_nearest[:, 0] = all_found_textline_polygons[int(region_final)][arg_min][:, 0] + all_box_coord[int(region_final)][2]
all_box_coord[int(region_final)][2] cnt_nearest[:, 1] = all_found_textline_polygons[int(region_final)][arg_min][:, 1] + all_box_coord[int(region_final)][0]
cnt_nearest[:, 1] = all_found_textline_polygons[int(region_final)][arg_min][:, 1] + \
all_box_coord[int(region_final)][0]
img_textlines = np.zeros((text_regions_p.shape[0], text_regions_p.shape[1], 3)) img_textlines = np.zeros((text_regions_p.shape[0], text_regions_p.shape[1], 3))
img_textlines = cv2.fillPoly(img_textlines, pts=[cnt_nearest], color=(255, 255, 255)) img_textlines = cv2.fillPoly(img_textlines, pts=[cnt_nearest], color=(255, 255, 255))
img_textlines = cv2.fillPoly(img_textlines, pts=[polygons_of_drop_capitals[i_drop]], img_textlines = cv2.fillPoly(img_textlines, pts=[polygons_of_drop_capitals[i_drop]], color=(255, 255, 255))
color=(255, 255, 255))
img_textlines = img_textlines.astype(np.uint8) img_textlines = img_textlines.astype(np.uint8)
contours_combined = return_contours_of_interested_region(img_textlines, 255, 0) contours_combined = return_contours_of_interested_region(img_textlines, 255, 0)

6
src/eynollah/utils/marginals.py
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@ -126,8 +126,7 @@ def get_marginals(text_with_lines, text_regions, num_col, slope_deskew, light_ve
polygons_of_marginals = return_contours_of_interested_region(text_regions, pixel_img, min_area_text) polygons_of_marginals = return_contours_of_interested_region(text_regions, pixel_img, min_area_text)
cx_text_only, cy_text_only, x_min_text_only, x_max_text_only, y_min_text_only, y_max_text_only, y_cor_x_min_main = find_new_features_of_contours( (cx_text_only, cy_text_only, x_min_text_only, x_max_text_only, y_min_text_only, y_max_text_only, y_cor_x_min_main) = (find_new_features_of_contours(polygons_of_marginals))
polygons_of_marginals)
text_regions[(text_regions[:, :] == 4)] = 1 text_regions[(text_regions[:, :] == 4)] = 1
@ -155,8 +154,7 @@ def get_marginals(text_with_lines, text_regions, num_col, slope_deskew, light_ve
polygons_of_marginals = return_contours_of_interested_region(text_regions, pixel_img, min_area_text) polygons_of_marginals = return_contours_of_interested_region(text_regions, pixel_img, min_area_text)
cx_text_only, cy_text_only, x_min_text_only, x_max_text_only, y_min_text_only, y_max_text_only, y_cor_x_min_main = find_new_features_of_contours( (cx_text_only, cy_text_only, x_min_text_only, x_max_text_only, y_min_text_only, y_max_text_only, y_cor_x_min_main) = (find_new_features_of_contours(polygons_of_marginals))
polygons_of_marginals)
text_regions[(text_regions[:, :] == 4)] = 1 text_regions[(text_regions[:, :] == 4)] = 1

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