typo: s,contoures,contours,g

qurator/eynollah/eynollah.py

@@ -32,7 +32,7 @@ warnings.filterwarnings("ignore")
 from .utils.contour import (
     filter_contours_area_of_image,
     find_contours_mean_y_diff,
-    find_new_features_of_contoures,
+    find_new_features_of_contours,
     get_text_region_boxes_by_given_contours,
     get_textregion_contours_in_org_image,
     return_contours_of_image,
@@ -1124,8 +1124,8 @@ class Eynollah:
 
     def do_order_of_regions_full_layout(self, contours_only_text_parent, contours_only_text_parent_h, boxes, textline_mask_tot):
         self.logger.debug("enter do_order_of_regions_full_layout")
-        cx_text_only, cy_text_only, x_min_text_only, _, _, _, y_cor_x_min_main = find_new_features_of_contoures(contours_only_text_parent)
+        cx_text_only, cy_text_only, x_min_text_only, _, _, _, y_cor_x_min_main = find_new_features_of_contours(contours_only_text_parent)
-        cx_text_only_h, cy_text_only_h, x_min_text_only_h, _, _, _, y_cor_x_min_main_h = find_new_features_of_contoures(contours_only_text_parent_h)
+        cx_text_only_h, cy_text_only_h, x_min_text_only_h, _, _, _, y_cor_x_min_main_h = find_new_features_of_contours(contours_only_text_parent_h)
 
         try:
             arg_text_con = []
@@ -1274,7 +1274,7 @@ class Eynollah:
 
     def do_order_of_regions_no_full_layout(self, contours_only_text_parent, contours_only_text_parent_h, boxes, textline_mask_tot):
         self.logger.debug("enter do_order_of_regions_no_full_layout")
-        cx_text_only, cy_text_only, x_min_text_only, _, _, _, y_cor_x_min_main = find_new_features_of_contoures(contours_only_text_parent)
+        cx_text_only, cy_text_only, x_min_text_only, _, _, _, y_cor_x_min_main = find_new_features_of_contours(contours_only_text_parent)
 
         try:
             arg_text_con = []
@@ -1655,8 +1655,8 @@ class Eynollah:
             contours_only_text_parent = list(np.array(contours_only_text_parent)[index_con_parents])
             areas_cnt_text_parent = list(np.array(areas_cnt_text_parent)[index_con_parents])
 
-            cx_bigest_big, cy_biggest_big, _, _, _, _, _ = find_new_features_of_contoures([contours_biggest])
+            cx_bigest_big, cy_biggest_big, _, _, _, _, _ = find_new_features_of_contours([contours_biggest])
-            cx_bigest, cy_biggest, _, _, _, _, _ = find_new_features_of_contoures(contours_only_text_parent)
+            cx_bigest, cy_biggest, _, _, _, _, _ = find_new_features_of_contours(contours_only_text_parent)
 
             contours_only_text_d, hir_on_text_d = return_contours_of_image(text_only_d)
             contours_only_text_parent_d = return_parent_contours(contours_only_text_d, hir_on_text_d)
@@ -1669,8 +1669,8 @@ class Eynollah:
             contours_only_text_parent_d=list(np.array(contours_only_text_parent_d)[index_con_parents_d] )
             areas_cnt_text_d=list(np.array(areas_cnt_text_d)[index_con_parents_d] )
 
-            cx_bigest_d_big, cy_biggest_d_big, _, _, _, _, _ = find_new_features_of_contoures([contours_biggest_d])
+            cx_bigest_d_big, cy_biggest_d_big, _, _, _, _, _ = find_new_features_of_contours([contours_biggest_d])
-            cx_bigest_d, cy_biggest_d, _, _, _, _, _ = find_new_features_of_contoures(contours_only_text_parent_d)
+            cx_bigest_d, cy_biggest_d, _, _, _, _, _ = find_new_features_of_contours(contours_only_text_parent_d)
             try:
                 cx_bigest_d_last5 = cx_bigest_d[-5:]
                 cy_biggest_d_last5 = cy_biggest_d[-5:]
@@ -1715,8 +1715,8 @@ class Eynollah:
             contours_only_text_parent = list(np.array(contours_only_text_parent)[index_con_parents])
             areas_cnt_text_parent = list(np.array(areas_cnt_text_parent)[index_con_parents])
 
-            cx_bigest_big, cy_biggest_big, _, _, _, _, _ = find_new_features_of_contoures([contours_biggest])
+            cx_bigest_big, cy_biggest_big, _, _, _, _, _ = find_new_features_of_contours([contours_biggest])
-            cx_bigest, cy_biggest, _, _, _, _, _ = find_new_features_of_contoures(contours_only_text_parent)
+            cx_bigest, cy_biggest, _, _, _, _, _ = find_new_features_of_contours(contours_only_text_parent)
             self.logger.debug('areas_cnt_text_parent %s', areas_cnt_text_parent)
             # self.logger.debug('areas_cnt_text_parent_d %s', areas_cnt_text_parent_d)
             # self.logger.debug('len(contours_only_text_parent) %s', len(contours_only_text_parent_d))

qurator/eynollah/plot.py

@@ -153,10 +153,10 @@ class EynollahPlotter():
             plt.legend(loc='best')
             plt.savefig(os.path.join(self.dir_of_all, self.image_filename_stem+'_rotation_angle.png'))
 
-    def write_images_into_directory(self, img_contoures, image_page):
+    def write_images_into_directory(self, img_contours, image_page):
         if self.dir_of_cropped_images is not None:
             index = 0
-            for cont_ind in img_contoures:
+            for cont_ind in img_contours:
                 x, y, w, h = cv2.boundingRect(cont_ind)
                 box = [x, y, w, h]
                 croped_page, page_coord = crop_image_inside_box(box, image_page)

qurator/eynollah/utils/__init__.py

@@ -10,7 +10,7 @@ from scipy.ndimage import gaussian_filter1d
 
 from .is_nan import isNaN
 from .contour import (contours_in_same_horizon,
-                      find_new_features_of_contoures,
+                      find_new_features_of_contours,
                       return_contours_of_image,
                       return_parent_contours)
 
@@ -783,7 +783,7 @@ def putt_bb_of_drop_capitals_of_model_in_patches_in_layout(layout_in_patch):
     return layout_in_patch
 
 def check_any_text_region_in_model_one_is_main_or_header(regions_model_1,regions_model_full,contours_only_text_parent,all_box_coord,all_found_texline_polygons,slopes,contours_only_text_parent_d_ordered):
-    cx_main,cy_main ,x_min_main , x_max_main, y_min_main ,y_max_main,y_corr_x_min_from_argmin=find_new_features_of_contoures(contours_only_text_parent)
+    cx_main,cy_main ,x_min_main , x_max_main, y_min_main ,y_max_main,y_corr_x_min_from_argmin=find_new_features_of_contours(contours_only_text_parent)
 
     length_con=x_max_main-x_min_main
     height_con=y_max_main-y_min_main
@@ -1267,7 +1267,7 @@ def combine_hor_lines_and_delete_cross_points_and_get_lines_features_back_new(im
         ret, thresh = cv2.threshold(imgray, 0, 255, 0)
         contours_cross,_=cv2.findContours(thresh,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
         
-        cx_cross,cy_cross ,_ , _, _ ,_,_=find_new_features_of_contoures(contours_cross)
+        cx_cross,cy_cross ,_ , _, _ ,_,_=find_new_features_of_contours(contours_cross)
         
         for ii in range(len(cx_cross)):
             img_p_in[int(cy_cross[ii])-30:int(cy_cross[ii])+30,int(cx_cross[ii])+5:int(cx_cross[ii])+40,0]=0

qurator/eynollah/utils/contour.py

@@ -75,7 +75,7 @@ def filter_contours_area_of_image_tables(image, contours, hirarchy, max_area, mi
         jv += 1
     return found_polygons_early
 
-def find_new_features_of_contoures(contours_main):
+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))]

qurator/eynollah/utils/drop_capitals.py

@@ -1,7 +1,7 @@
 import numpy as np
 import cv2
 from .contour import (
-    find_new_features_of_contoures,
+    find_new_features_of_contours,
     return_contours_of_image,
     return_parent_contours,
 )
@@ -20,9 +20,9 @@ def adhere_drop_capital_region_into_corresponding_textline(
 ):
     # print(np.shape(all_found_texline_polygons),np.shape(all_found_texline_polygons[3]),'all_found_texline_polygonsshape')
     # print(all_found_texline_polygons[3])
-    cx_m, cy_m, _, _, _, _, _ = find_new_features_of_contoures(contours_only_text_parent)
+    cx_m, cy_m, _, _, _, _, _ = find_new_features_of_contours(contours_only_text_parent)
-    cx_h, cy_h, _, _, _, _, _ = find_new_features_of_contoures(contours_only_text_parent_h)
+    cx_h, cy_h, _, _, _, _, _ = find_new_features_of_contours(contours_only_text_parent_h)
-    cx_d, cy_d, _, _, y_min_d, y_max_d, _ = find_new_features_of_contoures(polygons_of_drop_capitals)
+    cx_d, cy_d, _, _, y_min_d, y_max_d, _ = find_new_features_of_contours(polygons_of_drop_capitals)
 
     img_con_all = np.zeros((text_regions_p.shape[0], text_regions_p.shape[1], 3))
     for j_cont in range(len(contours_only_text_parent)):
@@ -87,9 +87,9 @@ def adhere_drop_capital_region_into_corresponding_textline(
                 region_final = region_with_intersected_drop[np.argmax(sum_pixels_of_intersection)] - 1
 
                 # print(region_final,'region_final')
-                # cx_t,cy_t ,_, _, _ ,_,_= find_new_features_of_contoures(all_found_texline_polygons[int(region_final)])
+                # cx_t,cy_t ,_, _, _ ,_,_= find_new_features_of_contours(all_found_texline_polygons[int(region_final)])
                 try:
-                    cx_t, cy_t, _, _, _, _, _ = find_new_features_of_contoures(all_found_texline_polygons[int(region_final)])
+                    cx_t, cy_t, _, _, _, _, _ = find_new_features_of_contours(all_found_texline_polygons[int(region_final)])
                     # print(all_box_coord[j_cont])
                     # print(cx_t)
                     # print(cy_t)
@@ -141,9 +141,9 @@ def adhere_drop_capital_region_into_corresponding_textline(
 
                 # areas_main=np.array([cv2.contourArea(all_found_texline_polygons[int(region_final)][0][j] ) for j in range(len(all_found_texline_polygons[int(region_final)]))])
 
-                # cx_t,cy_t ,_, _, _ ,_,_= find_new_features_of_contoures(all_found_texline_polygons[int(region_final)])
+                # cx_t,cy_t ,_, _, _ ,_,_= find_new_features_of_contours(all_found_texline_polygons[int(region_final)])
 
-                cx_t, cy_t, _, _, _, _, _ = find_new_features_of_contoures(all_found_texline_polygons[int(region_final)])
+                cx_t, cy_t, _, _, _, _, _ = find_new_features_of_contours(all_found_texline_polygons[int(region_final)])
                 # print(all_box_coord[j_cont])
                 # print(cx_t)
                 # print(cy_t)
@@ -191,7 +191,7 @@ def adhere_drop_capital_region_into_corresponding_textline(
                 # print(cx_t,'print')
                 try:
                     # print(all_found_texline_polygons[j_cont][0])
-                    cx_t, cy_t, _, _, _, _, _ = find_new_features_of_contoures(all_found_texline_polygons[int(region_final)])
+                    cx_t, cy_t, _, _, _, _, _ = find_new_features_of_contours(all_found_texline_polygons[int(region_final)])
                     # print(all_box_coord[j_cont])
                     # print(cx_t)
                     # print(cy_t)
@@ -238,7 +238,7 @@ def adhere_drop_capital_region_into_corresponding_textline(
             else:
                 pass
 
-            ##cx_t,cy_t ,_, _, _ ,_,_= find_new_features_of_contoures(all_found_texline_polygons[int(region_final)])
+            ##cx_t,cy_t ,_, _, _ ,_,_= find_new_features_of_contours(all_found_texline_polygons[int(region_final)])
             ###print(all_box_coord[j_cont])
             ###print(cx_t)
             ###print(cy_t)
@@ -292,9 +292,9 @@ def adhere_drop_capital_region_into_corresponding_textline(
                 region_final = region_with_intersected_drop[np.argmax(sum_pixels_of_intersection)] - 1
 
                 # print(region_final,'region_final')
-                # cx_t,cy_t ,_, _, _ ,_,_= find_new_features_of_contoures(all_found_texline_polygons[int(region_final)])
+                # cx_t,cy_t ,_, _, _ ,_,_= find_new_features_of_contours(all_found_texline_polygons[int(region_final)])
                 try:
-                    cx_t, cy_t, _, _, _, _, _ = find_new_features_of_contoures(all_found_texline_polygons[int(region_final)])
+                    cx_t, cy_t, _, _, _, _, _ = find_new_features_of_contours(all_found_texline_polygons[int(region_final)])
                     # print(all_box_coord[j_cont])
                     # print(cx_t)
                     # print(cy_t)
@@ -346,12 +346,12 @@ def adhere_drop_capital_region_into_corresponding_textline(
 
                 # areas_main=np.array([cv2.contourArea(all_found_texline_polygons[int(region_final)][0][j] ) for j in range(len(all_found_texline_polygons[int(region_final)]))])
 
-                # cx_t,cy_t ,_, _, _ ,_,_= find_new_features_of_contoures(all_found_texline_polygons[int(region_final)])
+                # cx_t,cy_t ,_, _, _ ,_,_= find_new_features_of_contours(all_found_texline_polygons[int(region_final)])
 
                 # print(cx_t,'print')
                 try:
                     # print(all_found_texline_polygons[j_cont][0])
-                    cx_t, cy_t, _, _, _, _, _ = find_new_features_of_contoures(all_found_texline_polygons[int(region_final)])
+                    cx_t, cy_t, _, _, _, _, _ = find_new_features_of_contours(all_found_texline_polygons[int(region_final)])
                     # print(all_box_coord[j_cont])
                     # print(cx_t)
                     # print(cy_t)
@@ -417,7 +417,7 @@ def adhere_drop_capital_region_into_corresponding_textline(
     #####try:
     #####if len(contours_new_parent)==1:
     ######print(all_found_texline_polygons[j_cont][0])
-    #####cx_t,cy_t ,_, _, _ ,_,_= find_new_features_of_contoures(all_found_texline_polygons[j_cont])
+    #####cx_t,cy_t ,_, _, _ ,_,_= find_new_features_of_contours(all_found_texline_polygons[j_cont])
     ######print(all_box_coord[j_cont])
     ######print(cx_t)
     ######print(cy_t)

qurator/eynollah/utils/marginals.py

@@ -4,7 +4,7 @@ from scipy.signal import find_peaks
 from scipy.ndimage import gaussian_filter1d
 
 
-from .contour import find_new_features_of_contoures, return_contours_of_interested_region
+from .contour import find_new_features_of_contours, return_contours_of_interested_region
 from .resize import resize_image
 from .rotate import rotate_image
 
@@ -185,7 +185,7 @@ def get_marginals(text_with_lines, text_regions, num_col, slope_deskew, kernel=N
         min_area_text=0.00001
         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_contoures(polygons_of_marginals)
+        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)
 
         text_regions[(text_regions[:,:]==4)]=1