From 4c81fa2e46d67a07315bf0cc35f43616a44dfd50 Mon Sep 17 00:00:00 2001 From: Konstantin Baierer Date: Wed, 24 Feb 2021 16:05:30 +0100 Subject: [PATCH] simplify constructs, remove print-debugging stmts --- sbb_newspapers_org_image/eynollah.py | 52 +++++----------------------- 1 file changed, 9 insertions(+), 43 deletions(-) diff --git a/sbb_newspapers_org_image/eynollah.py b/sbb_newspapers_org_image/eynollah.py index b4779da..258bedf 100644 --- a/sbb_newspapers_org_image/eynollah.py +++ b/sbb_newspapers_org_image/eynollah.py @@ -1392,11 +1392,11 @@ class eynollah: con_inter_box = [] con_inter_box_h = [] - for i in range(len(args_contours_box)): - con_inter_box.append(contours_only_text_parent[args_contours_box[i]]) + for box in args_contours_box: + con_inter_box.append(contours_only_text_parent[box]) - for i in range(len(args_contours_box_h)): - con_inter_box_h.append(contours_only_text_parent_h[args_contours_box_h[i]]) + for box in args_contours_box_h: + con_inter_box_h.append(contours_only_text_parent_h[box]) indexes_sorted, matrix_of_orders, kind_of_texts_sorted, index_by_kind_sorted = order_of_regions(textline_mask_tot[int(boxes[iij][2]) : int(boxes[iij][3]), int(boxes[iij][0]) : int(boxes[iij][1])], con_inter_box, con_inter_box_h, boxes[iij][2]) @@ -1431,8 +1431,7 @@ class eynollah: order_text_new = [] for iii in range(len(order_of_texts_tot)): - tartib_new = np.where(np.array(order_of_texts_tot) == iii)[0][0] - order_text_new.append(tartib_new) + order_text_new.append(np.where(np.array(order_of_texts_tot) == iii)[0][0]) except Exception as why: self.logger.error(why) @@ -1506,8 +1505,7 @@ class eynollah: order_text_new = [] for iii in range(len(order_of_texts_tot)): - tartib_new = np.where(np.array(order_of_texts_tot) == iii)[0][0] - order_text_new.append(tartib_new) + order_text_new.append(np.where(np.array(order_of_texts_tot) == iii)[0][0]) return order_text_new, id_of_texts_tot def do_order_of_regions_no_full_layout(self, contours_only_text_parent, contours_only_text_parent_h, boxes, textline_mask_tot): @@ -1557,8 +1555,7 @@ class eynollah: order_text_new = [] for iii in range(len(order_of_texts_tot)): - tartib_new = np.where(np.array(order_of_texts_tot) == iii)[0][0] - order_text_new.append(tartib_new) + order_text_new.append(np.where(np.array(order_of_texts_tot) == iii)[0][0]) except Exception as why: self.logger.error(why) @@ -1590,7 +1587,7 @@ class eynollah: indexes_sorted_main = np.array(indexes_sorted)[np.array(kind_of_texts_sorted) == 1] indexes_by_type_main = np.array(index_by_kind_sorted)[np.array(kind_of_texts_sorted) == 1] - for zahler, mtv in enumerate(args_contours_box): + for zahler, _ in enumerate(args_contours_box): arg_order_v = indexes_sorted_main[zahler] tartib = np.where(indexes_sorted == arg_order_v)[0][0] order_by_con_main[args_contours_box[indexes_by_type_main[zahler]]] = tartib + ref_point @@ -1606,8 +1603,7 @@ class eynollah: order_text_new = [] for iii in range(len(order_of_texts_tot)): - tartib_new = np.where(np.array(order_of_texts_tot) == iii)[0][0] - order_text_new.append(tartib_new) + order_text_new.append(np.where(np.array(order_of_texts_tot) == iii)[0][0]) return order_text_new, id_of_texts_tot @@ -1675,11 +1671,7 @@ class eynollah: scaler_h_textline = 1 # 1.2#1.2 scaler_w_textline = 1 # 0.9#1 textline_mask_tot_ea, _ = self.textline_contours(image_page, True, scaler_h_textline, scaler_w_textline) - K.clear_session() - #print(np.unique(textline_mask_tot_ea[:, :]), "textline") - # plt.imshow(textline_mask_tot_ea) - # plt.show() if self.plotter: self.plotter.save_plot_of_textlines(textline_mask_tot_ea, image_page) return textline_mask_tot_ea @@ -1878,21 +1870,9 @@ class eynollah: # plt.imshow(img_revised_tab) # plt.show() - # print(img_revised_tab.shape,text_regions_p_1_n.shape) - # text_regions_p_1_n=resize_image(text_regions_p_1_n,img_revised_tab.shape[0],img_revised_tab.shape[1]) - # print(np.unique(text_regions_p_1_n),'uni') - text_only = ((img_revised_tab[:, :] == 1)) * 1 if np.abs(slope_deskew) >= SLOPE_THRESHOLD: text_only_d = ((text_regions_p_1_n[:, :] == 1)) * 1 - ##text_only_h=( (img_revised_tab[:,:,0]==2) )*1 - - # print(text_only.shape,text_only_d.shape) - # plt.imshow(text_only) - # plt.show() - - # plt.imshow(text_only_d) - # plt.show() min_con_area = 0.000005 if np.abs(slope_deskew) >= SLOPE_THRESHOLD: @@ -1943,26 +1923,12 @@ class eynollah: x_diff = p_big[0] - cx_bigest_d_big y_diff = p_big[1] - cy_biggest_d_big - # print(p_big) - # print(cx_bigest_d_big,cy_biggest_d_big) - # print(x_diff,y_diff) - contours_only_text_parent_d_ordered = [] for i in range(len(contours_only_text_parent)): - # img1=np.zeros((text_only.shape[0],text_only.shape[1],3)) - # img1=cv2.fillPoly(img1,pts=[contours_only_text_parent[i]] ,color=(1,1,1)) - # plt.imshow(img1[:,:,0]) - # plt.show() - p = np.dot(M_22, [cx_bigest[i], cy_biggest[i]]) - # print(p) p[0] = p[0] - x_diff[0] p[1] = p[1] - y_diff[0] - # print(p) - # print(cx_bigest_d) - # print(cy_biggest_d) dists = [math.sqrt((p[0] - cx_bigest_d[j]) ** 2 + (p[1] - cy_biggest_d[j]) ** 2) for j in range(len(cx_bigest_d))] - # print(np.argmin(dists)) contours_only_text_parent_d_ordered.append(contours_only_text_parent_d[np.argmin(dists)]) # img2=np.zeros((text_only.shape[0],text_only.shape[1],3)) # img2=cv2.fillPoly(img2,pts=[contours_only_text_parent_d[np.argmin(dists)]] ,color=(1,1,1))