From 254dd356663ae238dbba7adc123fc207b97eeb64 Mon Sep 17 00:00:00 2001 From: Konstantin Baierer Date: Wed, 24 Feb 2021 13:48:20 +0100 Subject: [PATCH] MAX_SLOPE constant --- sbb_newspapers_org_image/eynollah.py | 37 ++++++---------------------- 1 file changed, 7 insertions(+), 30 deletions(-) diff --git a/sbb_newspapers_org_image/eynollah.py b/sbb_newspapers_org_image/eynollah.py index 78fc523..0267f12 100644 --- a/sbb_newspapers_org_image/eynollah.py +++ b/sbb_newspapers_org_image/eynollah.py @@ -3,7 +3,6 @@ tool to extract table form data from alto xml data """ -import gc import math import os import sys @@ -91,6 +90,7 @@ from .plot import EynollahPlotter SLOPE_THRESHOLD = 0.13 RATIO_OF_TWO_MODEL_THRESHOLD = 95.50 #98.45: DPI_THRESHOLD = 298 +MAX_SLOPE = 999 class eynollah: def __init__( @@ -357,19 +357,13 @@ class eynollah: _, page_coord = self.early_page_for_num_of_column_classification() model_num_classifier, session_col_classifier = self.start_new_session_and_model(self.model_dir_of_col_classifier) - img_1ch = self.imread(grayscale=True) - width_early = img_1ch.shape[1] - img_1ch = img_1ch[page_coord[0] : page_coord[1], page_coord[2] : page_coord[3]] - # plt.imshow(img_1ch) # plt.show() img_1ch = img_1ch / 255.0 - img_1ch = cv2.resize(img_1ch, (448, 448), interpolation=cv2.INTER_NEAREST) - img_in = np.zeros((1, img_1ch.shape[0], img_1ch.shape[1], 3)) img_in[0, :, :, 0] = img_1ch[:, :] img_in[0, :, :, 1] = img_1ch[:, :] @@ -380,9 +374,7 @@ class eynollah: label_p_pred = model_num_classifier.predict(img_in) num_col = np.argmax(label_p_pred[0]) + 1 - self.logger.info("Found %s columns (%s)", num_col, label_p_pred) - session_col_classifier.close() K.clear_session() @@ -430,8 +422,6 @@ class eynollah: self.scale_y = img_res.shape[0] / float(self.image_org.shape[0]) self.scale_x = img_res.shape[1] / float(self.image_org.shape[1]) - - def start_new_session_and_model(self, model_dir): self.logger.debug("enter start_new_session_and_model (model_dir=%s)", model_dir) @@ -864,9 +854,9 @@ class eynollah: # text_patch_processed=textline_contours_postprocessing(gada) except Exception as why: self.logger.error(why) - slope_for_all = 999 + slope_for_all = MAX_SLOPE - if slope_for_all == 999: + if slope_for_all == MAX_SLOPE: slope_for_all = [slope_deskew][0] slopes_per_each_subprocess.append(slope_for_all) @@ -975,9 +965,9 @@ class eynollah: slope_for_all = [slope_deskew][0] except Exception as why: self.logger.error(why) - slope_for_all = 999 + slope_for_all = MAX_SLOPE - if slope_for_all == 999: + if slope_for_all == MAX_SLOPE: slope_for_all = [slope_deskew][0] slopes_per_each_subprocess.append(slope_for_all) mask_only_con_region = np.zeros(textline_mask_tot_ea.shape) @@ -1049,9 +1039,9 @@ class eynollah: slope_corresponding_textregion = return_deskew_slop(crop_img, sigma_des, plotter=self.plotter) except Exception as why: self.logger.error(why) - slope_corresponding_textregion = 999 + slope_corresponding_textregion = MAX_SLOPE - if slope_corresponding_textregion == 999: + if slope_corresponding_textregion == MAX_SLOPE: slope_corresponding_textregion = slope_biggest slopes_sub.append(slope_corresponding_textregion) @@ -1851,28 +1841,21 @@ class eynollah: K.clear_session() image_page = image_page.astype(np.uint8) - # print(type(image_page)) regions_fully, regions_fully_only_drop = self.extract_text_regions(image_page, True, cols=num_col_classifier) text_regions_p[:,:][regions_fully[:,:,0]==6]=6 - regions_fully_only_drop = put_drop_out_from_only_drop_model(regions_fully_only_drop, text_regions_p) regions_fully[:, :, 0][regions_fully_only_drop[:, :, 0] == 4] = 4 K.clear_session() # plt.imshow(regions_fully[:,:,0]) # plt.show() - regions_fully = putt_bb_of_drop_capitals_of_model_in_patches_in_layout(regions_fully) - # plt.imshow(regions_fully[:,:,0]) # plt.show() - K.clear_session() regions_fully_np, _ = self.extract_text_regions(image_page, False, cols=num_col_classifier) - # plt.imshow(regions_fully_np[:,:,0]) # plt.show() - if num_col_classifier > 2: regions_fully_np[:, :, 0][regions_fully_np[:, :, 0] == 4] = 0 else: @@ -1880,20 +1863,14 @@ class eynollah: # plt.imshow(regions_fully_np[:,:,0]) # plt.show() - K.clear_session() - # plt.imshow(regions_fully[:,:,0]) # plt.show() - regions_fully = boosting_headers_by_longshot_region_segmentation(regions_fully, regions_fully_np, img_only_regions) - # plt.imshow(regions_fully[:,:,0]) # plt.show() - text_regions_p[:, :][regions_fully[:, :, 0] == 4] = 4 text_regions_p[:, :][regions_fully_np[:, :, 0] == 4] = 4 - #plt.imshow(text_regions_p) #plt.show()