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@ -2125,7 +2125,7 @@ class eynollah:
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return self.do_order_of_regions_full_layout(*args, **kwargs)
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return self.do_order_of_regions_full_layout(*args, **kwargs)
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return self.do_order_of_regions_no_full_layout(*args, **kwargs)
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return self.do_order_of_regions_no_full_layout(*args, **kwargs)
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def run_graphics_and_columns(self, text_regions_p_1, num_column_is_classified):
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def run_graphics_and_columns(self, text_regions_p_1, num_col_classifier, num_column_is_classified):
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img_g = cv2.imread(self.image_filename, cv2.IMREAD_GRAYSCALE)
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img_g = cv2.imread(self.image_filename, cv2.IMREAD_GRAYSCALE)
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img_g = img_g.astype(np.uint8)
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img_g = img_g.astype(np.uint8)
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@ -2154,19 +2154,20 @@ class eynollah:
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img_only_regions_with_sep = img_only_regions_with_sep.astype(np.uint8)
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img_only_regions_with_sep = img_only_regions_with_sep.astype(np.uint8)
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img_only_regions = cv2.erode(img_only_regions_with_sep[:, :], self.kernel, iterations=6)
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img_only_regions = cv2.erode(img_only_regions_with_sep[:, :], self.kernel, iterations=6)
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num_col_classifier = None
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try:
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try:
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num_col, peaks_neg_fin = find_num_col(img_only_regions, multiplier=6.0)
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num_col, peaks_neg_fin = find_num_col(img_only_regions, multiplier=6.0)
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if not num_column_is_classified:
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if not num_column_is_classified:
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num_col_classifier = num_col + 1
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num_col_classifier = num_col + 1
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except:
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except:
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num_col = None
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num_col = None
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peaks_neg_fin = []
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peaks_neg_fin = []
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return num_col, num_col_classifier, img_only_regions, page_coord, image_page, mask_images, mask_lines
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return num_col+1, num_col_classifier, img_only_regions, page_coord, image_page, mask_images, mask_lines, text_regions_p_1
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def run_enhancement(self):
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def run_enhancement(self):
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self.logger.info("resize and enhance image")
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self.logger.info("resize and enhance image")
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is_image_enhanced, img_org, img_res, _, num_column_is_classified = self.resize_and_enhance_image_with_column_classifier()
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is_image_enhanced, img_org, img_res, num_col_classifier, num_column_is_classified = self.resize_and_enhance_image_with_column_classifier()
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self.logger.info("Image is %senhanced", '' if is_image_enhanced else 'not ')
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self.logger.info("Image is %senhanced", '' if is_image_enhanced else 'not ')
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K.clear_session()
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K.clear_session()
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scale = 1
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scale = 1
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@ -2185,7 +2186,7 @@ class eynollah:
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if self.allow_scaling:
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if self.allow_scaling:
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img_org, img_res, is_image_enhanced = self.resize_image_with_column_classifier(is_image_enhanced)
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img_org, img_res, is_image_enhanced = self.resize_image_with_column_classifier(is_image_enhanced)
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self.get_image_and_scales_after_enhancing(img_org, img_res)
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self.get_image_and_scales_after_enhancing(img_org, img_res)
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return img_res, is_image_enhanced, num_column_is_classified
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return img_res, is_image_enhanced, num_col_classifier, num_column_is_classified
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def run_textline(self, image_page):
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def run_textline(self, image_page):
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scaler_h_textline = 1 # 1.2#1.2
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scaler_h_textline = 1 # 1.2#1.2
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@ -2228,6 +2229,8 @@ class eynollah:
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try:
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try:
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regions_without_seperators = (text_regions_p[:, :] == 1) * 1
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regions_without_seperators = (text_regions_p[:, :] == 1) * 1
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regions_without_seperators = regions_without_seperators.astype(np.uint8)
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regions_without_seperators = regions_without_seperators.astype(np.uint8)
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text_regions_p = get_marginals(rotate_image(regions_without_seperators, slope_deskew), text_regions_p, num_col_classifier, slope_deskew, kernel=self.kernel)
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text_regions_p = get_marginals(rotate_image(regions_without_seperators, slope_deskew), text_regions_p, num_col_classifier, slope_deskew, kernel=self.kernel)
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except:
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except:
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pass
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pass
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@ -2249,6 +2252,12 @@ class eynollah:
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regions_without_seperators_d = (text_regions_p_1_n[:, :] == 1) * 1
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regions_without_seperators_d = (text_regions_p_1_n[:, :] == 1) * 1
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regions_without_seperators = (text_regions_p[:, :] == 1) * 1 # ( (text_regions_p[:,:]==1) | (text_regions_p[:,:]==2) )*1 #self.return_regions_without_seperators_new(text_regions_p[:,:,0],img_only_regions)
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regions_without_seperators = (text_regions_p[:, :] == 1) * 1 # ( (text_regions_p[:,:]==1) | (text_regions_p[:,:]==2) )*1 #self.return_regions_without_seperators_new(text_regions_p[:,:,0],img_only_regions)
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if np.abs(slope_deskew) < SLOPE_THRESHOLD:
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text_regions_p_1_n = None
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textline_mask_tot_d = None
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regions_without_seperators_d = None
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pixel_lines = 3
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pixel_lines = 3
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if np.abs(slope_deskew) < SLOPE_THRESHOLD:
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if np.abs(slope_deskew) < SLOPE_THRESHOLD:
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num_col, peaks_neg_fin, matrix_of_lines_ch, spliter_y_new, seperators_closeup_n = find_number_of_columns_in_document(np.repeat(text_regions_p[:, :, np.newaxis], 3, axis=2), num_col_classifier, pixel_lines)
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num_col, peaks_neg_fin, matrix_of_lines_ch, spliter_y_new, seperators_closeup_n = find_number_of_columns_in_document(np.repeat(text_regions_p[:, :, np.newaxis], 3, axis=2), num_col_classifier, pixel_lines)
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@ -2280,9 +2289,13 @@ class eynollah:
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t1 = time.time()
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t1 = time.time()
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if np.abs(slope_deskew) < SLOPE_THRESHOLD:
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if np.abs(slope_deskew) < SLOPE_THRESHOLD:
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boxes = return_boxes_of_images_by_order_of_reading_new(spliter_y_new, regions_without_seperators, matrix_of_lines_ch, num_col_classifier)
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boxes = return_boxes_of_images_by_order_of_reading_new(spliter_y_new, regions_without_seperators, matrix_of_lines_ch, num_col_classifier)
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boxes_d = None
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self.logger.debug("len(boxes): %s", len(boxes))
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else:
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else:
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boxes_d = return_boxes_of_images_by_order_of_reading_new(spliter_y_new_d, regions_without_seperators_d, matrix_of_lines_ch_d, num_col_classifier)
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boxes_d = return_boxes_of_images_by_order_of_reading_new(spliter_y_new_d, regions_without_seperators_d, matrix_of_lines_ch_d, num_col_classifier)
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self.logger.debug("len(boxes): %s", len(boxes))
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boxes = None
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self.logger.debug("len(boxes): %s", len(boxes_d))
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self.logger.info("detecting boxes took %ss", str(time.time() - t1))
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self.logger.info("detecting boxes took %ss", str(time.time() - t1))
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img_revised_tab = text_regions_p[:, :]
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img_revised_tab = text_regions_p[:, :]
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polygons_of_images = return_contours_of_interested_region(img_revised_tab, 2)
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polygons_of_images = return_contours_of_interested_region(img_revised_tab, 2)
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@ -2291,7 +2304,7 @@ class eynollah:
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# plt.show()
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# plt.show()
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K.clear_session()
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K.clear_session()
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self.logger.debug('exit run_boxes_no_full_layout')
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self.logger.debug('exit run_boxes_no_full_layout')
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return polygons_of_images, img_revised_tab, text_regions_p_1_n, textline_mask_tot_d, regions_without_seperators_d
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return polygons_of_images, img_revised_tab, text_regions_p_1_n, textline_mask_tot_d, regions_without_seperators_d, boxes, boxes_d
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def run_boxes_full_layout(self, image_page, textline_mask_tot, text_regions_p, slope_deskew, num_col_classifier, img_only_regions):
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def run_boxes_full_layout(self, image_page, textline_mask_tot, text_regions_p, slope_deskew, num_col_classifier, img_only_regions):
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self.logger.debug('enter run_boxes_full_layout')
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self.logger.debug('enter run_boxes_full_layout')
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@ -2361,6 +2374,13 @@ class eynollah:
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regions_fully_n = resize_image(regions_fully_n, text_regions_p.shape[0], text_regions_p.shape[1])
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regions_fully_n = resize_image(regions_fully_n, text_regions_p.shape[0], text_regions_p.shape[1])
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regions_without_seperators_d = (text_regions_p_1_n[:, :] == 1) * 1
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regions_without_seperators_d = (text_regions_p_1_n[:, :] == 1) * 1
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else:
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text_regions_p_1_n = None
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textline_mask_tot_d = None
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regions_without_seperators_d = None
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regions_without_seperators = (text_regions_p[:, :] == 1) * 1 # ( (text_regions_p[:,:]==1) | (text_regions_p[:,:]==2) )*1 #self.return_regions_without_seperators_new(text_regions_p[:,:,0],img_only_regions)
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regions_without_seperators = (text_regions_p[:, :] == 1) * 1 # ( (text_regions_p[:,:]==1) | (text_regions_p[:,:]==2) )*1 #self.return_regions_without_seperators_new(text_regions_p[:,:,0],img_only_regions)
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K.clear_session()
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K.clear_session()
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@ -2369,7 +2389,7 @@ class eynollah:
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pixel_img = 5
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pixel_img = 5
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polygons_of_images = return_contours_of_interested_region(img_revised_tab, pixel_img)
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polygons_of_images = return_contours_of_interested_region(img_revised_tab, pixel_img)
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self.logger.debug('exit run_boxes_full_layout')
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self.logger.debug('exit run_boxes_full_layout')
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return polygons_of_images, img_revised_tab, text_regions_p_1_n, textline_mask_tot_d, regions_without_seperators_d, regions_fully
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return polygons_of_images, img_revised_tab, text_regions_p_1_n, textline_mask_tot_d, regions_without_seperators_d, regions_fully, regions_without_seperators
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def run(self):
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def run(self):
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"""
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"""
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@ -2378,7 +2398,7 @@ class eynollah:
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self.logger.debug("enter run")
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self.logger.debug("enter run")
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t1 = time.time()
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t1 = time.time()
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img_res, is_image_enhanced, num_column_is_classified = self.run_enhancement()
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img_res, is_image_enhanced, num_col_classifier, num_column_is_classified = self.run_enhancement()
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self.logger.info("Enhancing took %ss ", str(time.time() - t1))
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self.logger.info("Enhancing took %ss ", str(time.time() - t1))
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t1 = time.time()
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t1 = time.time()
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@ -2386,10 +2406,11 @@ class eynollah:
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self.logger.info("Textregion detection took %ss ", str(time.time() - t1))
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self.logger.info("Textregion detection took %ss ", str(time.time() - t1))
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t1 = time.time()
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t1 = time.time()
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num_col, num_col_classifier, img_only_regions, page_coord, image_page, mask_images, mask_lines = \
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num_col, num_col_classifier, img_only_regions, page_coord, image_page, mask_images, mask_lines, text_regions_p_1 = \
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self.run_graphics_and_columns(text_regions_p_1, num_column_is_classified)
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self.run_graphics_and_columns(text_regions_p_1, num_col_classifier, num_column_is_classified)
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self.logger.info("Graphics detection took %ss ", str(time.time() - t1))
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self.logger.info("Graphics detection took %ss ", str(time.time() - t1))
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if not num_col:
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if not num_col:
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self.logger.info("No columns detected, outputting an empty PAGE-XML")
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self.logger.info("No columns detected, outputting an empty PAGE-XML")
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self.write_into_page_xml([], page_coord, self.dir_out, [], [], [], [], [], [], [], [], self.curved_line, [], [])
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self.write_into_page_xml([], page_coord, self.dir_out, [], [], [], [], [], [], [], [], self.curved_line, [], [])
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@ -2410,14 +2431,14 @@ class eynollah:
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t1 = time.time()
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t1 = time.time()
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if not self.full_layout:
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if not self.full_layout:
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polygons_of_images, img_revised_tab, text_regions_p_1_n, textline_mask_tot_d, regions_without_seperators_d = self.run_boxes_no_full_layout(image_page, textline_mask_tot, text_regions_p, slope_deskew, num_col_classifier)
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polygons_of_images, img_revised_tab, text_regions_p_1_n, textline_mask_tot_d, regions_without_seperators_d, boxes, boxes_d = self.run_boxes_no_full_layout(image_page, textline_mask_tot, text_regions_p, slope_deskew, num_col_classifier)
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pixel_img = 4
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pixel_img = 4
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min_area_mar = 0.00001
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min_area_mar = 0.00001
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polygons_of_marginals = return_contours_of_interested_region(text_regions_p, pixel_img, min_area_mar)
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polygons_of_marginals = return_contours_of_interested_region(text_regions_p, pixel_img, min_area_mar)
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if self.full_layout:
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if self.full_layout:
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polygons_of_images, img_revised_tab, text_regions_p_1_n, textline_mask_tot_d, regions_without_seperators_d, regions_fully = self.run_boxes_full_layout(image_page, textline_mask_tot, text_regions_p, slope_deskew, num_col_classifier, img_only_regions)
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polygons_of_images, img_revised_tab, text_regions_p_1_n, textline_mask_tot_d, regions_without_seperators_d, regions_fully, regions_without_seperators = self.run_boxes_full_layout(image_page, textline_mask_tot, text_regions_p, slope_deskew, num_col_classifier, img_only_regions)
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# plt.imshow(img_revised_tab)
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# plt.imshow(img_revised_tab)
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# plt.show()
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# plt.show()
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