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@ -37,9 +37,7 @@ from tensorflow.keras.models import load_model
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sys.stderr = stderr
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tf.get_logger().setLevel("ERROR")
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warnings.filterwarnings("ignore")
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from scipy.signal import find_peaks
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import matplotlib.pyplot as plt
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from scipy.ndimage import gaussian_filter1d
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from tensorflow.python.keras.backend import set_session
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from tensorflow.keras import layers
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@ -2056,8 +2054,8 @@ class Eynollah:
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mask_texts_only = mask_texts_only.astype('uint8')
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#mask_texts_only = cv2.erode(mask_texts_only, KERNEL, iterations=1)
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#mask_texts_only = cv2.dilate(mask_texts_only, KERNEL, iterations=1)
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mask_texts_only = cv2.erode(mask_texts_only, KERNEL, iterations=1)
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mask_texts_only = cv2.dilate(mask_texts_only, KERNEL, iterations=1)
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mask_images_only=(prediction_regions_org[:,:] ==2)*1
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@ -2097,6 +2095,8 @@ class Eynollah:
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polygons_of_only_texts = return_contours_of_interested_region(mask_texts_only,1,0.00001)
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##polygons_of_only_texts = self.dilate_textregions_contours(polygons_of_only_texts)
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polygons_of_only_lines = return_contours_of_interested_region(mask_lines_only,1,0.00001)
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@ -3845,6 +3845,79 @@ class Eynollah:
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return x_differential_new
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def dilate_textregions_contours(self,all_found_textline_polygons):
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for j in range(len(all_found_textline_polygons)):
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con_ind = all_found_textline_polygons[j]
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con_ind = con_ind.astype(np.float)
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x_differential = np.diff( con_ind[:,0,0])
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y_differential = np.diff( con_ind[:,0,1])
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x_differential = gaussian_filter1d(x_differential, 3)
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y_differential = gaussian_filter1d(y_differential, 3)
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x_min = float(np.min( con_ind[:,0,0] ))
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y_min = float(np.min( con_ind[:,0,1] ))
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x_max = float(np.max( con_ind[:,0,0] ))
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y_max = float(np.max( con_ind[:,0,1] ))
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x_differential_mask_nonzeros = [ ind/abs(ind) if ind!=0 else ind for ind in x_differential]
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y_differential_mask_nonzeros = [ ind/abs(ind) if ind!=0 else ind for ind in y_differential]
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abs_diff=abs(abs(x_differential)- abs(y_differential) )
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inc_x = np.zeros(len(x_differential)+1)
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inc_y = np.zeros(len(x_differential)+1)
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for i in range(len(x_differential)):
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if abs_diff[i]==0:
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inc_x[i+1] = 7*(-1*y_differential_mask_nonzeros[i])
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inc_y[i+1] = 7*(x_differential_mask_nonzeros[i])
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elif abs_diff[i]!=0 and x_differential_mask_nonzeros[i]==0 and y_differential_mask_nonzeros[i]!=0:
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inc_x[i+1]= 12*(-1*y_differential_mask_nonzeros[i])
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elif abs_diff[i]!=0 and x_differential_mask_nonzeros[i]!=0 and y_differential_mask_nonzeros[i]==0:
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inc_y[i+1] = 12*(x_differential_mask_nonzeros[i])
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elif abs_diff[i]!=0 and abs_diff[i]>=3:
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if abs(x_differential[i])>abs(y_differential[i]):
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inc_y[i+1] = 12*(x_differential_mask_nonzeros[i])
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else:
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inc_x[i+1]= 12*(-1*y_differential_mask_nonzeros[i])
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else:
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inc_x[i+1] = 7*(-1*y_differential_mask_nonzeros[i])
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inc_y[i+1] = 7*(x_differential_mask_nonzeros[i])
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###inc_x =list(inc_x)
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###inc_x.append(inc_x[0])
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###inc_y =list(inc_y)
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###inc_y.append(inc_y[0])
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inc_x[0] = inc_x[-1]
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inc_y[0] = inc_y[-1]
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con_scaled = con_ind*1
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con_scaled[:,0, 0] = con_ind[:,0,0] + np.array(inc_x)[:]
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con_scaled[:,0, 1] = con_ind[:,0,1] + np.array(inc_y)[:]
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con_scaled[:,0, 1][con_scaled[:,0, 1]<0] = 0
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con_scaled[:,0, 0][con_scaled[:,0, 0]<0] = 0
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all_found_textline_polygons[j][:,0,1] = con_scaled[:,0, 1]
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all_found_textline_polygons[j][:,0,0] = con_scaled[:,0, 0]
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return all_found_textline_polygons
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def dilate_textlines(self,all_found_textline_polygons):
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for j in range(len(all_found_textline_polygons)):
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for i in range(len(all_found_textline_polygons[j])):
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@ -4096,7 +4169,7 @@ class Eynollah:
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t1 = time.time()
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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_separators_d, boxes, boxes_d, polygons_of_marginals, contours_tables = self.run_boxes_no_full_layout(image_page, textline_mask_tot, text_regions_p, slope_deskew, num_col_classifier, table_prediction, erosion_hurts)
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polygons_of_marginals = self.dilate_textregions_contours(polygons_of_marginals)
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if self.full_layout:
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if not self.light_version:
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img_bin_light = None
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@ -4230,6 +4303,7 @@ class Eynollah:
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#print("text region early 3 in %.1fs", time.time() - t0)
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if self.light_version:
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txt_con_org = get_textregion_contours_in_org_image_light(contours_only_text_parent, self.image, slope_first)
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txt_con_org = self.dilate_textregions_contours(txt_con_org)
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else:
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txt_con_org = get_textregion_contours_in_org_image(contours_only_text_parent, self.image, slope_first)
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#print("text region early 4 in %.1fs", time.time() - t0)
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vahidrezanezhad
3 months ago