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https://github.com/qurator-spk/eynollah.git
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dilate_textregions_contours: simplify (via shapely's Polygon.buffer()), ensure validity
This commit is contained in:
Robert Sachunsky
parent
a2359ea4c4
commit
f994ea5f0b
3 changed files with 33 additions and 104 deletions
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@ -27,6 +27,7 @@ from loky import ProcessPoolExecutor
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import xml.etree.ElementTree as ET
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import cv2
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import numpy as np
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from shapely.geometry import Polygon
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from scipy.signal import find_peaks
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from scipy.ndimage import gaussian_filter1d
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from numba import cuda
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@ -68,6 +69,7 @@ from .utils.contour import (
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get_text_region_boxes_by_given_contours,
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get_textregion_contours_in_org_image,
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get_textregion_contours_in_org_image_light,
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make_valid,
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return_contours_of_image,
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return_contours_of_interested_region,
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return_contours_of_interested_region_by_min_size,
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@ -3774,107 +3776,9 @@ class Eynollah:
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return all_found_textline_polygons
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def dilate_textregions_contours(self, all_found_textline_polygons):
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#print(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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#print(len(con_ind[:,0,0]),'con_ind[:,0,0]')
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area = cv2.contourArea(con_ind)
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con_ind = con_ind.astype(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, 0.1)
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y_differential = gaussian_filter1d(y_differential, 0.1)
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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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if (y_max-y_min) <= (x_max-x_min):
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dilation_m1 = round(area / (x_max-x_min) * 0.12)
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else:
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dilation_m1 = round(area / (y_max-y_min) * 0.12)
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if dilation_m1>8:
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dilation_m1 = 8
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if dilation_m1<6:
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dilation_m1 = 6
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#print(dilation_m1, 'dilation_m1')
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dilation_m1 = 6
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dilation_m2 = int(dilation_m1/2.) +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] = dilation_m2*(-1*y_differential_mask_nonzeros[i])
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inc_y[i+1] = dilation_m2*(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]= dilation_m1*(-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] = dilation_m1*(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] = dilation_m1*(x_differential_mask_nonzeros[i])
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else:
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inc_x[i+1]= dilation_m1*(-1*y_differential_mask_nonzeros[i])
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else:
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inc_x[i+1] = dilation_m2*(-1*y_differential_mask_nonzeros[i])
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inc_y[i+1] = dilation_m2*(x_differential_mask_nonzeros[i])
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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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area_scaled = cv2.contourArea(con_scaled.astype(np.int32))
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con_ind = con_ind.astype(np.int32)
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results = [cv2.pointPolygonTest(con_ind, (con_scaled[ind,0, 0], con_scaled[ind,0, 1]), False)
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for ind in range(len(con_scaled[:,0, 1])) ]
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results = np.array(results)
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#print(results,'results')
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results[results==0] = 1
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diff_result = np.diff(results)
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indices_2 = [ind for ind in range(len(diff_result)) if diff_result[ind]==2]
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indices_m2 = [ind for ind in range(len(diff_result)) if diff_result[ind]==-2]
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if results[0]==1:
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con_scaled[:indices_m2[0]+1,0, 1] = con_ind[:indices_m2[0]+1,0,1]
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con_scaled[:indices_m2[0]+1,0, 0] = con_ind[:indices_m2[0]+1,0,0]
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#indices_2 = indices_2[1:]
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indices_m2 = indices_m2[1:]
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if len(indices_2)>len(indices_m2):
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con_scaled[indices_2[-1]+1:,0, 1] = con_ind[indices_2[-1]+1:,0,1]
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con_scaled[indices_2[-1]+1:,0, 0] = con_ind[indices_2[-1]+1:,0,0]
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indices_2 = indices_2[:-1]
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for ii in range(len(indices_2)):
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con_scaled[indices_2[ii]+1:indices_m2[ii]+1,0, 1] = con_scaled[indices_2[ii],0, 1]
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con_scaled[indices_2[ii]+1:indices_m2[ii]+1,0, 0] = con_scaled[indices_2[ii],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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return [np.array(make_valid(Polygon(poly[:, 0])).buffer(5).exterior.coords,
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dtype=int)[:, np.newaxis]
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for poly in all_found_textline_polygons]
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def dilate_textline_contours(self, all_found_textline_polygons):
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for j in range(len(all_found_textline_polygons)):
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@ -2156,6 +2156,7 @@ def return_boxes_of_images_by_order_of_reading_new(
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x_end_itself=x_end_copy.pop(il)
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#print(y_copy,'y_copy2')
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# FIXME: cannot convert numpy.float64 to integer...
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for column in range(x_start_itself, x_end_itself+1):
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#print(column,'cols')
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y_in_cols=[]
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@ -1,7 +1,7 @@
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from functools import partial
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import cv2
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import numpy as np
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from shapely import geometry
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from shapely.geometry import Polygon
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from .rotate import rotate_image, rotation_image_new
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@ -43,7 +43,7 @@ def filter_contours_area_of_image(image, contours, hierarchy, max_area, min_area
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if len(c) < 3: # A polygon cannot have less than 3 points
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continue
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polygon = geometry.Polygon([point[0] for point in c])
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polygon = Polygon([point[0] for point in c])
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area = polygon.area
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if (area >= min_area * np.prod(image.shape[:2]) and
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area <= max_area * np.prod(image.shape[:2]) and
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@ -58,7 +58,7 @@ def filter_contours_area_of_image_tables(image, contours, hierarchy, max_area, m
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if len(c) < 3: # A polygon cannot have less than 3 points
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continue
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polygon = geometry.Polygon([point[0] for point in c])
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polygon = Polygon([point[0] for point in c])
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# area = cv2.contourArea(c)
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area = polygon.area
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##print(np.prod(thresh.shape[:2]))
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@ -332,3 +332,27 @@ def return_contours_of_interested_region_by_size(region_pre_p, pixel, min_area,
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return img_ret[:, :, 0]
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def make_valid(polygon: Polygon) -> Polygon:
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"""Ensures shapely.geometry.Polygon object is valid by repeated rearrangement/simplification/enlargement."""
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points = list(polygon.exterior.coords)
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# try by re-arranging points
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for split in range(1, len(points)):
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if polygon.is_valid or polygon.simplify(polygon.area).is_valid:
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break
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# simplification may not be possible (at all) due to ordering
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# in that case, try another starting point
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polygon = Polygon(points[-split:]+points[:-split])
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# try by simplification
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for tolerance in range(int(polygon.area + 1.5)):
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if polygon.is_valid:
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break
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# simplification may require a larger tolerance
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polygon = polygon.simplify(tolerance + 1)
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# try by enlarging
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for tolerance in range(1, int(polygon.area + 2.5)):
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if polygon.is_valid:
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break
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# enlargement may require a larger tolerance
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polygon = polygon.buffer(tolerance)
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assert polygon.is_valid, polygon.wkt
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return polygon
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