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eynollah
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clean up empty lines, fix syntax error

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pull/19/head
Konstantin Baierer 4 years ago
parent 7905b3b9d2
commit b93c1923d0
1 changed files with 11 additions and 99 deletions
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sbb_newspapers_org_image/eynollah.py
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@ -744,9 +744,7 @@ class eynollah:
if patches and cols == 2: if patches and cols == 2:
img = otsu_copy_binary(img) # otsu_copy(img) img = otsu_copy_binary(img) # otsu_copy(img)
img = img.astype(np.uint8) img = img.astype(np.uint8)
if img_width_h >= 2000: if img_width_h >= 2000:
img = resize_image(img, int(img_height_h * 0.9), int(img_width_h * 0.9)) img = resize_image(img, int(img_height_h * 0.9), int(img_width_h * 0.9))
else: else:
@ -755,7 +753,6 @@ class eynollah:
if patches and cols == 1: if patches and cols == 1:
img = otsu_copy_binary(img) # otsu_copy(img) img = otsu_copy_binary(img) # otsu_copy(img)
img = img.astype(np.uint8) img = img.astype(np.uint8)
img = resize_image(img, int(img_height_h * 0.5), int(img_width_h * 0.5)) img = resize_image(img, int(img_height_h * 0.5), int(img_width_h * 0.5))
img = img.astype(np.uint8) img = img.astype(np.uint8)
@ -766,13 +763,11 @@ class eynollah:
img = img.astype(np.uint8) img = img.astype(np.uint8)
#img= self.resize_image(img, int(img_height_h*0.8), int(img_width_h*0.8) ) #img= self.resize_image(img, int(img_height_h*0.8), int(img_width_h*0.8) )
img= resize_image(img, int(img_height_h*2800/float(img_width_h)), 2800 ) img= resize_image(img, int(img_height_h*2800/float(img_width_h)), 2800 )
else: else:
img = otsu_copy_binary(img)#self.otsu_copy(img) img = otsu_copy_binary(img)#self.otsu_copy(img)
img = img.astype(np.uint8) img = img.astype(np.uint8)
#img= self.resize_image(img, int(img_height_h*0.9), int(img_width_h*0.9) ) #img= self.resize_image(img, int(img_height_h*0.9), int(img_width_h*0.9) )
if patches and cols==4: if patches and cols==4:
#print(self.scale_x,img_width_h,'scale') #print(self.scale_x,img_width_h,'scale')
if (self.scale_x==1 and img_width_h>4000) or (self.scale_x!=1 and img_width_h>3700): if (self.scale_x==1 and img_width_h>4000) or (self.scale_x!=1 and img_width_h>3700):
@ -943,28 +938,21 @@ class eynollah:
all_text_region_raw = textline_mask_tot_ea[boxes_text[mv][1] : boxes_text[mv][1] + boxes_text[mv][3], boxes_text[mv][0] : boxes_text[mv][0] + boxes_text[mv][2]] all_text_region_raw = textline_mask_tot_ea[boxes_text[mv][1] : boxes_text[mv][1] + boxes_text[mv][3], boxes_text[mv][0] : boxes_text[mv][0] + boxes_text[mv][2]]
all_text_region_raw = all_text_region_raw.astype(np.uint8) all_text_region_raw = all_text_region_raw.astype(np.uint8)
img_int_p = all_text_region_raw[:, :] # self.all_text_region_raw[mv] img_int_p = all_text_region_raw[:, :] # self.all_text_region_raw[mv]
##img_int_p=cv2.erode(img_int_p,self.kernel,iterations = 2) ##img_int_p=cv2.erode(img_int_p,self.kernel,iterations = 2)
# plt.imshow(img_int_p) # plt.imshow(img_int_p)
# plt.show() # plt.show()
if img_int_p.shape[0] / img_int_p.shape[1] < 0.1: if img_int_p.shape[0] / img_int_p.shape[1] < 0.1:
slopes_per_each_subprocess.append(0) slopes_per_each_subprocess.append(0)
slope_first = 0 slope_first = 0
slope_for_all = [slope_deskew][0] slope_for_all = [slope_deskew][0]
else: else:
try: try:
textline_con, hierachy = return_contours_of_image(img_int_p) textline_con, hierachy = return_contours_of_image(img_int_p)
textline_con_fil = filter_contours_area_of_image(img_int_p, textline_con, hierachy, max_area=1, min_area=0.0008) textline_con_fil = filter_contours_area_of_image(img_int_p, textline_con, hierachy, max_area=1, min_area=0.0008)
y_diff_mean = find_contours_mean_y_diff(textline_con_fil) y_diff_mean = find_contours_mean_y_diff(textline_con_fil)
sigma_des = int(y_diff_mean * (4.0 / 40.0)) sigma_des = int(y_diff_mean * (4.0 / 40.0))
if sigma_des < 1: if sigma_des < 1:
@ -979,37 +967,26 @@ class eynollah:
# old method # old method
# slope_for_all=self.textline_contours_to_get_slope_correctly(self.all_text_region_raw[mv],denoised,contours[mv]) # slope_for_all=self.textline_contours_to_get_slope_correctly(self.all_text_region_raw[mv],denoised,contours[mv])
# text_patch_processed=textline_contours_postprocessing(gada) # text_patch_processed=textline_contours_postprocessing(gada)
except: except:
slope_for_all = 999 slope_for_all = 999
##slope_for_all=return_deskew_slop(img_int_p,sigma_des, dir_of_all=self.dir_of_all, image_filename_stem=self.image_filename_stem)
if slope_for_all == 999: if slope_for_all == 999:
slope_for_all = [slope_deskew][0] slope_for_all = [slope_deskew][0]
##if np.abs(slope_for_all)>32.5 and slope_for_all!=999:
##slope_for_all=slope_biggest
##elif slope_for_all==999:
##slope_for_all=slope_biggest
slopes_per_each_subprocess.append(slope_for_all) slopes_per_each_subprocess.append(slope_for_all)
index_by_text_region_contours.append(indexes_r_con_per_pro[mv]) index_by_text_region_contours.append(indexes_r_con_per_pro[mv])
crop_img, crop_coor = crop_image_inside_box(boxes_text[mv], image_page_rotated) crop_img, crop_coor = crop_image_inside_box(boxes_text[mv], image_page_rotated)
if abs(slope_for_all) < 45: if abs(slope_for_all) < 45:
# all_box_coord.append(crop_coor) # all_box_coord.append(crop_coor)
textline_region_in_image = np.zeros(textline_mask_tot_ea.shape) textline_region_in_image = np.zeros(textline_mask_tot_ea.shape)
cnt_o_t_max = contours_par_per_process[mv] cnt_o_t_max = contours_par_per_process[mv]
x, y, w, h = cv2.boundingRect(cnt_o_t_max) x, y, w, h = cv2.boundingRect(cnt_o_t_max)
mask_biggest = np.zeros(mask_texts_only.shape) mask_biggest = np.zeros(mask_texts_only.shape)
mask_biggest = cv2.fillPoly(mask_biggest, pts=[cnt_o_t_max], color=(1, 1, 1)) mask_biggest = cv2.fillPoly(mask_biggest, pts=[cnt_o_t_max], color=(1, 1, 1))
mask_region_in_patch_region = mask_biggest[y : y + h, x : x + w] mask_region_in_patch_region = mask_biggest[y : y + h, x : x + w]
textline_biggest_region = mask_biggest * textline_mask_tot_ea textline_biggest_region = mask_biggest * textline_mask_tot_ea
# print(slope_for_all,'slope_for_all') # print(slope_for_all,'slope_for_all')
@ -1025,7 +1002,6 @@ class eynollah:
# plt.imshow(textline_region_in_image) # plt.imshow(textline_region_in_image)
# plt.show() # plt.show()
# plt.imshow(textline_cnt_seperated) # plt.imshow(textline_cnt_seperated)
# plt.show() # plt.show()
@ -1039,21 +1015,16 @@ class eynollah:
if num_col + 1 == 1: if num_col + 1 == 1:
mask_biggest2 = cv2.dilate(mask_biggest2, self.kernel, iterations=5) mask_biggest2 = cv2.dilate(mask_biggest2, self.kernel, iterations=5)
else: else:
mask_biggest2 = cv2.dilate(mask_biggest2, self.kernel, iterations=4) mask_biggest2 = cv2.dilate(mask_biggest2, self.kernel, iterations=4)
pixel_img = 1 pixel_img = 1
mask_biggest2 = resize_image(mask_biggest2, int(mask_biggest2.shape[0] * scale_par), int(mask_biggest2.shape[1] * scale_par)) mask_biggest2 = resize_image(mask_biggest2, int(mask_biggest2.shape[0] * scale_par), int(mask_biggest2.shape[1] * scale_par))
cnt_textlines_in_image_ind = return_contours_of_interested_textline(mask_biggest2, pixel_img) cnt_textlines_in_image_ind = return_contours_of_interested_textline(mask_biggest2, pixel_img)
try: try:
# textlines_cnt_per_region.append(cnt_textlines_in_image_ind[0]/scale_par) # textlines_cnt_per_region.append(cnt_textlines_in_image_ind[0]/scale_par)
textlines_cnt_per_region.append(cnt_textlines_in_image_ind[0]) textlines_cnt_per_region.append(cnt_textlines_in_image_ind[0])
except: except:
pass pass
else: else:
slope_first = 0 slope_first = 0
add_boxes_coor_into_textlines = True add_boxes_coor_into_textlines = True
@ -1061,13 +1032,8 @@ class eynollah:
add_boxes_coor_into_textlines = False add_boxes_coor_into_textlines = False
# print(np.shape(textlines_cnt_per_region),'textlines_cnt_per_region') # print(np.shape(textlines_cnt_per_region),'textlines_cnt_per_region')
# textlines_cnt_tot_per_process.append(textlines_cnt_per_region)
# index_polygons_per_process_per_process.append(index_polygons_per_process[iiii])
textlines_rectangles_per_each_subprocess.append(textlines_cnt_per_region) textlines_rectangles_per_each_subprocess.append(textlines_cnt_per_region)
# all_found_texline_polygons.append(cnt_clean_rot)
bounding_box_of_textregion_per_each_subprocess.append(boxes_text[mv]) bounding_box_of_textregion_per_each_subprocess.append(boxes_text[mv])
contours_textregion_per_each_subprocess.append(contours_per_process[mv]) contours_textregion_per_each_subprocess.append(contours_per_process[mv])
contours_textregion_par_per_each_subprocess.append(contours_par_per_process[mv]) contours_textregion_par_per_each_subprocess.append(contours_par_per_process[mv])
all_box_coord_per_process.append(crop_coor) all_box_coord_per_process.append(crop_coor)
@ -1086,74 +1052,42 @@ class eynollah:
slope_biggest = 0 slope_biggest = 0
for mv in range(len(boxes_text)): for mv in range(len(boxes_text)):
crop_img,crop_coor=crop_image_inside_box(boxes_text[mv],image_page_rotated) crop_img,crop_coor=crop_image_inside_box(boxes_text[mv],image_page_rotated)
#all_box_coord.append(crop_coor)
mask_textline=np.zeros((textline_mask_tot_ea.shape)) mask_textline=np.zeros((textline_mask_tot_ea.shape))
mask_textline=cv2.fillPoly(mask_textline,pts=[contours_per_process[mv]],color=(1,1,1)) mask_textline=cv2.fillPoly(mask_textline,pts=[contours_per_process[mv]],color=(1,1,1))
denoised=None denoised=None
all_text_region_raw=(textline_mask_tot_ea*mask_textline[:,:])[boxes_text[mv][1]:boxes_text[mv][1]+boxes_text[mv][3] , boxes_text[mv][0]:boxes_text[mv][0]+boxes_text[mv][2] ] all_text_region_raw=(textline_mask_tot_ea*mask_textline[:,:])[boxes_text[mv][1]:boxes_text[mv][1]+boxes_text[mv][3] , boxes_text[mv][0]:boxes_text[mv][0]+boxes_text[mv][2] ]
all_text_region_raw=all_text_region_raw.astype(np.uint8) all_text_region_raw=all_text_region_raw.astype(np.uint8)
img_int_p=all_text_region_raw[:,:]#self.all_text_region_raw[mv] img_int_p=all_text_region_raw[:,:]#self.all_text_region_raw[mv]
img_int_p=cv2.erode(img_int_p,self.kernel,iterations = 2) img_int_p=cv2.erode(img_int_p,self.kernel,iterations = 2)
if img_int_p.shape[0]/img_int_p.shape[1]<0.1: if img_int_p.shape[0]/img_int_p.shape[1]<0.1:
slopes_per_each_subprocess.append(0) slopes_per_each_subprocess.append(0)
slope_for_all = [slope_deskew][0] slope_for_all = [slope_deskew][0]
all_text_region_raw = textline_mask_tot_ea[boxes_text[mv][1] : boxes_text[mv][1] + boxes_text[mv][3], boxes_text[mv][0] : boxes_text[mv][0] + boxes_text[mv][2]] all_text_region_raw = textline_mask_tot_ea[boxes_text[mv][1] : boxes_text[mv][1] + boxes_text[mv][3], boxes_text[mv][0] : boxes_text[mv][0] + boxes_text[mv][2]]
cnt_clean_rot = textline_contours_postprocessing(all_text_region_raw, slope_for_all, contours_par_per_process[mv], boxes_text[mv], 0) cnt_clean_rot = textline_contours_postprocessing(all_text_region_raw, slope_for_all, contours_par_per_process[mv], boxes_text[mv], 0)
textlines_rectangles_per_each_subprocess.append(cnt_clean_rot) textlines_rectangles_per_each_subprocess.append(cnt_clean_rot)
index_by_text_region_contours.append(indexes_r_con_per_pro[mv]) index_by_text_region_contours.append(indexes_r_con_per_pro[mv])
# all_found_texline_polygons.append(cnt_clean_rot)
bounding_box_of_textregion_per_each_subprocess.append(boxes_text[mv]) bounding_box_of_textregion_per_each_subprocess.append(boxes_text[mv])
else: else:
try: try:
textline_con, hierachy = return_contours_of_image(img_int_p) textline_con, hierachy = return_contours_of_image(img_int_p)
textline_con_fil = filter_contours_area_of_image(img_int_p, textline_con, hierachy, max_area=1, min_area=0.00008) textline_con_fil = filter_contours_area_of_image(img_int_p, textline_con, hierachy, max_area=1, min_area=0.00008)
y_diff_mean = find_contours_mean_y_diff(textline_con_fil) y_diff_mean = find_contours_mean_y_diff(textline_con_fil)
sigma_des = int(y_diff_mean * (4.0 / 40.0)) sigma_des = int(y_diff_mean * (4.0 / 40.0))
if sigma_des < 1: if sigma_des < 1:
sigma_des = 1 sigma_des = 1
img_int_p[img_int_p > 0] = 1 img_int_p[img_int_p > 0] = 1
# slope_for_all=self.return_deskew_slope_new(img_int_p,sigma_des)
slope_for_all = return_deskew_slop(img_int_p, sigma_des, dir_of_all=self.dir_of_all, image_filename_stem=self.image_filename_stem) slope_for_all = return_deskew_slop(img_int_p, sigma_des, dir_of_all=self.dir_of_all, image_filename_stem=self.image_filename_stem)
if abs(slope_for_all) <= 0.5: if abs(slope_for_all) <= 0.5:
slope_for_all = [slope_deskew][0] slope_for_all = [slope_deskew][0]
except: except:
slope_for_all = 999 slope_for_all = 999
##slope_for_all=return_deskew_slop(img_int_p,sigma_des, dir_of_all=self.dir_of_all, image_filename_stem=self.image_filename_stem)
if slope_for_all == 999: if slope_for_all == 999:
slope_for_all = [slope_deskew][0] slope_for_all = [slope_deskew][0]
##if np.abs(slope_for_all)>32.5 and slope_for_all!=999:
##slope_for_all=slope_biggest
##elif slope_for_all==999:
##slope_for_all=slope_biggest
slopes_per_each_subprocess.append(slope_for_all) slopes_per_each_subprocess.append(slope_for_all)
slope_first = 0 slope_first = 0
mask_only_con_region = np.zeros(textline_mask_tot_ea.shape) mask_only_con_region = np.zeros(textline_mask_tot_ea.shape)
mask_only_con_region = cv2.fillPoly(mask_only_con_region, pts=[contours_par_per_process[mv]], color=(1, 1, 1)) mask_only_con_region = cv2.fillPoly(mask_only_con_region, pts=[contours_par_per_process[mv]], color=(1, 1, 1))
@ -1166,7 +1100,6 @@ class eynollah:
##plt.show() ##plt.show()
##plt.imshow(all_text_region_raw) ##plt.imshow(all_text_region_raw)
##plt.show() ##plt.show()
##plt.imshow(mask_only_con_region) ##plt.imshow(mask_only_con_region)
##plt.show() ##plt.show()
@ -1175,7 +1108,6 @@ class eynollah:
textlines_rectangles_per_each_subprocess.append(cnt_clean_rot) textlines_rectangles_per_each_subprocess.append(cnt_clean_rot)
index_by_text_region_contours.append(indexes_r_con_per_pro[mv]) index_by_text_region_contours.append(indexes_r_con_per_pro[mv])
# all_found_texline_polygons.append(cnt_clean_rot)
bounding_box_of_textregion_per_each_subprocess.append(boxes_text[mv]) bounding_box_of_textregion_per_each_subprocess.append(boxes_text[mv])
contours_textregion_per_each_subprocess.append(contours_per_process[mv]) contours_textregion_per_each_subprocess.append(contours_per_process[mv])
@ -1190,38 +1122,22 @@ class eynollah:
model_textline, session_textline = self.start_new_session_and_model(self.model_textline_dir) model_textline, session_textline = self.start_new_session_and_model(self.model_textline_dir)
if not patches: if not patches:
model_textline, session_textline = self.start_new_session_and_model(self.model_textline_dir_np) model_textline, session_textline = self.start_new_session_and_model(self.model_textline_dir_np)
##img = otsu_copy(img)
img = img.astype(np.uint8) img = img.astype(np.uint8)
img_org = np.copy(img) img_org = np.copy(img)
img_h = img_org.shape[0] img_h = img_org.shape[0]
img_w = img_org.shape[1] img_w = img_org.shape[1]
img = resize_image(img_org, int(img_org.shape[0] * scaler_h), int(img_org.shape[1] * scaler_w)) img = resize_image(img_org, int(img_org.shape[0] * scaler_h), int(img_org.shape[1] * scaler_w))
prediction_textline = self.do_prediction(patches, img, model_textline) prediction_textline = self.do_prediction(patches, img, model_textline)
prediction_textline = resize_image(prediction_textline, img_h, img_w) prediction_textline = resize_image(prediction_textline, img_h, img_w)
patches = False patches = False
prediction_textline_longshot = self.do_prediction(patches, img, model_textline) prediction_textline_longshot = self.do_prediction(patches, img, model_textline)
prediction_textline_longshot_true_size = resize_image(prediction_textline_longshot, img_h, img_w) prediction_textline_longshot_true_size = resize_image(prediction_textline_longshot, img_h, img_w)
# scaler_w=1.5
# scaler_h=1.5
# patches=True
# img= resize_image(img_org, int(img_org.shape[0]*scaler_h), int(img_org.shape[1]*scaler_w))
# prediction_textline_streched=self.do_prediction(patches,img,model_textline) # prediction_textline_streched=self.do_prediction(patches,img,model_textline)
# prediction_textline_streched= resize_image(prediction_textline_streched, img_h, img_w) # prediction_textline_streched= resize_image(prediction_textline_streched, img_h, img_w)
##plt.imshow(prediction_textline_streched[:,:,0]) ##plt.imshow(prediction_textline_streched[:,:,0])
##plt.show() ##plt.show()
# sys.exit()
session_textline.close() session_textline.close()
del model_textline del model_textline
@ -1261,10 +1177,6 @@ class eynollah:
if slope_corresponding_textregion == 999: if slope_corresponding_textregion == 999:
slope_corresponding_textregion = slope_biggest slope_corresponding_textregion = slope_biggest
##if np.abs(slope_corresponding_textregion)>12.5 and slope_corresponding_textregion!=999:
##slope_corresponding_textregion=slope_biggest
##elif slope_corresponding_textregion==999:
##slope_corresponding_textregion=slope_biggest
slopes_sub.append(slope_corresponding_textregion) slopes_sub.append(slope_corresponding_textregion)
cnt_clean_rot = textline_contours_postprocessing(crop_img, slope_corresponding_textregion, contours_per_process[mv], boxes_per_process[mv]) cnt_clean_rot = textline_contours_postprocessing(crop_img, slope_corresponding_textregion, contours_per_process[mv], boxes_per_process[mv])
@ -1478,11 +1390,11 @@ class eynollah:
#else: #else:
# textregion.set('type','paragraph') # textregion.set('type','paragraph')
coord_text = ET.SubElement(textregion, 'Coords') coord_text = ET.SubElement(textregion, 'Coords')
coord_text.set('points', self.calculate_polygon_coords(found_polygons_drop_capitals, mm, lmm, page_coord) coord_text.set('points', self.calculate_polygon_coords(found_polygons_drop_capitals, mm, lmm, page_coord))
texteqreg = ET.SubElement(textregion, 'TextEquiv')
texteqreg = ET.SubElement(textregion, 'TextEquiv')
unireg=ET.SubElement(texteqreg, 'Unicode') unireg=ET.SubElement(texteqreg, 'Unicode')
unireg.text = ' ' unireg.text = ' '
@ -1507,7 +1419,7 @@ class eynollah:
#else: #else:
# textregion.set('type','paragraph') # textregion.set('type','paragraph')
coord_text = ET.SubElement(textregion, 'Coords') coord_text = ET.SubElement(textregion, 'Coords')
coord_text.set('points', self.calculate_polygon_coords(found_polygons_marginals, mm, lmm, page_coord) coord_text.set('points', self.calculate_polygon_coords(found_polygons_marginals, mm, lmm, page_coord))
for j in range(len(all_found_texline_polygons_marginals[mm])): for j in range(len(all_found_texline_polygons_marginals[mm])):
@ -1583,7 +1495,7 @@ class eynollah:
textregion.set('id','r'+str(id_indexer)) textregion.set('id','r'+str(id_indexer))
id_indexer+=1 id_indexer+=1
coord_text = ET.SubElement(textregion, 'Coords') coord_text = ET.SubElement(textregion, 'Coords')
coord_text.set('points', self.calculate_polygon_coords(found_polygons_text_region_img, mm, lmm, page_coord) coord_text.set('points', self.calculate_polygon_coords(found_polygons_text_region_img, mm, lmm, page_coord))
except: except:
pass pass
@ -1595,7 +1507,7 @@ class eynollah:
textregion.set('id','r'+str(id_indexer)) textregion.set('id','r'+str(id_indexer))
id_indexer+=1 id_indexer+=1
coord_text = ET.SubElement(textregion, 'Coords') coord_text = ET.SubElement(textregion, 'Coords')
coord_text.set('points', self.calculate_polygon_coords(found_polygons_tables, mm, lmm, page_coord) coord_text.set('points', self.calculate_polygon_coords(found_polygons_tables, mm, lmm, page_coord))
except: except:
pass pass
@ -1770,7 +1682,7 @@ class eynollah:
textregion.set('id', id_of_marginalia[mm]) textregion.set('id', id_of_marginalia[mm])
textregion.set('type', 'marginalia') textregion.set('type', 'marginalia')
coord_text = ET.SubElement(textregion, 'Coords') coord_text = ET.SubElement(textregion, 'Coords')
coord_text.set('points', self.calculate_polygon_coords(found_polygons_marginals, mm, lmm, page_coord) coord_text.set('points', self.calculate_polygon_coords(found_polygons_marginals, mm, lmm, page_coord))
for j in range(len(all_found_texline_polygons_marginals[mm])): for j in range(len(all_found_texline_polygons_marginals[mm])):
textline=ET.SubElement(textregion, 'TextLine') textline=ET.SubElement(textregion, 'TextLine')
textline.set('id','l'+str(id_indexer_l)) textline.set('id','l'+str(id_indexer_l))

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