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@ -744,9 +744,7 @@ class eynollah:
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if patches and cols == 2:
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if patches and cols == 2:
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img = otsu_copy_binary(img) # otsu_copy(img)
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img = otsu_copy_binary(img) # otsu_copy(img)
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img = img.astype(np.uint8)
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img = img.astype(np.uint8)
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if img_width_h >= 2000:
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if img_width_h >= 2000:
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img = resize_image(img, int(img_height_h * 0.9), int(img_width_h * 0.9))
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img = resize_image(img, int(img_height_h * 0.9), int(img_width_h * 0.9))
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else:
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else:
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@ -755,7 +753,6 @@ class eynollah:
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if patches and cols == 1:
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if patches and cols == 1:
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img = otsu_copy_binary(img) # otsu_copy(img)
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img = otsu_copy_binary(img) # otsu_copy(img)
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img = img.astype(np.uint8)
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img = img.astype(np.uint8)
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img = resize_image(img, int(img_height_h * 0.5), int(img_width_h * 0.5))
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img = resize_image(img, int(img_height_h * 0.5), int(img_width_h * 0.5))
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img = img.astype(np.uint8)
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img = img.astype(np.uint8)
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@ -766,13 +763,11 @@ class eynollah:
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img = img.astype(np.uint8)
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img = img.astype(np.uint8)
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#img= self.resize_image(img, int(img_height_h*0.8), int(img_width_h*0.8) )
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#img= self.resize_image(img, int(img_height_h*0.8), int(img_width_h*0.8) )
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img= resize_image(img, int(img_height_h*2800/float(img_width_h)), 2800 )
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img= resize_image(img, int(img_height_h*2800/float(img_width_h)), 2800 )
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else:
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else:
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img = otsu_copy_binary(img)#self.otsu_copy(img)
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img = otsu_copy_binary(img)#self.otsu_copy(img)
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img = img.astype(np.uint8)
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img = img.astype(np.uint8)
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#img= self.resize_image(img, int(img_height_h*0.9), int(img_width_h*0.9) )
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#img= self.resize_image(img, int(img_height_h*0.9), int(img_width_h*0.9) )
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if patches and cols==4:
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if patches and cols==4:
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#print(self.scale_x,img_width_h,'scale')
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#print(self.scale_x,img_width_h,'scale')
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if (self.scale_x==1 and img_width_h>4000) or (self.scale_x!=1 and img_width_h>3700):
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if (self.scale_x==1 and img_width_h>4000) or (self.scale_x!=1 and img_width_h>3700):
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@ -784,7 +779,7 @@ class eynollah:
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img = otsu_copy_binary(img)#self.otsu_copy(img)
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img = otsu_copy_binary(img)#self.otsu_copy(img)
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img = img.astype(np.uint8)
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img = img.astype(np.uint8)
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img= resize_image(img, int(img_height_h*0.9), int(img_width_h*0.9) )
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img= resize_image(img, int(img_height_h*0.9), int(img_width_h*0.9) )
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if patches and cols==5:
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if patches and cols==5:
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if (self.scale_x==1 and img_width_h>5000):
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if (self.scale_x==1 and img_width_h>5000):
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img = otsu_copy_binary(img)#self.otsu_copy(img)
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img = otsu_copy_binary(img)#self.otsu_copy(img)
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@ -795,7 +790,7 @@ class eynollah:
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img = otsu_copy_binary(img)#self.otsu_copy(img)
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img = otsu_copy_binary(img)#self.otsu_copy(img)
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img = img.astype(np.uint8)
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img = img.astype(np.uint8)
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img= resize_image(img, int(img_height_h*0.9), int(img_width_h*0.9) )
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img= resize_image(img, int(img_height_h*0.9), int(img_width_h*0.9) )
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if patches and cols>=6:
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if patches and cols>=6:
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if img_width_h>5600:
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if img_width_h>5600:
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img = otsu_copy_binary(img)#self.otsu_copy(img)
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img = otsu_copy_binary(img)#self.otsu_copy(img)
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@ -943,28 +938,21 @@ class eynollah:
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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]]
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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]]
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all_text_region_raw = all_text_region_raw.astype(np.uint8)
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all_text_region_raw = all_text_region_raw.astype(np.uint8)
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img_int_p = all_text_region_raw[:, :] # self.all_text_region_raw[mv]
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img_int_p = all_text_region_raw[:, :] # self.all_text_region_raw[mv]
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##img_int_p=cv2.erode(img_int_p,self.kernel,iterations = 2)
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##img_int_p=cv2.erode(img_int_p,self.kernel,iterations = 2)
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# plt.imshow(img_int_p)
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# plt.imshow(img_int_p)
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# plt.show()
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# plt.show()
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if img_int_p.shape[0] / img_int_p.shape[1] < 0.1:
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if img_int_p.shape[0] / img_int_p.shape[1] < 0.1:
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slopes_per_each_subprocess.append(0)
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slopes_per_each_subprocess.append(0)
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slope_first = 0
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slope_first = 0
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slope_for_all = [slope_deskew][0]
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slope_for_all = [slope_deskew][0]
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else:
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else:
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try:
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try:
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textline_con, hierachy = return_contours_of_image(img_int_p)
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textline_con, hierachy = return_contours_of_image(img_int_p)
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textline_con_fil = filter_contours_area_of_image(img_int_p, textline_con, hierachy, max_area=1, min_area=0.0008)
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textline_con_fil = filter_contours_area_of_image(img_int_p, textline_con, hierachy, max_area=1, min_area=0.0008)
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y_diff_mean = find_contours_mean_y_diff(textline_con_fil)
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y_diff_mean = find_contours_mean_y_diff(textline_con_fil)
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sigma_des = int(y_diff_mean * (4.0 / 40.0))
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sigma_des = int(y_diff_mean * (4.0 / 40.0))
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if sigma_des < 1:
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if sigma_des < 1:
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@ -979,37 +967,26 @@ class eynollah:
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# old method
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# old method
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# slope_for_all=self.textline_contours_to_get_slope_correctly(self.all_text_region_raw[mv],denoised,contours[mv])
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# slope_for_all=self.textline_contours_to_get_slope_correctly(self.all_text_region_raw[mv],denoised,contours[mv])
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# text_patch_processed=textline_contours_postprocessing(gada)
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# text_patch_processed=textline_contours_postprocessing(gada)
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except:
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except:
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slope_for_all = 999
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slope_for_all = 999
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##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)
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if slope_for_all == 999:
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if slope_for_all == 999:
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slope_for_all = [slope_deskew][0]
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slope_for_all = [slope_deskew][0]
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##if np.abs(slope_for_all)>32.5 and slope_for_all!=999:
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##slope_for_all=slope_biggest
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##elif slope_for_all==999:
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##slope_for_all=slope_biggest
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slopes_per_each_subprocess.append(slope_for_all)
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slopes_per_each_subprocess.append(slope_for_all)
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index_by_text_region_contours.append(indexes_r_con_per_pro[mv])
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index_by_text_region_contours.append(indexes_r_con_per_pro[mv])
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crop_img, crop_coor = crop_image_inside_box(boxes_text[mv], image_page_rotated)
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crop_img, crop_coor = crop_image_inside_box(boxes_text[mv], image_page_rotated)
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if abs(slope_for_all) < 45:
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if abs(slope_for_all) < 45:
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# all_box_coord.append(crop_coor)
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# all_box_coord.append(crop_coor)
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textline_region_in_image = np.zeros(textline_mask_tot_ea.shape)
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textline_region_in_image = np.zeros(textline_mask_tot_ea.shape)
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cnt_o_t_max = contours_par_per_process[mv]
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cnt_o_t_max = contours_par_per_process[mv]
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x, y, w, h = cv2.boundingRect(cnt_o_t_max)
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x, y, w, h = cv2.boundingRect(cnt_o_t_max)
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mask_biggest = np.zeros(mask_texts_only.shape)
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mask_biggest = np.zeros(mask_texts_only.shape)
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mask_biggest = cv2.fillPoly(mask_biggest, pts=[cnt_o_t_max], color=(1, 1, 1))
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mask_biggest = cv2.fillPoly(mask_biggest, pts=[cnt_o_t_max], color=(1, 1, 1))
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mask_region_in_patch_region = mask_biggest[y : y + h, x : x + w]
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mask_region_in_patch_region = mask_biggest[y : y + h, x : x + w]
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textline_biggest_region = mask_biggest * textline_mask_tot_ea
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textline_biggest_region = mask_biggest * textline_mask_tot_ea
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# print(slope_for_all,'slope_for_all')
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# print(slope_for_all,'slope_for_all')
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@ -1025,7 +1002,6 @@ class eynollah:
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# plt.imshow(textline_region_in_image)
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# plt.imshow(textline_region_in_image)
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# plt.show()
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# plt.show()
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# plt.imshow(textline_cnt_seperated)
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# plt.imshow(textline_cnt_seperated)
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# plt.show()
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# plt.show()
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@ -1039,21 +1015,16 @@ class eynollah:
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if num_col + 1 == 1:
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if num_col + 1 == 1:
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mask_biggest2 = cv2.dilate(mask_biggest2, self.kernel, iterations=5)
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mask_biggest2 = cv2.dilate(mask_biggest2, self.kernel, iterations=5)
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else:
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else:
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mask_biggest2 = cv2.dilate(mask_biggest2, self.kernel, iterations=4)
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mask_biggest2 = cv2.dilate(mask_biggest2, self.kernel, iterations=4)
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pixel_img = 1
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pixel_img = 1
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mask_biggest2 = resize_image(mask_biggest2, int(mask_biggest2.shape[0] * scale_par), int(mask_biggest2.shape[1] * scale_par))
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mask_biggest2 = resize_image(mask_biggest2, int(mask_biggest2.shape[0] * scale_par), int(mask_biggest2.shape[1] * scale_par))
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cnt_textlines_in_image_ind = return_contours_of_interested_textline(mask_biggest2, pixel_img)
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cnt_textlines_in_image_ind = return_contours_of_interested_textline(mask_biggest2, pixel_img)
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try:
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try:
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# textlines_cnt_per_region.append(cnt_textlines_in_image_ind[0]/scale_par)
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# textlines_cnt_per_region.append(cnt_textlines_in_image_ind[0]/scale_par)
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textlines_cnt_per_region.append(cnt_textlines_in_image_ind[0])
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textlines_cnt_per_region.append(cnt_textlines_in_image_ind[0])
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except:
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except:
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pass
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pass
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else:
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else:
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slope_first = 0
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slope_first = 0
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add_boxes_coor_into_textlines = True
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add_boxes_coor_into_textlines = True
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@ -1061,13 +1032,8 @@ class eynollah:
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add_boxes_coor_into_textlines = False
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add_boxes_coor_into_textlines = False
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# print(np.shape(textlines_cnt_per_region),'textlines_cnt_per_region')
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# print(np.shape(textlines_cnt_per_region),'textlines_cnt_per_region')
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# textlines_cnt_tot_per_process.append(textlines_cnt_per_region)
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# index_polygons_per_process_per_process.append(index_polygons_per_process[iiii])
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textlines_rectangles_per_each_subprocess.append(textlines_cnt_per_region)
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textlines_rectangles_per_each_subprocess.append(textlines_cnt_per_region)
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# all_found_texline_polygons.append(cnt_clean_rot)
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bounding_box_of_textregion_per_each_subprocess.append(boxes_text[mv])
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bounding_box_of_textregion_per_each_subprocess.append(boxes_text[mv])
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contours_textregion_per_each_subprocess.append(contours_per_process[mv])
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contours_textregion_per_each_subprocess.append(contours_per_process[mv])
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contours_textregion_par_per_each_subprocess.append(contours_par_per_process[mv])
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contours_textregion_par_per_each_subprocess.append(contours_par_per_process[mv])
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all_box_coord_per_process.append(crop_coor)
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all_box_coord_per_process.append(crop_coor)
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@ -1086,74 +1052,42 @@ class eynollah:
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slope_biggest = 0
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slope_biggest = 0
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for mv in range(len(boxes_text)):
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for mv in range(len(boxes_text)):
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crop_img,crop_coor=crop_image_inside_box(boxes_text[mv],image_page_rotated)
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crop_img,crop_coor=crop_image_inside_box(boxes_text[mv],image_page_rotated)
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#all_box_coord.append(crop_coor)
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mask_textline=np.zeros((textline_mask_tot_ea.shape))
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mask_textline=np.zeros((textline_mask_tot_ea.shape))
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mask_textline=cv2.fillPoly(mask_textline,pts=[contours_per_process[mv]],color=(1,1,1))
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mask_textline=cv2.fillPoly(mask_textline,pts=[contours_per_process[mv]],color=(1,1,1))
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denoised=None
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denoised=None
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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] ]
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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] ]
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all_text_region_raw=all_text_region_raw.astype(np.uint8)
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all_text_region_raw=all_text_region_raw.astype(np.uint8)
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img_int_p=all_text_region_raw[:,:]#self.all_text_region_raw[mv]
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img_int_p=all_text_region_raw[:,:]#self.all_text_region_raw[mv]
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img_int_p=cv2.erode(img_int_p,self.kernel,iterations = 2)
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img_int_p=cv2.erode(img_int_p,self.kernel,iterations = 2)
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if img_int_p.shape[0]/img_int_p.shape[1]<0.1:
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if img_int_p.shape[0]/img_int_p.shape[1]<0.1:
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slopes_per_each_subprocess.append(0)
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slopes_per_each_subprocess.append(0)
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slope_for_all = [slope_deskew][0]
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slope_for_all = [slope_deskew][0]
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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]]
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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]]
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cnt_clean_rot = textline_contours_postprocessing(all_text_region_raw, slope_for_all, contours_par_per_process[mv], boxes_text[mv], 0)
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cnt_clean_rot = textline_contours_postprocessing(all_text_region_raw, slope_for_all, contours_par_per_process[mv], boxes_text[mv], 0)
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textlines_rectangles_per_each_subprocess.append(cnt_clean_rot)
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textlines_rectangles_per_each_subprocess.append(cnt_clean_rot)
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index_by_text_region_contours.append(indexes_r_con_per_pro[mv])
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index_by_text_region_contours.append(indexes_r_con_per_pro[mv])
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# all_found_texline_polygons.append(cnt_clean_rot)
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bounding_box_of_textregion_per_each_subprocess.append(boxes_text[mv])
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bounding_box_of_textregion_per_each_subprocess.append(boxes_text[mv])
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else:
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else:
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try:
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try:
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textline_con, hierachy = return_contours_of_image(img_int_p)
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textline_con, hierachy = return_contours_of_image(img_int_p)
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textline_con_fil = filter_contours_area_of_image(img_int_p, textline_con, hierachy, max_area=1, min_area=0.00008)
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textline_con_fil = filter_contours_area_of_image(img_int_p, textline_con, hierachy, max_area=1, min_area=0.00008)
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y_diff_mean = find_contours_mean_y_diff(textline_con_fil)
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y_diff_mean = find_contours_mean_y_diff(textline_con_fil)
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sigma_des = int(y_diff_mean * (4.0 / 40.0))
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sigma_des = int(y_diff_mean * (4.0 / 40.0))
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if sigma_des < 1:
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if sigma_des < 1:
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sigma_des = 1
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sigma_des = 1
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img_int_p[img_int_p > 0] = 1
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img_int_p[img_int_p > 0] = 1
|
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|
# slope_for_all=self.return_deskew_slope_new(img_int_p,sigma_des)
|
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|
|
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)
|
|
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|
if abs(slope_for_all) <= 0.5:
|
|
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|
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
|
|
|
|
|
|
|
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|
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|
|
##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)
|
|
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|
|
|
|
|
|
|
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|
|
|
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
|
|
|
|
|
|
|
|
|
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@ -1595,7 +1507,7 @@ class eynollah:
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textregion.set('id','r'+str(id_indexer))
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textregion.set('id','r'+str(id_indexer))
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id_indexer+=1
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id_indexer+=1
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coord_text = ET.SubElement(textregion, 'Coords')
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coord_text = ET.SubElement(textregion, 'Coords')
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coord_text.set('points', self.calculate_polygon_coords(found_polygons_tables, mm, lmm, page_coord)
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coord_text.set('points', self.calculate_polygon_coords(found_polygons_tables, mm, lmm, page_coord))
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except:
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except:
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pass
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pass
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@ -1770,7 +1682,7 @@ class eynollah:
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textregion.set('id', id_of_marginalia[mm])
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textregion.set('id', id_of_marginalia[mm])
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textregion.set('type', 'marginalia')
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textregion.set('type', 'marginalia')
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coord_text = ET.SubElement(textregion, 'Coords')
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coord_text = ET.SubElement(textregion, 'Coords')
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coord_text.set('points', self.calculate_polygon_coords(found_polygons_marginals, mm, lmm, page_coord)
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coord_text.set('points', self.calculate_polygon_coords(found_polygons_marginals, mm, lmm, page_coord))
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for j in range(len(all_found_texline_polygons_marginals[mm])):
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for j in range(len(all_found_texline_polygons_marginals[mm])):
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textline=ET.SubElement(textregion, 'TextLine')
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textline=ET.SubElement(textregion, 'TextLine')
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textline.set('id','l'+str(id_indexer_l))
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textline.set('id','l'+str(id_indexer_l))
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