qurator-spk/eynollah
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updating inference for early layout in the case of documents with number of columns bigger than 2

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vahidrezanezhad 2024-10-30 15:02:50 +01:00
parent 438df52287
commit e796a99c5c
1 changed files with 5 additions and 6 deletions
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11
qurator/eynollah/eynollah.py
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@ -2296,9 +2296,8 @@ class Eynollah:
#plt.show()
if not skip_layout_and_reading_order:
#print("inside 2 ", time.time()-t_in)
if not self.dir_in:
if num_col_classifier == 1 or num_col_classifier >= 2:
if num_col_classifier == 1 or num_col_classifier == 2:
model_region, session_region = self.start_new_session_and_model(self.model_region_dir_p_1_2_sp_np)
if self.image_org.shape[0]/self.image_org.shape[1] > 2.5:
prediction_regions_org = self.do_prediction_new_concept(True, img_resized, model_region, n_batch_inference=1, thresholding_for_artificial_class_in_light_version = True)
@ -2307,12 +2306,12 @@ class Eynollah:
prediction_regions_page = self.do_prediction_new_concept(False, self.image_page_org_size, model_region, n_batch_inference=1, thresholding_for_artificial_class_in_light_version = True)
prediction_regions_org[self.page_coord[0] : self.page_coord[1], self.page_coord[2] : self.page_coord[3],:] = prediction_regions_page
else:
model_region, session_region = self.start_new_session_and_model(self.model_region_dir_p_ens_light)
prediction_regions_org = self.do_prediction_new_concept(True, img_bin, model_region)
model_region, session_region = self.start_new_session_and_model(self.model_region_dir_p_1_2_sp_np)
prediction_regions_org = self.do_prediction_new_concept(True, resize_image(img_bin, int( (900+ (num_col_classifier-3)*100) *(img_bin.shape[0]/img_bin.shape[1]) ), 900+ (num_col_classifier-3)*100), model_region)
##model_region, session_region = self.start_new_session_and_model(self.model_region_dir_p_ens_light)
##prediction_regions_org = self.do_prediction(True, img_bin, model_region, n_batch_inference=3, thresholding_for_some_classes_in_light_version=True)
else:
if num_col_classifier == 1 or num_col_classifier >= 2:
if num_col_classifier == 1 or num_col_classifier == 2:
if self.image_org.shape[0]/self.image_org.shape[1] > 2.5:
prediction_regions_org = self.do_prediction_new_concept(True, img_resized, self.model_region_1_2, n_batch_inference=1, thresholding_for_artificial_class_in_light_version=True)
else:
@ -2320,7 +2319,7 @@ class Eynollah:
prediction_regions_page = self.do_prediction_new_concept(False, self.image_page_org_size, self.model_region_1_2, n_batch_inference=1, thresholding_for_artificial_class_in_light_version=True)
prediction_regions_org[self.page_coord[0] : self.page_coord[1], self.page_coord[2] : self.page_coord[3],:] = prediction_regions_page
else:
prediction_regions_org = self.do_prediction_new_concept(True, img_bin, self.model_region, n_batch_inference=3)
prediction_regions_org = self.do_prediction_new_concept(True, resize_image(img_bin, int( (900+ (num_col_classifier-3)*100) *(img_bin.shape[0]/img_bin.shape[1]) ), 900+ (num_col_classifier-3)*100), self.model_region_1_2, n_batch_inference=2)
###prediction_regions_org = self.do_prediction(True, img_bin, self.model_region, n_batch_inference=3, thresholding_for_some_classes_in_light_version=True)
#print("inside 3 ", time.time()-t_in)