diff --git a/qurator/eynollah/eynollah.py b/qurator/eynollah/eynollah.py index b83db98..35992c9 100644 --- a/qurator/eynollah/eynollah.py +++ b/qurator/eynollah/eynollah.py @@ -2857,32 +2857,20 @@ class Eynollah: return model def do_order_of_regions_with_machine(self,contours_only_text_parent, contours_only_text_parent_h, text_regions_p): - - #print(text_regions_p.shape) y_len = text_regions_p.shape[0] x_len = text_regions_p.shape[1] img_poly = np.zeros((y_len,x_len), dtype='uint8') unique_pix = np.unique(text_regions_p) - #print(unique_pix, 'unique_pix') - - #for pix in unique_pix: - #print(pix) - #plt.imshow((text_regions_p[:,:]==pix)*1 ) - #plt.show() + img_poly[text_regions_p[:,:]==1] = 1 img_poly[text_regions_p[:,:]==2] = 2 img_poly[text_regions_p[:,:]==3] = 4 img_poly[text_regions_p[:,:]==6] = 5 - #plt.imshow(text_regions_p) - #plt.show() - - - #plt.imshow(img_poly) - #plt.show() + model_ro_machine, _ = self.start_new_session_and_model(self.model_reading_order_machine_dir) height1 =672#448 @@ -2900,19 +2888,11 @@ class Eynollah: img_header_and_sep = np.zeros((y_len,x_len), dtype='uint8') for j in range(len(cy_main)): - #print(j, int(y_max_main[j]), x_min_main[j], x_max_main[j] ) img_header_and_sep[int(y_max_main[j]):int(y_max_main[j])+12,int(x_min_main[j]):int(x_max_main[j]) ] = 1 - #plt.imshow(img_header_and_sep[:,:]) - #plt.show() co_text_all = contours_only_text_parent + contours_only_text_parent_h - #id_all_text = id_paragraph + id_header - - #texts_corr_order_index = [index_tot_regions[tot_region_ref.index(i)] for i in id_all_text ] - #texts_corr_order_index_int = [int(x) for x in texts_corr_order_index] - #co_text_all, texts_corr_order_index_int = filter_contours_area_of_image(img_poly, co_text_all, texts_corr_order_index_int, max_area, min_area) labels_con = np.zeros((y_len,x_len,len(co_text_all)),dtype='uint8') for i in range(len(co_text_all)): @@ -2932,63 +2912,69 @@ class Eynollah: img3 = img3.astype(np.uint16) - #plt.imshow(img3) - #plt.show() - order_matrix = np.zeros((labels_con.shape[2], labels_con.shape[2]))-1 + inference_bs = 6 + tot_counter = 1 + batch_counter = 0 + i_indexer = [] + j_indexer =[] + + input_1= np.zeros( (inference_bs, height1, width1,3)) + tot_iteration = int( ( labels_con.shape[2]*(labels_con.shape[2]-1) )/2. ) + full_bs_ite= tot_iteration//inference_bs + last_bs = tot_iteration % inference_bs + + #print(labels_con.shape[2],"number of regions for reading order") for i in range(labels_con.shape[2]): for j in range(labels_con.shape[2]): if j>i: img1= np.repeat(labels_con[:,:,i][:, :, np.newaxis], 3, axis=2) img2 = np.repeat(labels_con[:,:,j][:, :, np.newaxis], 3, axis=2) - #img1 = img1.astype(np.uint16) - #img2 = img2.astype(np.uint16) img2[:,:,0][img3[:,:]==5] = 2 img2[:,:,0][img_header_and_sep[:,:]==1] = 3 - - img1[:,:,0][img3[:,:]==5] = 2 img1[:,:,0][img_header_and_sep[:,:]==1] = 3 - #plt.imshow(labels_con[:,:,i]) - #plt.show() - - #plt.imshow(img2[:,:,0]) - #plt.show() - + i_indexer.append(i) + j_indexer.append(j) - #plt.imshow(img1[:,:,0]) - #plt.show() + input_1[batch_counter,:,:,0] = img1[:,:,0]/3. + input_1[batch_counter,:,:,2] = img2[:,:,0]/3. + input_1[batch_counter,:,:,1] = img3[:,:]/5. - #sys.exit() - input_1= np.zeros( (height1, width1,3)) + batch_counter = batch_counter+1 - input_1[:,:,0] = img1[:,:,0]/3. - input_1[:,:,2] = img2[:,:,0]/3. - input_1[:,:,1] = img3[:,:]/5. - - #y_pr=model.predict([img1.reshape(1,height1,width1,3) , img2.reshape(1,height2,width2,3),img3.reshape(1,height3,width3,3) ], verbose=2) - y_pr=model_ro_machine.predict(input_1.reshape(1,height1,width1,3) , verbose=0) - #print(y_pr) + if batch_counter==inference_bs or ( (tot_counter//inference_bs)==full_bs_ite and tot_counter%inference_bs==last_bs): + y_pr=model_ro_machine.predict(input_1 , verbose=0) - if y_pr>=0.5: - order_class = 1 - else: - order_class = 0 + if batch_counter==inference_bs: + iteration_batches = inference_bs + else: + iteration_batches = last_bs + for jb in range(iteration_batches): + if y_pr[jb][0]>=0.5: + order_class = 1 + else: + order_class = 0 + + order_matrix[i_indexer[jb],j_indexer[jb]] = y_pr[jb][0]#order_class + order_matrix[j_indexer[jb],i_indexer[jb]] = 1-y_pr[jb][0]#int( 1 - order_class) + + batch_counter = 0 - order_matrix[i,j] = y_pr#order_class - order_matrix[j,i] = 1-y_pr#int( 1 - order_class) + i_indexer = [] + j_indexer = [] + tot_counter = tot_counter+1 sum_mat = np.sum(order_matrix, axis=1) index_sort = np.argsort(sum_mat) index_sort = index_sort[::-1] - print(index_sort) REGION_ID_TEMPLATE = 'region_%04d' order_of_texts = [] id_of_texts = [] @@ -3272,13 +3258,12 @@ class Eynollah: order_text_new, id_of_texts_tot = self.do_order_of_regions(contours_only_text_parent, contours_only_text_parent_h, boxes, textline_mask_tot) else: order_text_new, id_of_texts_tot = self.do_order_of_regions(contours_only_text_parent_d_ordered, contours_only_text_parent_h_d_ordered, boxes_d, textline_mask_tot_d) + self.logger.info("detection of reading order took %.1fs", time.time() - t_order) pcgts = self.writer.build_pagexml_full_layout(contours_only_text_parent, contours_only_text_parent_h, page_coord, order_text_new, id_of_texts_tot, all_found_textline_polygons, all_found_textline_polygons_h, all_box_coord, all_box_coord_h, polygons_of_images, contours_tables, polygons_of_drop_capitals, polygons_of_marginals, all_found_textline_polygons_marginals, all_box_coord_marginals, slopes, slopes_h, slopes_marginals, cont_page, polygons_lines_xml) self.logger.info("Job done in %.1fs", time.time() - t0) ##return pcgts - print(id_of_texts_tot,'id_of_texts_tot') - print(order_text_new,'order_text_new') else: contours_only_text_parent_h = None @@ -3291,6 +3276,7 @@ class Eynollah: contours_only_text_parent_d_ordered = list(np.array(contours_only_text_parent_d_ordered, dtype=object)[index_by_text_par_con]) order_text_new, id_of_texts_tot = self.do_order_of_regions(contours_only_text_parent_d_ordered, contours_only_text_parent_h, boxes_d, textline_mask_tot_d) + self.logger.info("detection of reading order took %.1fs", time.time() - t_order) pcgts = self.writer.build_pagexml_no_full_layout(txt_con_org, page_coord, order_text_new, id_of_texts_tot, all_found_textline_polygons, all_box_coord, polygons_of_images, polygons_of_marginals, all_found_textline_polygons_marginals, all_box_coord_marginals, slopes, slopes_marginals, cont_page, polygons_lines_xml, contours_tables) self.logger.info("Job done in %.1fs", time.time() - t0) ##return pcgts