cleaning and debug HAL

lium_baseline/cross_show.py

@@ -316,6 +316,7 @@ def allies_cross_show_clustering(show_idx, model, current_diar, current_vec, th_
                                                                          lim=lim,
                                                                          reference_path=reference_path,
                                                                          do_hal=hal)
+
         model["previous_vec"]=previous_vec
         model["previous_diar"]=previous_diar
 

lium_baseline/interactive.py

@@ -1051,7 +1051,6 @@ def run_active_learning_tree(link,
     stop_clustering_list = []  # a list of nodes that have gotten confirmation for clustering question
 
     der, new_diar = check_der(init_diar, bottomline_cluster_list, temporary_link_list, ref, uem)
-    print("Initial DER based on bottomline_diar and linkage : ", der)
     der_track_show = {"der_log": [der], "correction": ["initial"]}
 
     for node in links_to_check:
@@ -1277,12 +1276,12 @@ def allies_within_show_hal(model_cfg,
     model_cfg["model"]["vad"]["type"] = "reference"
     model_cfg['first_seg']['thr_h']=model_cfg['within_show']['thr_h']
 
+
     bottomline_diar, link_within_clusters_dic, vec_within_clusters_dic = create_bottomline_clustering(model,
                                                                                                       model_cfg,
                                                                                                       show,
                                                                                                       init_diar,
                                                                                                       data_folder)
-
     model_cfg["model"]["vad"]["type"] = backup_vad_type
     model_cfg['first_seg']['thr_h'] = backup_thr_h
 
@@ -1296,15 +1295,14 @@ def allies_within_show_hal(model_cfg,
     #       check does bottomline_diar plus sub cluster linkage make current_diar          #
     hyp = s4d_to_allies(init_diar)
     der_init, fa_rate, miss_rate, conf_rate, error, time, newspkmap = compute_der([ref], [hyp], [uem], collar = 0.250)
-    print("Current DER (original) : ", der_init)
 
     hyp = s4d_to_allies(bottomline_diar)
     der, fa_rate, miss_rate, conf_rate, error, time, newspkmap = compute_der([ref], [hyp], [uem], collar = 0.250)
     print("DER of bottomline_diar: ", der)
 
     vec_per_seg.modelset = vec_per_seg.modelset.astype(object)
-    for idx in range(len(bottomline_diar)):
-        vec_per_seg.modelset[idx] = bottomline_diar[idx]['cluster']
+    #for idx in range(len(bottomline_diar)):
+    #    vec_per_seg.modelset[idx] = bottomline_diar[idx]['cluster']
 
     if c2s != 'ideal':
 

lium_baseline/system.py

@@ -68,11 +68,6 @@ def bic_linear_segmentation(init_diar, cep, model_cfg):
     output_diar = s4d.segmentation(cep, output_diar)
     output_diar = s4d.bic_linear(cep, output_diar, model_cfg['first_seg']['thr_l'], sr=False)
 
-    #for seg in output_diar:
-    #    if seg.duration() > 3:
-    #        final_diar.append_diar(seg)
-    
-    #print(f"Nombre de segments apres BIC LIN filtering: {len(final_diar)}")
 
     return output_diar
 

lium_baseline/utils.py

@@ -209,7 +209,7 @@ def apply_link_on_diar(current_diar, cluster_list, full_link_tmp):
             cluster_list.append(c_label)
             current_diar.rename('cluster', [c0], c_label)
         else:
-            print("in gone", full_link_tmp[i])
+            #print("in gone", full_link_tmp[i])
             pass
 
         i += 1