fixes

prime-slam · Apr 22, 2024 · 7c80b21 · 7c80b21
1 parent 4fc6aca
commit 7c80b21
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Showing 3 changed files with 85 additions and 28 deletions.
diff --git a/main_calc_metrics_by_csv.py b/main_calc_metrics_by_csv.py
@@ -19,12 +19,14 @@ def calculate_metrics(exec_id):
     values_pres = []
     values_recall = []
     values_fScore = []
-    with open("experiment_{}_sem_voxel_offset0_T0l02_50.csv".format(exec_id), "r") as file:
+    with open(
+        "experiment_{}_sem_voxel_offset0_T0l02_50.csv".format(exec_id), "r"
+    ) as file:
         reader = csv.DictReader(file)
         for row in reader:
-            values_pres.append(row['precision'])
-            values_recall.append(row['recall'])
-            values_fScore.append(row['fScore'])
+            values_pres.append(row["precision"])
+            values_recall.append(row["recall"])
+            values_fScore.append(row["fScore"])
 
     sum_pres = 0
     pres1 = 0
@@ -57,9 +59,21 @@ def calculate_metrics(exec_id):
             fscore0 += 1
 
     print("start exec_id={}".format(exec_id))
-    print("precision={}, 1={}, 0={}".format(sum_pres/float(len(values_pres)), pres1, pres0))
-    print("recall={}, 1={}, 0={}".format(sum_recall/float(len(values_recall)), recall1, recall0))
-    print("fscore={}, 1={}, 0={}".format(sum_fScore/float(len(values_fScore)), fscore1, fscore0))
+    print(
+        "precision={}, 1={}, 0={}".format(
+            sum_pres/float(len(values_pres)), pres1, pres0
+        )
+    )
+    print(
+        "recall={}, 1={}, 0={}".format(
+            sum_recall/float(len(values_recall)), recall1, recall0
+        )
+    )
+    print(
+        "fscore={}, 1={}, 0={}".format(
+            sum_fScore/float(len(values_fScore)), fscore1, fscore0
+        )
+    )
     print("finish exec_id={}".format(exec_id))
 
 

diff --git a/main_kitti_processing.py b/main_kitti_processing.py
@@ -77,7 +77,11 @@ def build_tuple_bin_saving(
 
     return (
         {"config": params},
-        {"pcd_for_clustering_before_voxelization_points": np.asarray(pcd_for_clustering.points)},
+        {
+            "pcd_for_clustering_before_voxelization_points": np.asarray(
+                pcd_for_clustering.points
+            )
+        },
         {"voxel_pcd_original_points": np.asarray(voxel_pcd.points)},
         {"voxel_trace_original": src_trace_arrays},
         {"trace_graphcut": trace_arrays},
@@ -160,7 +164,12 @@ def segment_pcds(config):
 
 
 def process_kitti(
-    from_num, to_num, id_exec, alpha_physical_distance, beta_instance_distance, T_normalized_cut
+    from_num,
+    to_num,
+    id_exec,
+    alpha_physical_distance,
+    beta_instance_distance,
+    T_normalized_cut,
 ):
 
     reduce_detail_int_to_union_threshold = 0.5
@@ -192,10 +201,8 @@ def process_kitti(
 
         result_tuple = segment_pcds(config)
 
-        file_name = (
-            "experiment_{}_sem_voxel_offset0_T0l02/start{}_end{}.pickle".format(
-                id_exec, config.start_index, config.end_index
-            )
+        file_name = "experiment_{}_sem_voxel_offset0_T0l02/start{}_end{}.pickle".format(
+            id_exec, config.start_index, config.end_index
         )
         new_file = open(file_name, "w")
         new_file.close()
@@ -208,44 +215,78 @@ def process_kitti(
 
 
 def main():
+    start_pcd_num = 1500
+    end_pcd_num = 4540
+    T_normalized_cut_common = 0.02
+
     exec_id_1 = 1
     alpha_physical_distance_1 = 5
     beta_instance_distance_1 = 3
-    T_normalized_cut_1 = 0.02
     print("start exec_id={}".format(exec_id_1))
-    process_kitti(1500, 4540, exec_id_1, alpha_physical_distance_1, beta_instance_distance_1, T_normalized_cut_1)
+    process_kitti(
+        start_pcd_num,
+        end_pcd_num,
+        exec_id_1,
+        alpha_physical_distance_1,
+        beta_instance_distance_1,
+        T_normalized_cut_common,
+    )
     print("finish exec_id={}".format(exec_id_1))
 
     exec_id_2 = 2
     alpha_physical_distance_2 = 5
     beta_instance_distance_2 = 5
-    T_normalized_cut_2 = 0.02
     print("start exec_id={}".format(exec_id_2))
-    process_kitti(1500, 4540, exec_id_2, alpha_physical_distance_2, beta_instance_distance_2, T_normalized_cut_2)
+    process_kitti(
+        start_pcd_num,
+        end_pcd_num,
+        exec_id_2,
+        alpha_physical_distance_2,
+        beta_instance_distance_2,
+        T_normalized_cut_common,
+    )
     print("finish exec_id={}".format(exec_id_2))
 
     exec_id_3 = 3
     alpha_physical_distance_3 = 3
     beta_instance_distance_3 = 5
-    T_normalized_cut_3 = 0.02
     print("start exec_id={}".format(exec_id_3))
-    process_kitti(1500, 4540, exec_id_3, alpha_physical_distance_3, beta_instance_distance_3, T_normalized_cut_3)
+    process_kitti(
+        start_pcd_num,
+        end_pcd_num,
+        exec_id_3,
+        alpha_physical_distance_3,
+        beta_instance_distance_3,
+        T_normalized_cut_common,
+    )
     print("finish exec_id={}".format(exec_id_3))
 
     exec_id_4 = 4
     alpha_physical_distance_4 = 3
     beta_instance_distance_4 = 3
-    T_normalized_cut_4 = 0.02
     print("start exec_id={}".format(exec_id_4))
-    process_kitti(1500, 4540, exec_id_4, alpha_physical_distance_4, beta_instance_distance_4, T_normalized_cut_4)
+    process_kitti(
+        start_pcd_num,
+        end_pcd_num,
+        exec_id_4,
+        alpha_physical_distance_4,
+        beta_instance_distance_4,
+        T_normalized_cut_common
+    )
     print("finish exec_id={}".format(exec_id_4))
 
     exec_id_5 = 5
     alpha_physical_distance_5 = 7
     beta_instance_distance_5 = 7
-    T_normalized_cut_5 = 0.02
     print("start exec_id={}".format(exec_id_5))
-    process_kitti(1500, 4540, exec_id_5, alpha_physical_distance_5, beta_instance_distance_5, T_normalized_cut_5)
+    process_kitti(
+        start_pcd_num,
+        end_pcd_num,
+        exec_id_5,
+        alpha_physical_distance_5,
+        beta_instance_distance_5,
+        T_normalized_cut_common,
+    )
     print("finish exec_id={}".format(exec_id_5))
 
 

diff --git a/main_kitti_processing_metrics.py b/main_kitti_processing_metrics.py
@@ -76,16 +76,18 @@ def main():
                 start_index = current_from_num
                 end_index = start_index + 4
 
-                file_name = "experiment_{}_sem_voxel_offset0_T0l02/start{}_end{}.pickle".format(
-                    execution_id, start_index, end_index
+                file_name = (
+                    "experiment_{}_sem_voxel_offset0_T0l02/start{}_end{}.pickle".format(
+                        execution_id, start_index, end_index
+                    )
                 )
 
                 with open(file_name, "rb") as file:
                     data = pickle.load(file)
 
-                trace = data[4]['trace_graphcut']
-                clusters = data[5]['clusters_graphcut']
-                inst_label_array_for_clustering = data[6]['inst_label_array_for_clustering']
+                trace = data[4]["trace_graphcut"]
+                clusters = data[5]["clusters_graphcut"]
+                inst_label_array_for_clustering = data[6]["inst_label_array_for_clustering"]
 
                 if (
                     inst_label_array_for_clustering.sum() == 0