From c9c759168b7a30a8c01e3bb8c63df48225fd8ec3 Mon Sep 17 00:00:00 2001
From: Denis <62305993+gudovskiyd@users.noreply.github.com>
Date: Tue, 21 Mar 2023 13:15:21 -0700
Subject: [PATCH] fixed old np.bool with bool

---
 train.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/train.py b/train.py
index 51fbbc7..65c31f4 100644
--- a/train.py
+++ b/train.py
@@ -329,11 +329,11 @@ def train(c):
         super_mask = score_mask.max() - score_mask
         # calculate detection AUROC
         score_label = np.max(super_mask, axis=(1, 2))
-        gt_label = np.asarray(gt_label_list, dtype=np.bool)
+        gt_label = np.asarray(gt_label_list, dtype=bool)
         det_roc_auc = roc_auc_score(gt_label, score_label)
         _ = det_roc_obs.update(100.0*det_roc_auc, epoch)
         # calculate segmentation AUROC
-        gt_mask = np.squeeze(np.asarray(gt_mask_list, dtype=np.bool), axis=1)
+        gt_mask = np.squeeze(np.asarray(gt_mask_list, dtype=bool), axis=1)
         seg_roc_auc = roc_auc_score(gt_mask.flatten(), super_mask.flatten())
         save_best_seg_weights = seg_roc_obs.update(100.0*seg_roc_auc, epoch)
         if save_best_seg_weights and c.action_type != 'norm-test':
@@ -352,7 +352,7 @@ def train(c):
             pros_std = []
             threds = []
             fprs = []
-            binary_score_maps = np.zeros_like(super_mask, dtype=np.bool)
+            binary_score_maps = np.zeros_like(super_mask, dtype=bool)
             for step in range(max_step):
                 thred = max_th - step * delta
                 # segmentation