[Fix]: Deprecate np.bool Type Alias (open-mmlab#9498)

* deprecating np.bool type alias

* updating the flake8 version to fix flake8 bug

mmdet/core/evaluation/mean_ap.py

@@ -93,8 +93,8 @@ def tpfp_imagenet(det_bboxes,
 
     # an indicator of ignored gts
     gt_ignore_inds = np.concatenate(
-        (np.zeros(gt_bboxes.shape[0], dtype=np.bool),
-         np.ones(gt_bboxes_ignore.shape[0], dtype=np.bool)))
+        (np.zeros(gt_bboxes.shape[0],
+                  dtype=bool), np.ones(gt_bboxes_ignore.shape[0], dtype=bool)))
     # stack gt_bboxes and gt_bboxes_ignore for convenience
     gt_bboxes = np.vstack((gt_bboxes, gt_bboxes_ignore))
 
@@ -202,8 +202,8 @@ def tpfp_default(det_bboxes,
 
     # an indicator of ignored gts
     gt_ignore_inds = np.concatenate(
-        (np.zeros(gt_bboxes.shape[0], dtype=np.bool),
-         np.ones(gt_bboxes_ignore.shape[0], dtype=np.bool)))
+        (np.zeros(gt_bboxes.shape[0],
+                  dtype=bool), np.ones(gt_bboxes_ignore.shape[0], dtype=bool)))
     # stack gt_bboxes and gt_bboxes_ignore for convenience
     gt_bboxes = np.vstack((gt_bboxes, gt_bboxes_ignore))
 
@@ -317,8 +317,8 @@ def tpfp_openimages(det_bboxes,
 
     # an indicator of ignored gts
     gt_ignore_inds = np.concatenate(
-        (np.zeros(gt_bboxes.shape[0], dtype=np.bool),
-         np.ones(gt_bboxes_ignore.shape[0], dtype=np.bool)))
+        (np.zeros(gt_bboxes.shape[0],
+                  dtype=bool), np.ones(gt_bboxes_ignore.shape[0], dtype=bool)))
     # stack gt_bboxes and gt_bboxes_ignore for convenience
     gt_bboxes = np.vstack((gt_bboxes, gt_bboxes_ignore))
 
@@ -517,7 +517,7 @@ def get_cls_group_ofs(annotations, class_id):
         if ann.get('gt_is_group_ofs', None) is not None:
             gt_group_ofs.append(ann['gt_is_group_ofs'][gt_inds])
         else:
-            gt_group_ofs.append(np.empty((0, 1), dtype=np.bool))
+            gt_group_ofs.append(np.empty((0, 1), dtype=bool))
 
     return gt_group_ofs
 

mmdet/core/export/model_wrappers.py

@@ -82,7 +82,7 @@ def forward(self, img, img_metas, return_loss=True, **kwargs):
                     masks = torch.nn.functional.interpolate(
                         masks.unsqueeze(0), size=(ori_h, ori_w))
                     masks = masks.squeeze(0).detach().numpy()
-                if masks.dtype != np.bool:
+                if masks.dtype != bool:
                     masks = masks >= 0.5
                 segms_results = [[] for _ in range(len(self.CLASSES))]
                 for j in range(len(dets)):

mmdet/core/mask/structures.py

@@ -1068,7 +1068,7 @@ def polygon_to_bitmap(polygons, height, width):
     """
     rles = maskUtils.frPyObjects(polygons, height, width)
     rle = maskUtils.merge(rles)
-    bitmap_mask = maskUtils.decode(rle).astype(np.bool)
+    bitmap_mask = maskUtils.decode(rle).astype(bool)
     return bitmap_mask
 
 

mmdet/datasets/openimages.py

@@ -267,13 +267,13 @@ def get_ann_info(self, idx):
             labels_ignore = np.array(labels_ignore)
 
         assert len(is_group_ofs) == len(labels) == len(bboxes)
-        gt_is_group_ofs = np.array(is_group_ofs, dtype=np.bool)
+        gt_is_group_ofs = np.array(is_group_ofs, dtype=bool)
 
         # These parameters is not used yet.
-        is_occludeds = np.array(is_occludeds, dtype=np.bool)
-        is_truncateds = np.array(is_truncateds, dtype=np.bool)
-        is_depictions = np.array(is_depictions, dtype=np.bool)
-        is_insides = np.array(is_insides, dtype=np.bool)
+        is_occludeds = np.array(is_occludeds, dtype=bool)
+        is_truncateds = np.array(is_truncateds, dtype=bool)
+        is_depictions = np.array(is_depictions, dtype=bool)
+        is_insides = np.array(is_insides, dtype=bool)
 
         ann = dict(
             bboxes=bboxes.astype(np.float32),
@@ -450,7 +450,7 @@ def add_supercategory_ann(self, annotations):
                 bboxes=np.array(gt_bboxes).astype(np.float32),
                 labels=np.array(gt_labels).astype(np.int64),
                 bboxes_ignore=ann['bboxes_ignore'],
-                gt_is_group_ofs=np.array(gt_is_group_ofs).astype(np.bool))
+                gt_is_group_ofs=np.array(gt_is_group_ofs).astype(bool))
 
         return annotations
 
@@ -790,7 +790,7 @@ def load_annotations(self, ann_file):
             gt_bboxes = np.array(bboxes, dtype=np.float32)
             gt_labels = np.array(labels, dtype=np.int64)
             gt_bboxes_ignore = np.zeros((0, 4), dtype=np.float32)
-            gt_is_group_ofs = np.array(is_group_ofs, dtype=np.bool)
+            gt_is_group_ofs = np.array(is_group_ofs, dtype=bool)
 
             img_info = dict(filename=filename)
             ann_info = dict(

tests/test_metrics/test_mean_ap.py

@@ -114,7 +114,7 @@ def test_tpfp_openimages():
                            [10, 10, 25, 25, 0.98], [28, 28, 35, 35, 0.97],
                            [30, 30, 51, 51, 0.96], [100, 110, 120, 130, 0.15]])
     gt_bboxes = np.array([[10., 10., 30., 30.], [30., 30., 50., 50.]])
-    gt_groups_of = np.array([True, False], dtype=np.bool)
+    gt_groups_of = np.array([True, False], dtype=bool)
     gt_ignore = np.zeros((0, 4))
 
     # Open Images evaluation using group of.
@@ -158,7 +158,7 @@ def test_tpfp_openimages():
     assert cls_dets.shape == (6, 5)
 
     # Open Images evaluation using group of, and gt is all group of bboxes.
-    gt_groups_of = np.array([True, True], dtype=np.bool)
+    gt_groups_of = np.array([True, True], dtype=bool)
     result = tpfp_openimages(
         det_bboxes,
         gt_bboxes,