assigner delete mask_positive (#8279)

ppdet/modeling/assigners/atss_assigner.py

@@ -222,4 +222,4 @@ class ATSSAssigner(nn.Layer):
                                          paddle.zeros_like(gather_scores))
             assigned_scores *= gather_scores.unsqueeze(-1)
 
-        return assigned_labels, assigned_bboxes, assigned_scores, mask_positive
+        return assigned_labels, assigned_bboxes, assigned_scores

ppdet/modeling/assigners/task_aligned_assigner.py

@@ -191,4 +191,4 @@ class TaskAlignedAssigner(nn.Layer):
         alignment_metrics = alignment_metrics.max(-2).unsqueeze(-1)
         assigned_scores = assigned_scores * alignment_metrics
 
-        return assigned_labels, assigned_bboxes, assigned_scores, mask_positive
+        return assigned_labels, assigned_bboxes, assigned_scores

ppdet/modeling/assigners/task_aligned_assigner_cr.py

@@ -179,4 +179,4 @@ class TaskAlignedAssigner_CR(nn.Layer):
         alignment_metrics = alignment_metrics.max(-2).unsqueeze(-1)
         assigned_scores = assigned_scores * alignment_metrics
 
-        return assigned_labels, assigned_bboxes, assigned_scores, mask_positive
+        return assigned_labels, assigned_bboxes, assigned_scores

ppdet/modeling/heads/pico_head.py

@@ -651,7 +651,7 @@ class PicoHeadV2(GFLHead):
 
         # label assignment
         if gt_meta['epoch_id'] < self.static_assigner_epoch:
-            assigned_labels, assigned_bboxes, assigned_scores, _ = self.static_assigner(
+            assigned_labels, assigned_bboxes, assigned_scores = self.static_assigner(
                 anchors,
                 num_anchors_list,
                 gt_labels,
@@ -662,7 +662,7 @@ class PicoHeadV2(GFLHead):
                 pred_bboxes=pred_bboxes.detach() * stride_tensor_list)
 
         else:
-            assigned_labels, assigned_bboxes, assigned_scores, _ = self.assigner(
+            assigned_labels, assigned_bboxes, assigned_scores = self.assigner(
                 pred_scores.detach(),
                 pred_bboxes.detach() * stride_tensor_list,
                 centers,

ppdet/modeling/heads/ppyoloe_contrast_head.py

@@ -121,7 +121,7 @@ class PPYOLOEContrastHead(PPYOLOEHead):
         pad_gt_mask = gt_meta['pad_gt_mask']
         # label assignment
         if gt_meta['epoch_id'] < self.static_assigner_epoch:
-            assigned_labels, assigned_bboxes, assigned_scores, _ = \
+            assigned_labels, assigned_bboxes, assigned_scores = \
                 self.static_assigner(
                     anchors,
                     num_anchors_list,
@@ -133,7 +133,7 @@ class PPYOLOEContrastHead(PPYOLOEHead):
             alpha_l = 0.25
         else:
             if self.sm_use:
-                assigned_labels, assigned_bboxes, assigned_scores, _ = \
+                assigned_labels, assigned_bboxes, assigned_scores = \
                     self.assigner(
                     pred_scores.detach(),
                     pred_bboxes.detach() * stride_tensor,
@@ -144,7 +144,7 @@ class PPYOLOEContrastHead(PPYOLOEHead):
                     pad_gt_mask,
                     bg_index=self.num_classes)
             else:
-                assigned_labels, assigned_bboxes, assigned_scores, _ = \
+                assigned_labels, assigned_bboxes, assigned_scores = \
                     self.assigner(
                     pred_scores.detach(),
                     pred_bboxes.detach() * stride_tensor,

ppdet/modeling/heads/ppyoloe_head.py

@@ -387,7 +387,7 @@ class PPYOLOEHead(nn.Layer):
         pad_gt_mask = gt_meta['pad_gt_mask']
         # label assignment
         if gt_meta['epoch_id'] < self.static_assigner_epoch:
-            assigned_labels, assigned_bboxes, assigned_scores, mask_positive = \
+            assigned_labels, assigned_bboxes, assigned_scores = \
                 self.static_assigner(
                     anchors,
                     num_anchors_list,
@@ -400,7 +400,7 @@ class PPYOLOEHead(nn.Layer):
         else:
             if self.sm_use:
                 # only used in smalldet of PPYOLOE-SOD model
-                assigned_labels, assigned_bboxes, assigned_scores, mask_positive = \
+                assigned_labels, assigned_bboxes, assigned_scores = \
                     self.assigner(
                     pred_scores.detach(),
                     pred_bboxes.detach() * stride_tensor,
@@ -413,7 +413,7 @@ class PPYOLOEHead(nn.Layer):
             else:
                 if aux_pred is None:
                     if not hasattr(self, "assigned_labels"):
-                        assigned_labels, assigned_bboxes, assigned_scores, mask_positive = \
+                        assigned_labels, assigned_bboxes, assigned_scores = \
                             self.assigner(
                             pred_scores.detach(),
                             pred_bboxes.detach() * stride_tensor,
@@ -427,15 +427,15 @@ class PPYOLOEHead(nn.Layer):
                             self.assigned_labels = assigned_labels
                             self.assigned_bboxes = assigned_bboxes
                             self.assigned_scores = assigned_scores
-                            self.mask_positive = mask_positive
+
                     else:
                         # only used in distill
                         assigned_labels = self.assigned_labels
                         assigned_bboxes = self.assigned_bboxes
                         assigned_scores = self.assigned_scores
-                        mask_positive = self.mask_positive
+
                 else:
-                    assigned_labels, assigned_bboxes, assigned_scores, mask_positive = \
+                    assigned_labels, assigned_bboxes, assigned_scores = \
                             self.assigner(
                             pred_scores_aux.detach(),
                             pred_bboxes_aux.detach() * stride_tensor,
@@ -451,14 +451,12 @@ class PPYOLOEHead(nn.Layer):
 
         assign_out_dict = self.get_loss_from_assign(
             pred_scores, pred_distri, pred_bboxes, anchor_points_s,
-            assigned_labels, assigned_bboxes, assigned_scores, mask_positive,
-            alpha_l)
+            assigned_labels, assigned_bboxes, assigned_scores, alpha_l)
 
         if aux_pred is not None:
             assign_out_dict_aux = self.get_loss_from_assign(
                 aux_pred[0], aux_pred[1], pred_bboxes_aux, anchor_points_s,
-                assigned_labels, assigned_bboxes, assigned_scores,
-                mask_positive, alpha_l)
+                assigned_labels, assigned_bboxes, assigned_scores, alpha_l)
             loss = {}
             for key in assign_out_dict.keys():
                 loss[key] = assign_out_dict[key] + assign_out_dict_aux[key]
@@ -469,7 +467,7 @@ class PPYOLOEHead(nn.Layer):
 
     def get_loss_from_assign(self, pred_scores, pred_distri, pred_bboxes,
                              anchor_points_s, assigned_labels, assigned_bboxes,
-                             assigned_scores, mask_positive, alpha_l):
+                             assigned_scores, alpha_l):
         # cls loss
         if self.use_varifocal_loss:
             one_hot_label = F.one_hot(assigned_labels,
@@ -490,7 +488,6 @@ class PPYOLOEHead(nn.Layer):
             self.distill_pairs['pred_cls_scores'] = pred_scores
             self.distill_pairs['pos_num'] = assigned_scores_sum
             self.distill_pairs['assigned_scores'] = assigned_scores
-            self.distill_pairs['mask_positive'] = mask_positive
             one_hot_label = F.one_hot(assigned_labels,
                                       self.num_classes + 1)[..., :-1]
             self.distill_pairs['target_labels'] = one_hot_label