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fix gardcam error using in mmdet (#779)

tutorials
Haian Huang(深度眸) 2023-05-17 19:39:43 +08:00 committed by GitHub
parent a3b6ae1d65
commit 1e5372e993
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1 changed files with 8 additions and 3 deletions
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11
mmyolo/utils/boxam_utils.py
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@ -202,8 +202,10 @@ class BoxAMDetectorWrapper(nn.Module):
if self.is_need_loss: if self.is_need_loss:
# Maybe this is a direction that can be optimized # Maybe this is a direction that can be optimized
# self.detector.init_weights() # self.detector.init_weights()
if hasattr(self.detector.bbox_head, 'head_module'):
self.detector.bbox_head.head_module.training = True self.detector.bbox_head.head_module.training = True
else:
self.detector.bbox_head.training = True
if hasattr(self.detector.bbox_head, 'featmap_sizes'): if hasattr(self.detector.bbox_head, 'featmap_sizes'):
# Prevent the model algorithm error when calculating loss # Prevent the model algorithm error when calculating loss
self.detector.bbox_head.featmap_sizes = None self.detector.bbox_head.featmap_sizes = None
@ -219,7 +221,10 @@ class BoxAMDetectorWrapper(nn.Module):
return [loss] return [loss]
else: else:
self.detector.bbox_head.head_module.training = False if hasattr(self.detector.bbox_head, 'head_module'):
self.detector.bbox_head.head_module.training = False
else:
self.detector.bbox_head.training = False
with torch.no_grad(): with torch.no_grad():
results = self.detector.test_step(self.input_data) results = self.detector.test_step(self.input_data)
return results return results