实施 Faster R-CNN 对象检测算法时出错
Error while implenting the Faster R-CNN Object detection algorithm
我正在尝试实施 Faster R-CNN 对象检测算法,但出现异常错误。
尝试在此 colab tutorial I had an error in the loss_dict = model(images, targets)
which is mentioned here 中调用 train_one_epoch
函数时。
我遇到的确切错误是:
101 cell_anchors = self.cell_anchors
102 assert cell_anchors is not None
--> 103 assert len(grid_sizes) == len(strides) == len(cell_anchors)
104
105 for size, stride, base_anchors in zip(
AssertionError:
有人有想法吗?提前致谢!
最后,我解决了这个问题,只是通过在 Faster R-CNN 函数中添加调整 AnchorGenerator 的大小及其对应的纵横比
ft_anchor_generator = AnchorGenerator(
sizes=((32, 64, 128),), aspect_ratios=((0.5, 1.0, 2.0),)
)
ft_model = FasterRCNN(
backbone=ft_backbone,
num_classes=num_classes,
rpn_anchor_generator=ft_anchor_generator)
我正在尝试实施 Faster R-CNN 对象检测算法,但出现异常错误。
尝试在此 colab tutorial I had an error in the loss_dict = model(images, targets)
which is mentioned here 中调用 train_one_epoch
函数时。
我遇到的确切错误是:
101 cell_anchors = self.cell_anchors
102 assert cell_anchors is not None
--> 103 assert len(grid_sizes) == len(strides) == len(cell_anchors)
104
105 for size, stride, base_anchors in zip(
AssertionError:
有人有想法吗?提前致谢!
最后,我解决了这个问题,只是通过在 Faster R-CNN 函数中添加调整 AnchorGenerator 的大小及其对应的纵横比
ft_anchor_generator = AnchorGenerator(
sizes=((32, 64, 128),), aspect_ratios=((0.5, 1.0, 2.0),)
)
ft_model = FasterRCNN(
backbone=ft_backbone,
num_classes=num_classes,
rpn_anchor_generator=ft_anchor_generator)