Comments (1)
model = Resnet(Bottleneck, [3, 0, 0, 0], **kwargs) ,you will remove self.layer2, self.layer3, self.layer4, but you must rewrite forward func.
you want keep two of any layers,i think not right, such as keep layer1 and layer3, the output of layer1 can't feed in layer3
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Related Issues (20)
- 0 gradients 问题 HOT 2
- ModuleNotFoundError: No module named 'od.models'; 'od' is not a package HOT 1
- 数据增强 HOT 1
- 更改backbone HOT 1
- 有关head的问题 HOT 3
- 请问yaml文件中有关head的网络结构 HOT 4
- 请问模型的flops应该在哪输出 HOT 3
- 作者大大是否有跟进YOLOv5 V7.0版本实例分割功能的打算? HOT 2
- About the Resume HOT 1
- 使用mobilenetv3作为主干网络,无法导出onnx,并且没有错误提示。 HOT 5
- Add True negative data to training dataset HOT 2
- 使用替换backbone为swimtransformer的yolov5时,detect的时候,只能框住物体,不能显示置信度和种类 HOT 2
- ONNX: export failure: Expected all tensors to be on the same device, but found at least two devices, cpu and cuda:0! (when checking argument for argument other in method wrapper__equal) HOT 5
- error during compile HOT 11
- 求教 HOT 1
- Error help please HOT 3
- repvgg做为backbone时,保存的pt模型是多分支结构还是单路结构? HOT 5
- 使用repvgg训练,然后参数deploy为true,即改成单路推理结构时,出现训练无法收敛的情况?是不是由于每一次训练都直接转成了单路结构的原因? HOT 30
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