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The optflow results of Pretrained weights is all zeros #13

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llltttppp opened this issue Jan 7, 2019 · 10 comments
Open

The optflow results of Pretrained weights is all zeros #13

llltttppp opened this issue Jan 7, 2019 · 10 comments

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@llltttppp
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预训练的SegFlow.caffemodel模型中的score_res3_con_flow层权值全为0导致光流输出结果全是0,希望能提供正确的权值下载

In pretrained weights SegFlow.caffemodel, weights of layer("score_res3_con_flow") is all zeros, please upload a correct pretrained weights, thank you!

@fish8sank
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I have the same questions as llltttppp said,even when i used the pretrained flownet model to train my own data,the flow result turns out to be all zeros.
Need some help.

@lcf000000
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I have the same questions as llltttppp said,even when i used the pretrained flownet model to train my own data,the flow result turns out to be all zeros.
Need some help.

I use the pre-trained model which they provide to us, but the result is wrong, it can't segment anything.
Should I train the model on myself ?

@fish8sank
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I have the same questions as llltttppp said,even when i used the pretrained flownet model to train my own data,the flow result turns out to be all zeros.
Need some help.

I use the pre-trained model which they provide to us, but the result is wrong, it can't segment anything.
Should I train the model on myself ?

I think you should train the network with your own data

@lcf000000
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I have the same questions as llltttppp said,even when i used the pretrained flownet model to train my own data,the flow result turns out to be all zeros.
Need some help.

I use the pre-trained model which they provide to us, but the result is wrong, it can't segment anything.
Should I train the model on myself ?

I think you should train the network with your own data

I just run the demo.
$ python infer_DAVIS.py dog
So they just provide a pre-trained model instead of a well trained model?

@fish8sank
Copy link

I have the same questions as llltttppp said,even when i used the pretrained flownet model to train my own data,the flow result turns out to be all zeros.
Need some help.

I use the pre-trained model which they provide to us, but the result is wrong, it can't segment anything.
Should I train the model on myself ?

I think you should train the network with your own data

I just run the demo.
$ python infer_DAVIS.py dog
So they just provide a pre-trained model instead of a well trained model?

You mean you test the data they provide by using the model they gave?If so, there should be segmentation results.You can check infer_DAVIS.py, I assume there are something wrong in your demo code.

@lcf000000
Copy link

I have the same questions as llltttppp said,even when i used the pretrained flownet model to train my own data,the flow result turns out to be all zeros.
Need some help.

I use the pre-trained model which they provide to us, but the result is wrong, it can't segment anything.
Should I train the model on myself ?

I think you should train the network with your own data

I just run the demo.
$ python infer_DAVIS.py dog
So they just provide a pre-trained model instead of a well trained model?

You mean you test the data they provide by using the model they gave?If so, there should be segmentation results.You can check infer_DAVIS.py, I assume there are something wrong in your demo code.

Oh, I modifed deploy.prototxt file.
Now , it works well, thx very much !

@xieguotian
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I have the same questions as llltttppp said,even when i used the pretrained flownet model to train my own data,the flow result turns out to be all zeros.
Need some help.

I use the pre-trained model which they provide to us, but the result is wrong, it can't segment anything.
Should I train the model on myself ?

I think you should train the network with your own data

I just run the demo.
$ python infer_DAVIS.py dog
So they just provide a pre-trained model instead of a well trained model?

You mean you test the data they provide by using the model they gave?If so, there should be segmentation results.You can check infer_DAVIS.py, I assume there are something wrong in your demo code.

Oh, I modifed deploy.prototxt file.
Now , it works well, thx very much !

How to modify deploy.prototxt file ?

@lcf000000
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I have the same questions as llltttppp said,even when i used the pretrained flownet model to train my own data,the flow result turns out to be all zeros.
Need s

预训练的SegFlow.caffemodel模型中的score_res3_con_flow层权值全为0导致光流输出结果全是0,希望能提供正确的权值下载

In pretrained weights SegFlow.caffemodel, weights of layer("score_res3_con_flow") is all zeros, please upload a correct pretrained weights, thank you!

Did you solve this problem ? The flow branch always output zero, so it doesn't contribute to segmentation result actually.

@mingqizhang
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在训练的时候有个问题,分割分支和光流分支的训练数据是不一样的。但两个分支在后部分有特征层相互使用,所以在训练分割分支时输入是分割数据,光流分支参数固定,但后面给分割分支的光流特征还是要有的,所以光流分支的输入是什么呢,难道是同样的分割数据吗。同理在训练光流分支的时候,输入的光流数据,那分割之分的输入是什么呢?请问有人知道吗?

@ShristiDasBiswas
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I have the same questions as llltttppp said,even when i used the pretrained flownet model to train my own data,the flow result turns out to be all zeros.
Need s

预训练的SegFlow.caffemodel模型中的score_res3_con_flow层权值全为0导致光流输出结果全是0,希望能提供正确的权值下载
In pretrained weights SegFlow.caffemodel, weights of layer("score_res3_con_flow") is all zeros, please upload a correct pretrained weights, thank you!

Did you solve this problem ? The flow branch always output zero, so it doesn't contribute to segmentation result actually.

were you able to get it working? please share what changes you made.

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