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hellochick avatar hellochick commented on July 28, 2024

Hey @irfanICMLL .
The pretrained model "90k_bn" comes from the source code of ICNet:
https://github.com/hszhao/ICNet/tree/master/evaluation/model
You can fine-tune on it, but I think it cannot be much better.

The reason is, this model have been already pruned by the original author. So, if you focus on the number of kernels, you will find all the numbers of kernels are half of those in PSPNet.

So the best approach is, fine-tuning on the model before pruning, and then do model compression.
Hope my answer can help you. Btw, I keep training ADE20k dataset on it, and get result in the bottom of README.

from icnet-tensorflow.

irfanICMLL avatar irfanICMLL commented on July 28, 2024

So the decrease of the accuracy is caused by the purning?
And if I want to fune-tuning the "90k", I need to write another script? What is the loss function of the ICNET. I found that the ICNET only has one branch for output, while the ICNET_BN has three and the loss is in a combined form. The loss function described in the artical is also a combined form. I feel really confused....

from icnet-tensorflow.

hellochick avatar hellochick commented on July 28, 2024

@irfanICMLL , I don't think the decrease of the accuracy is caused by the pruning, I still can't find the answer to the strange accuracy. Maybe the model is different to each other.
You can directly modified train.py, I have create the loss formula in it. You can take a look on it.

from icnet-tensorflow.

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