Comments (3)
Hi @Sunyingchun
For saving the model, it is a basic operation in Pytorch. If you are familiar with torch, you can easily add your code to save and load model with model.state_dict()
, torch.save
and torch.load
.
For evaluating the model, NYUv2 dataset has only two splits, namely train set and validate set. What the code prints in the screen are exactly evaluating the training model on the validate set.
Please forgive my race to be the first to answer the question @lorenmt. Please correct me if any mistake made.
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I think there is a similar issue: model_segnet_mtan prediction code · Issue #31 · lorenmt/mtan
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Thanks for your quick answer.
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Related Issues (20)
- depth and segmentation label in cityscape HOT 1
- NYUv2 surface normals grey boundary HOT 1
- Missing items in cityscapes/val/label_19 HOT 2
- Training with my own dataset HOT 16
- Definition of multi-task loss function HOT 5
- Training MTAN-DeepLabv3 HOT 10
- About the instantiation of the model HOT 1
- DWA HOT 1
- The para Temperature of DWA HOT 6
- How do you pre-process NYUv2 dataset? HOT 7
- about the uncertainty loss HOT 4
- about visulization of the result HOT 1
- Avg Cost accumulation HOT 2
- why dwa didn't consider common scale of gradient? HOT 8
- 关于Attention Module的设计 HOT 4
- results inconsistency HOT 19
- Question about the pre-processed cityscapes HOT 5
- DWA的loss梯度爆炸问题 HOT 2
- Question about the structure of the encoder_block_att. HOT 2
- Used Mtan on depth estimation and object detection HOT 5
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