Problem loading model
uricamic opened this issue · comments
Hi,
I tried downloading and converting the models as suggested in the README:
bash scripts/setup_caffemodels.sh
python convert.py --dataset coco
However, when I try to run the demo, I am getting this error message:
RuntimeError: Error(s) in loading state_dict for MSC:
Missing key(s) in state_dict: "base.layer1.conv1.conv.weight", "base.layer1.conv1.bn.weight", "base.layer1.conv1.bn.bias", "base.layer1.conv1.bn.running_mean", "base.layer1.conv1.bn.running_var", "base.layer2.block1.reduce.conv.weight", "base.layer2.block1.reduce.bn.weight", "base.layer2.block1.reduce.bn.bias", "base.layer2.block1.reduce.bn.running_mean", "base.layer2.block1.reduce.bn.running_var", "base.layer2.block1.conv3x3.conv.weight", "base.layer2.block1.conv3x3.bn.weight", "base.layer2.block1.conv3x3.bn.bias", "base.layer2.block1.conv3x3.bn.running_mean", "base.layer2.block1.conv3x3.bn.running_var", "base.layer2.block1.increase.conv.weight", "base.layer2.block1.increase.bn.weight", "base.layer2.block1.increase.bn.bias", "base.layer2.block1.increase.bn.running_mean", "base.layer2.block1.increase.bn.running_var", "base.layer2.block1.shortcut.conv.weight", "base.layer2.block1.shortcut.bn.weight", "base.layer2.block1.shortcut.bn.bias", "base.layer2.block1.shortcut.bn.running_mean", 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"base.layer5.block1.increase.bn.running_var", "base.layer5.block1.shortcut.conv.weight", "base.layer5.block1.shortcut.bn.weight", "base.layer5.block1.shortcut.bn.bias", "base.layer5.block1.shortcut.bn.running_mean", "base.layer5.block1.shortcut.bn.running_var", "base.layer5.block2.reduce.conv.weight", "base.layer5.block2.reduce.bn.weight", "base.layer5.block2.reduce.bn.bias", "base.layer5.block2.reduce.bn.running_mean", "base.layer5.block2.reduce.bn.running_var", "base.layer5.block2.conv3x3.conv.weight", "base.layer5.block2.conv3x3.bn.weight", "base.layer5.block2.conv3x3.bn.bias", "base.layer5.block2.conv3x3.bn.running_mean", "base.layer5.block2.conv3x3.bn.running_var", "base.layer5.block2.increase.conv.weight", "base.layer5.block2.increase.bn.weight", "base.layer5.block2.increase.bn.bias", "base.layer5.block2.increase.bn.running_mean", "base.layer5.block2.increase.bn.running_var", "base.layer5.block3.reduce.conv.weight", "base.layer5.block3.reduce.bn.weight", 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"layer5.block3.conv3x3.bn.bias", "layer5.block3.increase.conv.weight", "layer5.block3.increase.bn.running_mean", "layer5.block3.increase.bn.running_var", "layer5.block3.increase.bn.num_batches_tracked", "layer5.block3.increase.bn.weight", "layer5.block3.increase.bn.bias", "fc.weight", "fc.bias".
is there some way how to fix this?
Thanks.
The command you run generates an init model trained on 91-class COCO, not COCO-Stuff.
Please specify the appropriate combination of a config file and a model file.
| Dataset | Configuration | Model |
|---|---|---|
| 91-class COCO | coco.yaml |
deeplabv1_resnet101-coco.pth |
| COCO-Stuff 10k | cocostuff10k.yaml |
deeplabv2_resnet101_msc-cocostuff10k-20000.pth |
| COCO-Stuff 164k | cocostuff164k.yaml |
deeplabv2_resnet101_msc-cocostuff164k-100000.pth |
| Pascal VOC 2012 (+SBD) | voc12.yaml |
deeplabv2_resnet101_msc-vocaug-20000.pth |
Hi @kazuto1011,
thanks for the reply. I will try that out.
convert.py
line 246
model.load_state_dict(converted_state_dict, strict=False)