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backseason / PoolNet

Code for our CVPR 2019 paper "A Simple Pooling-Based Design for Real-Time Salient Object Detection"
MIT License
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Issue in reusing the pretrained models #76

Closed HarshitSinghChhabra closed 3 years ago

HarshitSinghChhabra commented 3 years ago

Hi, a very great project. When I try to use "PoolNet-ResNet50 w/ edge model" provided in the drive to test on my own data using -e mode by properly adding the files and making a .lst file, it shows incompatible shape in checkpoint and current model. Pasting the Error message - RuntimeError: Error(s) in loading state_dict for PoolNet: Unexpected key(s) in state_dict: "block.0.block_in1.0.weight", "block.0.block_in2.0.weight", "block.0.block_mid1.0.0.weight", "block.0.block_mid1.0.1.weight", "block.0.block_mid2.0.0.weight", "block.0.block_mid2.0.1.weight", "block.0.block_out.0.weight", "block.1.block_in1.0.weight", "block.1.block_in2.0.weight", "block.1.block_mid1.0.0.weight", "block.1.block_mid1.0.1.weight", "block.1.block_mid2.0.0.weight", "block.1.block_mid2.0.1.weight", "block.1.block_out.0.weight", "block.2.block_in1.0.weight", "block.2.block_in2.0.weight", "block.2.block_mid1.0.0.weight", "block.2.block_mid1.0.1.weight", "block.2.block_mid2.0.0.weight", "block.2.block_mid2.0.1.weight", "block.2.block_out.0.weight", "block.3.block_in1.0.weight", "block.3.block_in2.0.weight", "block.3.block_mid1.0.0.weight", "block.3.block_mid1.0.1.weight", "block.3.block_mid2.0.0.weight", "block.3.block_mid2.0.1.weight", "block.3.block_out.0.weight", "fuse.trans.0.weight", "fuse.trans.0.bias", "fuse.trans.1.weight", "fuse.trans.1.bias", "fuse.trans.2.weight", "fuse.trans.2.bias", "fuse.trans.3.weight", "fuse.trans.3.bias", "fuse.fuse.weight", "fuse.fuse.bias", "edgeinfo.trans.0.weight", "edgeinfo.trans.2.weight", "edgeinfo.trans.4.weight", "edgeinfo.trans.6.weight".

size mismatch for score.score.weight: copying a param with shape torch.Size([1, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([1, 128, 1, 1]).

Can you please tell why this is happening. Thanks

HarshitSinghChhabra commented 3 years ago

Issue Resolved. It was due to GPU specification on Colab

malcolmagius19 commented 2 years ago

Hi, can I ask how you solved the issue if you remember please? Did you have to run the model on your machine locally or were you able to run it through Colab still? Thanks