w1oves / Rein

[CVPR 2024] Official implement of <Stronger, Fewer, & Superior: Harnessing Vision Foundation Models for Domain Generalized Semantic Segmentation>
https://zxwei.site/rein
GNU General Public License v3.0
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Error about demo.ipynb #19

Closed SuiyvSYC closed 6 months ago

SuiyvSYC commented 6 months ago

/home/XXX/moe_seg/moe_exp_seg/pytorch_seg/Rein/rein/models/backbones/dino_layers/swiglu_ffn.py:43: UserWarning: xFormers is available (SwiGLU) warnings.warn("xFormers is available (SwiGLU)") /home/XXX/moe_seg/moe_exp_seg/pytorch_seg/Rein/rein/models/backbones/dino_layers/attention.py:27: UserWarning: xFormers is available (Attention) warnings.warn("xFormers is available (Attention)") /home/XXX/moe_seg/moe_exp_seg/pytorch_seg/Rein/rein/models/backbones/dino_layers/block.py:33: UserWarning: xFormers is available (Block) warnings.warn("xFormers is available (Block)") Loads checkpoint by local backend from path: checkpoints/dinov2_segmentor.pth /home/XXX/anaconda3/envs/rein/lib/python3.11/site-packages/torch/functional.py:504: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at /opt/conda/conda-bld/pytorch_1682343970094/work/aten/src/ATen/native/TensorShape.cpp:3483.) return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] /home/XXX/anaconda3/envs/rein/lib/python3.11/site-packages/mmengine/visualization/visualizer.py:196: UserWarning: Failed to add <class 'mmengine.visualization.vis_backend.LocalVisBackend'>, please provide the save_dir argument. warnings.warn(f'Failed to add {vis_backend.class}, '

The code is no longer running at this stage and the model is successfully loaded onto the gpu

SuiyvSYC commented 6 months ago

My running environment: mmcv 2.1.0 https://github.com/open-mmlab/mmcv mmdet 3.3.0 https://github.com/open-mmlab/mmdetection mmengine 0.10.3 https://github.com/open-mmlab/mmengine mmpretrain 1.2.0 https://github.com/open-mmlab/mmpretrain mmsegmentation 1.2.2 https://github.com/open-mmlab/mmsegmentation Training and testing are running normally

SuiyvSYC commented 6 months ago

vis_img=show_result_pyplot(network,im_path,result,wait_time=1) there is something changed in this function,because ”wait_time“ param

wait_time (float): The interval of show (s). 0 is the special value that means "forever". Defaults to 0. so we can change it to solve the problem

w1oves commented 6 months ago

Ok, Thank you.