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Transferring to Semantic Segmentation with MMSegmentation

For semantic segmentation task on ADE20K, we use MMSegmentation implementations. First, make sure you have installed MIM, which is also a project of OpenMMLab.

pip install openmim
mim install mmsegmentation

Besides, please refer to MMSegmentation for installation and data preparation.

Train

After installation, you can run MMSeg with simple command.

bash seg_mmsegmentation/mim_dist_train.sh ${CONFIG} ${PRETRAIN} ${GPUS}

Remarks:

  • CONFIG: Use config files under configs/benchmarks/mmsegmentation/ or write your own config files
  • PRETRAIN: the pre-trained model file (the backbone parameters only).
  • ${GPUS}: The number of GPUs that you want to use to train. We adopt 4 GPUs for segmentation tasks by default.

Test

After training, you can also run the command below to test your model.

bash seg_mmsegmentation/mim_dist_test.sh ${CONFIG} ${CHECKPOINT} ${GPUS}

Remarks:

  • ${CHECKPOINT}: The trained segmentation model that you want to test.

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