• Pick a model and its config file from. For example, configs/ade20k/swin/oneformer_swin_large_IN21k_384_bs16_160k.yaml.
• We provide demo.py that is able to demo builtin configs.
• You need to specify the task token value during inference, The outputs will be saved accordingly in the specified OUTPUT_DIR:
  • panoptic: Panoptic, Semantic and Instance Predictions when the value of task token is panoptic.
  • instance: Instance Predictions when the value of task token is instance.
  • semantic: Semantic Predictions when the value of task token is semantic.

  • Note: You can change the outputs to be saved on line 60 in predictor.py.

export task=panoptic

python demo.py --config-file ../configs/ade20k/swin/oneformer_swin_large_bs16_160k.yaml \
  --input <path-to-images> \
  --output <output-path> \
  --task $task \
  --opts MODEL.IS_TRAIN False MODEL.IS_DEMO True MODEL.WEIGHTS <path-to-checkpoint>

For details of the command line arguments, see demo.py -h or look at its source code to understand its behavior.