usage: run.py [-h] [--src-is-dir] [--dst-bucket DST_BUCKET] [--verbose] [--remote] [--clml-proj CLML_PROJ] [--clml-task-name CLML_TASK_NAME] [--clml-task-type CLML_TASK_TYPE]
              [--docker-img DOCKER_IMG] [--queue QUEUE]
              src_bucket src_path dst_path

positional arguments:
  src_bucket            Source bucket
  src_path              Source path
  dst_path              Destination path

optional arguments:
  -h, --help            show this help message and exit
  --src-is-dir          Flag to indicate that given src path is a directory. Will iteratively extract any files in it ending with .zip or .tar.
  --dst-bucket DST_BUCKET
                        Destination bucket (optional), will default to Source bucket.
  --verbose             print out current upload filename as it progresses
  --remote              use clearml to remotely run job
  --clml-proj CLML_PROJ
                        ClearML Project Name
  --clml-task-name CLML_TASK_NAME
                        ClearML Task Name
  --clml-task-type CLML_TASK_TYPE
                        ClearML Task Type, e.g. training, testing, inference, etc
  --docker-img DOCKER_IMG
                        Base docker image to pull for ClearML remote execution
  --queue QUEUE         ClearML remote execution queue

python run.py my-bucket dataset/coco/images.tar dataset/coco/ --verbose --remote --clml-proj coco --clml-task-name coco_extraction --docker-img ubuntu/20.04 --queue 1xGPU