Comments (3)
I think argparse
is a fine solution for now, though I'm not very experienced in testing them.
Can you make a list of the additional args you'd expect to see, with some possible values/ranges?
from deepcell-applications.
As discussed:
I think it would be nice to have an ouput_dir, and an optional output_filename. At a minimum, it saves the label_mask into the specified directory. If they have a preferred filename, this would allow them to specify that, to allow integrating with subsequent steps not require modifications
from deepcell-applications.
Nuclear_image: path to 2D single channel TIF file
Membrane_image: path to 2D single channel TIF file. Optional. If not provided, membrane channel input to network is blank
Output_dir: directory where segmentation masks are saved
Output_name: name of output file
compartment: either nuclear or whole_cell. Passed as argument to multiplexsegmentation application
from deepcell-applications.
Related Issues (19)
- Add example input/output image? HOT 1
- Update Dockerfile base image HOT 1
- Cache MultiplexSegmentation model weights in the docker image. HOT 1
- AttributeError: module 'deepcell.utils' has no attribute 'get_image' HOT 3
- Add support for multi-channel .ome.tiff HOT 2
- Improvements to the application HOT 1
- Integration with MCMICRO HOT 23
- Batch processing HOT 3
- --compartment argument mismatch HOT 3
- Problems reading OME-TIFF files with LZW compression HOT 8
- generated mask appears black in windows photo viewer HOT 7
- Memory usage with large .ome.tiff images HOT 4
- Changes to membrane-image definition HOT 8
- A Docker image without ENTRYPOINT HOT 3
- Adding conda package for mesmer HOT 2
- Error when running mesmer on multi-channel image HOT 1
- Remove Entrypoint from Docker image HOT 3
- Encountered error <COMPRESSION.LZW: 5> requires the 'imagecodecs' package
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from deepcell-applications.