Oguzhan Gencoglu
Oguzhan Gencoglu
@qubvel They have semantic segmentation results in their readme: https://github.com/tue-mps/eomt?tab=readme-ov-file#semantic-segmentation
Thanks for the swift reply.
I get this from my `uv sync`: ``` × No solution found when resolving dependencies for split (python_full_version == '3.12.10' and sys_platform == 'darwin'): ╰─▶ Because monai==1.5.0 depends on torch>=2.4.1,=2.4.1,
Can we fill the regions with random noise (pixel-level) instead of a value? From the documentation it seems like it just accepts a scalar value to fill in.
Any updates?
As a side topic, ss there a way to - configure a model to synthesize different responses to give the final response - make models judge each others' responses and...
Here: - https://obliquetree.readthedocs.io/en/latest/ - https://github.com/sametcopur/obliquetree