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Update Documentation #220

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Oct 3, 2023
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Update Documentation #220

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4 changes: 2 additions & 2 deletions doc/finetuned_models.md
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Expand Up @@ -26,8 +26,8 @@ See for example the [2d annotator example](https://github.com/computational-cell

As a rule of thumb:
- Use the `_lm` models for segmenting cells or nuclei in light microscopy.
- Use the `_em` models for segmenting ceells or neurites in electron microscopy.
- Note that this model does not work well for segmenting mitochondria or other organelles becuase it is biased towards segmenting the full cell / cellular compartment.
- Use the `_em` models for segmenting cells or neurites in electron microscopy.
- Note that this model does not work well for segmenting mitochondria or other organelles because it is biased towards segmenting the full cell / cellular compartment.
- For other cases use the default models.

See also the figures above for examples where the finetuned models work better than the vanilla models.
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4 changes: 2 additions & 2 deletions doc/python_library.md
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Expand Up @@ -6,8 +6,8 @@ import micro_sam
```

The library
- implements function to apply Segment Anything to 2d and 3d data more conviently in `micro_sam.prompt_based_segmentation`.
- provides more and imporoved automatic instance segmentation functionality in `micro_sam.instance_segmentation`.
- implements function to apply Segment Anything to 2d and 3d data more conveniently in `micro_sam.prompt_based_segmentation`.
- provides more and improved automatic instance segmentation functionality in `micro_sam.instance_segmentation`.
- implements training functionality that can be used for finetuning on your own data in `micro_sam.training`.
- provides functionality for quantitative and qualitative evaluation of Segment Anything models in `micro_sam.evaluation`.

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