torch_staintools.functional package

Subpackages

• torch_staintools.functional.conversion package
  • Submodules
  • torch_staintools.functional.conversion.lab module
    • lab_to_rgb()
    • rgb_to_lab()
  • torch_staintools.functional.conversion.od module
    • od2rgb()
    • rgb2od()
  • Module contents
• torch_staintools.functional.optimization package
  • Submodules
  • torch_staintools.functional.optimization.dict_learning module
    • _ls_batch()
    • dict_evaluate()
    • dict_learning()
    • get_concentration_batch()
    • get_concentration_one_by_one()
    • get_concentrations()
    • get_concentrations_single()
    • lasso_loss()
    • sparse_encode()
    • update_dict()
    • update_dict_ridge()
  • torch_staintools.functional.optimization.solver module
    • _lipschitz_constant()
    • coord_descent()
    • ista()
  • torch_staintools.functional.optimization.sparse_util module
    • initialize_code()
    • ridge()
  • Module contents
• torch_staintools.functional.stain_extraction package
  • Submodules
  • torch_staintools.functional.stain_extraction.extractor module
    • BaseExtractor
      • BaseExtractor._abc_impl
      • BaseExtractor.get_partial()
      • BaseExtractor.get_stain_matrix_from_od()
      • BaseExtractor.normalize_matrix_rows()
  • torch_staintools.functional.stain_extraction.factory module
    • build_from_name()
  • torch_staintools.functional.stain_extraction.macenko module
    • MacenkoExtractor
      • MacenkoExtractor._abc_impl
      • MacenkoExtractor.angular_helper()
      • MacenkoExtractor.cov()
      • MacenkoExtractor.get_stain_matrix_from_od()
      • MacenkoExtractor.stain_matrix_helper()
  • torch_staintools.functional.stain_extraction.utils module
    • percentile()
  • torch_staintools.functional.stain_extraction.vahadane module
    • VahadaneExtractor
      • VahadaneExtractor._abc_impl
      • VahadaneExtractor.get_stain_matrix_from_od()
  • Module contents
• torch_staintools.functional.tissue_mask package
  • Module contents
    • TissueMaskException
    • get_tissue_mask()
    • get_tissue_mask_np()
• torch_staintools.functional.utility package
  • Submodules
  • torch_staintools.functional.utility.implementation module
    • default_device()
    • default_rng()
    • img_from_concentration()
    • nanstd()
    • transpose_trailing()
  • Module contents

Submodules

torch_staintools.functional.eps module

Add small eps terms to avoid NaN in certain arithmetics (e.g., division and exp)

torch_staintools.functional.eps.get_eps(img: Tensor | None = None) → Tensor

Get the eps based on the device input tensor.

Precision is defined by the global variable _eps_val.

Parameters:

img – If specified, then the output will be moved to the same device of the img.

Returns:

output eps as a tensor. It will be moved to the device of img if img is specified.

Module contents