bioptimus.preprocess.wsi.models.base

Abstract interface for tissue segmentation models. Defines the TissueMaskModel abstract base class used by tissue mask providers to process individual tile requests into binary segmentation masks.

TissueMaskModel

class TissueMaskModel(ABC)

Abstract interface for tissue segmentation models. Accepts a batch of fixed-size RGB tiles and returns a batch of binary masks. GPU-backed models can process the whole batch at once; CPU-only models (like Otsu) can iterate internally. The batch dimension is always the first axis:

Input: (B, H, W, 3) — uint8 RGB.
Output: (B, H, W) — uint8, values in {0, 1}.

Example:

class MyGPUModel(TissueMaskModel):
    def __init__(self, net):
        self.net = net

    def process(self, batch):
        tensor = torch.from_numpy(batch).permute(0, 3, 1, 2).float() / 255
        with torch.no_grad():
            logits = self.net(tensor.cuda())
        return (logits.squeeze(1).cpu().numpy() > 0.5).astype(np.uint8)

tile_spec

@property
@abstractmethod
def tile_spec() -> TileSpec | None

Returns the tile specification for this model, or None. Subclasses must implement this property. Return None for models that operate on arbitrary tile sizes.

process

@abstractmethod
def process(request: ModelRequest) -> ModelResponse

Processes a single RGB tile into a binary mask.

Model request containing the RGB tile.

Returns:

ModelResponse - Model response containing the binary mask.

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TissueMaskModel

tile_spec

process

​TissueMaskModel

​tile_spec

​process

TissueMaskModel

tile_spec

process