Skip to main content
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.
​
request
ModelRequest
required
Model request containing the RGB tile.
​
returns
ModelResponse
Model response containing the binary mask.