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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.

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TissueMaskModel

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)

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tile_spec

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

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process

Processes a single RGB tile into a binary mask.
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ModelRequest
required
Model request containing the RGB tile.
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ModelResponse
Model response containing the binary mask.