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🐛 Fix sccnn Model #970

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Merged
merged 1 commit into from
Nov 14, 2025
Merged

🐛 Fix sccnn Model #970

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8 changes: 5 additions & 3 deletions tests/models/test_arch_sccnn.py
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Original file line number Diff line number Diff line change
Expand Up @@ -39,20 +39,22 @@ def test_functionality(remote_sample: Callable) -> None:
units="mpp",
coord_space="resolution",
)
batch = torch.from_numpy(patch)[None]
model = _load_sccnn(name="sccnn-crchisto")
patch = model.preproc(patch)
batch = torch.from_numpy(patch)[None]
output = model.infer_batch(
model,
batch,
device=select_device(on_gpu=env_detection.has_gpu()),
)
output = model.postproc(output[0])
assert np.all(output == [[8, 7]])
np.testing.assert_array_equal(output, np.array([[8, 7]]))

model = _load_sccnn(name="sccnn-conic")
output = model.infer_batch(
model,
batch,
device=select_device(on_gpu=env_detection.has_gpu()),
)
output = model.postproc(output[0])
assert np.all(output == [[7, 8]])
np.testing.assert_array_equal(output, np.array([[7, 8]]))
12 changes: 6 additions & 6 deletions tiatoolbox/data/pretrained_model.yaml
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Expand Up @@ -863,14 +863,14 @@ sccnn-crchisto:
class: semantic_segmentor.IOSegmentorConfig
kwargs:
input_resolutions:
- { "units": "mpp", "resolution": 0.5 }
- { "units": "mpp", "resolution": 0.25 }
output_resolutions:
- { "units": "mpp", "resolution": 0.5 }
- { "units": "mpp", "resolution": 0.25 }
tile_shape: [ 2048, 2048 ]
patch_input_shape: [ 31, 31 ]
patch_output_shape: [ 13, 13 ]
stride_shape: [ 8, 8 ]
save_resolution: { 'units': 'mpp', 'resolution': 0.5 }
save_resolution: { 'units': 'mpp', 'resolution': 0.25 }

sccnn-conic:
hf_repo_id: TIACentre/TIAToolbox_pretrained_weights
Expand All @@ -886,14 +886,14 @@ sccnn-conic:
class: semantic_segmentor.IOSegmentorConfig
kwargs:
input_resolutions:
- { "units": "mpp", "resolution": 0.5 }
- { "units": "mpp", "resolution": 0.25 }
output_resolutions:
- { "units": "mpp", "resolution": 0.5 }
- { "units": "mpp", "resolution": 0.25 }
tile_shape: [ 2048, 2048 ]
patch_input_shape: [ 31, 31 ]
patch_output_shape: [ 13, 13 ]
stride_shape: [ 8, 8 ]
save_resolution: { 'units': 'mpp', 'resolution': 0.5 }
save_resolution: { 'units': 'mpp', 'resolution': 0.25 }

nuclick_original-pannuke:
hf_repo_id: TIACentre/TIAToolbox_pretrained_weights
Expand Down
3 changes: 1 addition & 2 deletions tiatoolbox/models/architecture/sccnn.py
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Expand Up @@ -239,7 +239,7 @@ def spatially_constrained_layer2(
return sc2 * out_map_threshold

@staticmethod
def preproc(image: torch.Tensor) -> torch.Tensor:
def preproc(image: np.ndarray) -> np.ndarray:
"""Transforming network input to desired format.

This method is model and dataset specific, meaning that it can be replaced by
Expand Down Expand Up @@ -309,7 +309,6 @@ def spatially_constrained_layer1(
sigmoid2 = sigmoid[:, 2:3, :, :]
return sigmoid0, sigmoid1, sigmoid2

input_tensor = self.preproc(input_tensor)
l1 = self.layer["l1"]["conv1"](input_tensor)
p1 = self.layer["pool1"](l1)
l2 = self.layer["l2"]["conv1"](p1)
Expand Down
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