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auto updates (#6760)
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monai-bot authored Jul 24, 2023
1 parent 3410794 commit 28c9083
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Showing 5 changed files with 6 additions and 9 deletions.
5 changes: 2 additions & 3 deletions .github/workflows/docker.yml
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Expand Up @@ -85,12 +85,11 @@ jobs:
container:
image: docker://projectmonai/monai:latest
options: "--shm-size=4g --ipc=host"
runs-on: ubuntu-latest
runs-on: [self-hosted, linux, X64, docker]
steps:
- name: Import
run: |
export CUDA_VISIBLE_DEVICES=$(python -m tests.utils | tail -n 1)
echo $CUDA_VISIBLE_DEVICES
export CUDA_VISIBLE_DEVICES= # cpu-only
python -c 'import monai; monai.config.print_debug_info()'
cd /opt/monai
ls -al
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4 changes: 2 additions & 2 deletions monai/apps/deepgrow/transforms.py
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Expand Up @@ -441,8 +441,8 @@ def __call__(self, data):

if np.all(np.less(current_size, self.spatial_size)):
cropper = SpatialCrop(roi_center=center, roi_size=self.spatial_size)
box_start = np.array([s.start for s in cropper.slices]) # type: ignore
box_end = np.array([s.stop for s in cropper.slices]) # type: ignore
box_start = np.array([s.start for s in cropper.slices])
box_end = np.array([s.stop for s in cropper.slices])
else:
cropper = SpatialCrop(roi_start=box_start, roi_end=box_end)

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4 changes: 2 additions & 2 deletions monai/data/ultrasound_confidence_map.py
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Expand Up @@ -301,7 +301,7 @@ def confidence_estimation(self, img, seeds, labels, beta, gamma):
m[:, 0] = labels == 1

# Right-handside (-B^T*M)
rhs = -b @ m # type: ignore
rhs = -b @ m

# Solve linear system
x = self._solve_linear_system(lap, rhs)
Expand Down Expand Up @@ -334,7 +334,7 @@ def __call__(self, data: NDArray, sink_mask: NDArray | None = None) -> NDArray:

if self.mode == "RF":
# MATLAB hilbert applies the Hilbert transform to columns
data = np.abs(hilbert(data, axis=0)).astype("float64") # type: ignore
data = np.abs(hilbert(data, axis=0)).astype("float64")

seeds, labels = self.get_seed_and_labels(data, self.sink_mode, sink_mask)

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1 change: 0 additions & 1 deletion monai/transforms/intensity/array.py
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Expand Up @@ -39,7 +39,6 @@

skimage, _ = optional_import("skimage", "0.19.0", min_version)


__all__ = [
"RandGaussianNoise",
"RandRicianNoise",
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1 change: 0 additions & 1 deletion tests/test_ultrasound_confidence_map_transform.py
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Expand Up @@ -49,7 +49,6 @@
]
)


SINK_ALL_OUTPUT = np.array(
[
[1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0],
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