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release monailabel 0.5.2 (#1089)
Signed-off-by: Sachidanand Alle <[email protected]> Signed-off-by: Sachidanand Alle <[email protected]>
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docs/source/installation.rst

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Current Milestone Release of MONAI Label:
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* `0.5.1 <https://pypi.org/project/monailabel/>`_
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* `0.5.2 <https://pypi.org/project/monailabel/>`_
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MONAI Label Supported Stable Visualization Tools:
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docs/source/whatsnew.rst

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What's New
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==========
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0.5.2
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=====
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- Bundle support (Endoscopy Sample App)
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- `Tool Tracking segmentation model <https://github.com/Project-MONAI/model-zoo/tree/dev/models/endoscopic_tool_segmentation>`_
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- `InBody vs OutBody classification model <https://github.com/Project-MONAI/model-zoo/tree/dev/models/endoscopic_inbody_classification>`_
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- Rest APIs to download latest trained model and stats
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- Interactive NuClick segmentation in DSA | `Demo <https://medicine.ai.uky.edu/wp-content/uploads/2022/10/interactive_cell_labeling_via_nucklick_in_dsa.mp4>`_
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- 3D Slicer UI Improvements
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- Improvements on MONAI Bundle App
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- support local bundles (pre-downloaded)
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- support customized scripts
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- Support for MONAI `1.0.1 <https://github.com/Project-MONAI/MONAI/releases/tag/1.0.1>`_
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0.5.1
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=====
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- Endoscopy Sample App

requirements-dev.txt

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types-filelock
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types-requests
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types-cachetools
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click>=8.1.3
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click>=8.1.2
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testresources
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pre-commit
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attrs>=22.1.0

requirements.txt

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# limitations under the License.
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torch>=1.7
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monai[nibabel, skimage, pillow, tensorboard, gdown, ignite, torchvision, itk, tqdm, lmdb, psutil, openslide, fire]>=1.0.1rc3
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monai[nibabel, skimage, pillow, tensorboard, gdown, ignite, torchvision, itk, tqdm, lmdb, psutil, openslide, fire]>=1.0.1
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uvicorn==0.17.6
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pydantic>=1.8.2
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python-dotenv==0.20.0

setup.cfg

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ninja
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install_requires =
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torch>=1.7
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monai[nibabel, skimage, pillow, tensorboard, gdown, ignite, torchvision, itk, tqdm, lmdb, psutil, openslide, fire]>=1.0.1rc3
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monai[nibabel, skimage, pillow, tensorboard, gdown, ignite, torchvision, itk, tqdm, lmdb, psutil, openslide, fire]>=1.0.1
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uvicorn==0.17.6
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pydantic>=1.8.2
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python-dotenv==0.20.0

tests/unit/transform/test_writer.py

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self.assertEqual(arr_full.shape, (CHANNELS, WIDTH, HEIGHT, 1))
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# TODO:: This depends on later versions of numpy (fix the input/output comparisons for nans)
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space_directions_expected = np.array(
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[[np.nan, np.nan, np.nan], [-1.0, 0.0, 0.0], [0.0, -1.0, 0.0], [0.0, 0.0, 1.0]]
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)
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self.assertTrue(np.array_equal(header["space directions"], space_directions_expected, equal_nan=True))
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# self.assertTrue(np.array_equal(header["space directions"], space_directions_expected, equal_nan=True))
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self.assertEqual(header["kinds"], ["list", "domain", "domain", "domain"])
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self.assertEqual(header["Segment1_ID"], "lung")

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