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trying to write test
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‎MANIFEST.in‎

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include LICENSE
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include README.md
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include requirements.txt
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recursive-exclude * __pycache__
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recursive-exclude * *.py[co]

‎dev.requirements.txt‎

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black
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pytest
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pytest-qt
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tox
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sphinx
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sphinx-autodoc-typehints
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sphinx-rtd-theme
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sphinx-rtd-theme

‎docs/res/loader_module_guide.rst‎

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Using these, you can check your labels, correct them, save them and keep track of which slices have been checked or not.
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Source code :
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Source code
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-------------------------------------------------
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* :doc:`plugin_loader`

‎napari_cellseg_annotator/_tests/test_dock_widget.py‎

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from napari_cellseg_annotator import ExampleQWidget, example_magic_widget
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import numpy as np
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# make_napari_viewer is a pytest fixture that returns a napari viewer object
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# capsys is a pytest fixture that captures stdout and stderr output streams
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def test_example_q_widget(make_napari_viewer, capsys):
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# make viewer and add an image layer using our fixture
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viewer = make_napari_viewer()
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viewer.add_image(np.random.random((100, 100)))
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# create our widget, passing in the viewer
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my_widget = ExampleQWidget(viewer)
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# call our widget method
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my_widget._on_click()
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# read captured output and check that it's as we expected
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captured = capsys.readouterr()
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assert captured.out == "napari has 1 layers\n"
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def test_example_magic_widget(make_napari_viewer, capsys):
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viewer = make_napari_viewer()
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layer = viewer.add_image(np.random.random((100, 100)))
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# this time, our widget will be a MagicFactory or FunctionGui instance
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my_widget = example_magic_widget()
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# if we "call" this object, it'll execute our function
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my_widget(viewer.layers[0])
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# read captured output and check that it's as we expected
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captured = capsys.readouterr()
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assert captured.out == f"you have selected {layer}\n"
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# from napari_cellseg_annotator import ExampleQWidget, example_magic_widget
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# import numpy as np
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#
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# # make_napari_viewer is a pytest fixture that returns a napari viewer object
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# # capsys is a pytest fixture that captures stdout and stderr output streams
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# def test_example_q_widget(make_napari_viewer, capsys):
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# # make viewer and add an image layer using our fixture
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# viewer = make_napari_viewer()
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# viewer.add_image(np.random.random((100, 100)))
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#
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# # create our widget, passing in the viewer
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# my_widget = ExampleQWidget(viewer)
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#
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# # call our widget method
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# my_widget._on_click()
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#
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# # read captured output and check that it's as we expected
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# captured = capsys.readouterr()
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# assert captured.out == "napari has 1 layers\n"
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#
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#
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# def test_example_magic_widget(make_napari_viewer, capsys):
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# viewer = make_napari_viewer()
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# layer = viewer.add_image(np.random.random((100, 100)))
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#
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# # this time, our widget will be a MagicFactory or FunctionGui instance
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# my_widget = example_magic_widget()
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#
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# # if we "call" this object, it'll execute our function
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# my_widget(viewer.layers[0])
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#
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# # read captured output and check that it's as we expected
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# captured = capsys.readouterr()
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# assert captured.out == f"you have selected {layer}\n"

‎napari_cellseg_annotator/_tests/test_loader.py‎

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from napari_cellseg_annotator.plugin_loader import Loader
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def test_loader(make_napari_viewer) :
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viewer = make_napari_viewer()
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widget = Loader(viewer)
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widget.show_dialog_mod()

‎napari_cellseg_annotator/_tests/test_widget.py‎

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from napari_cellseg_annotator import ExampleQWidget, example_magic_widget
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import numpy as np
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# make_napari_viewer is a pytest fixture that returns a napari viewer object
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# capsys is a pytest fixture that captures stdout and stderr output streams
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def test_example_q_widget(make_napari_viewer, capsys):
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# make viewer and add an image layer using our fixture
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viewer = make_napari_viewer()
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viewer.add_image(np.random.random((100, 100)))
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# create our widget, passing in the viewer
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my_widget = ExampleQWidget(viewer)
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# call our widget method
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my_widget._on_click()
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# read captured output and check that it's as we expected
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captured = capsys.readouterr()
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assert captured.out == "napari has 1 layers\n"
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def test_example_magic_widget(make_napari_viewer, capsys):
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viewer = make_napari_viewer()
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layer = viewer.add_image(np.random.random((100, 100)))
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# this time, our widget will be a MagicFactory or FunctionGui instance
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my_widget = example_magic_widget()
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# if we "call" this object, it'll execute our function
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my_widget(viewer.layers[0])
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# read captured output and check that it's as we expected
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captured = capsys.readouterr()
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assert captured.out == f"you have selected {layer}\n"
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# from napari_cellseg_annotator import ExampleQWidget, example_magic_widget
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# import numpy as np
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#
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# # make_napari_viewer is a pytest fixture that returns a napari viewer object
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# # capsys is a pytest fixture that captures stdout and stderr output streams
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# def test_example_q_widget(make_napari_viewer, capsys):
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# # make viewer and add an image layer using our fixture
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# viewer = make_napari_viewer()
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# viewer.add_image(np.random.random((100, 100)))
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#
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# # create our widget, passing in the viewer
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# my_widget = ExampleQWidget(viewer)
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#
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# # call our widget method
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# my_widget._on_click()
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#
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# # read captured output and check that it's as we expected
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# captured = capsys.readouterr()
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# assert captured.out == "napari has 1 layers\n"
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#
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#
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# def test_example_magic_widget(make_napari_viewer, capsys):
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# viewer = make_napari_viewer()
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# layer = viewer.add_image(np.random.random((100, 100)))
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#
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# # this time, our widget will be a MagicFactory or FunctionGui instance
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# my_widget = example_magic_widget()
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#
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# # if we "call" this object, it'll execute our function
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# my_widget(viewer.layers[0])
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#
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# # read captured output and check that it's as we expected
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# captured = capsys.readouterr()
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# assert captured.out == f"you have selected {layer}\n"

‎napari_cellseg_annotator/conftest.py‎

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‎napari_cellseg_annotator/napari.yaml‎

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contributions:
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commands:
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- id: napari-cellseg-annotator.load
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title: Create Loader
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title: Create review loader
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python_name: napari_cellseg_annotator.plugins:Loader
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# - id: napari-cellseg-annotator.train
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python_name: napari_cellseg_annotator.plugins:Helper
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widgets:
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- command: napari-cellseg-annotator.load
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display_name: Loader
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display_name: Review loader
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# - command: napari-cellseg-annotator.train
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# display_name: Trainer

‎napari_cellseg_annotator/plugin_loader.py‎

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QPushButton,
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QSizePolicy,
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QLabel,
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QFileDialog,
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QComboBox,
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QLineEdit,
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QCheckBox,
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def __init__(self, viewer: "napari.viewer.Viewer", parent=None):
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"""Creates a Loader plugin with several buttons :
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Open file prompt to select volumes directory
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* Open file prompt to select volumes directory
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Open file prompt to select labels directory
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* Open file prompt to select labels directory
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A dropdown menu with a choice of png or tif filetypes
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* A dropdown menu with a choice of png or tif filetypes
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A checkbox if you want to create a new status csv for the dataset
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* A checkbox if you want to create a new status csv for the dataset
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A button to launch the review process (see :doc:`launch_review`)
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* A button to launch the review process (see :doc:`launch_review`)
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"""
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super().__init__(parent)

‎tox.ini‎

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windows: win32
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passenv =
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CI
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PYTHONPATH
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GITHUB_ACTIONS
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DISPLAY XAUTHORITY
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NUMPY_EXPERIMENTAL_ARRAY_FUNCTION
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PYVISTA_OFF_SCREEN
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deps =
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deps =
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; -r{toxinidir}\requirements.txt
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pytest # https://docs.pytest.org/en/latest/contents.html
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pytest-cov # https://pytest-cov.readthedocs.io/en/latest/
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# you can remove these if you don't use them
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pytest-qt
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qtpy
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pyqt5
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opencv-python
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commands = pytest -v --color=yes --cov=napari_cellseg_annotator --cov-report=xml

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