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Bump to 0.2.1 + typos fixes
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README.md

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@@ -59,17 +59,17 @@ The strength of our approach is we can match supervised model performance with p
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## News
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**New version: v0.2.0post1**
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**New version: v0.2.1**
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- v0.2.0post1:
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- v0.2.1:
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- Updated plugin default behaviors across the board to be more readily applicable to demo data
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- Threshold value in inference is now automatically set by default according to performance on demo data on a per-model basis
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- Added a grid search utility to find best thresholds for supervised models
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- v0.2.0:
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- Changed project name to "napari_cellseg3d" to avoid setuptools deprecation
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- Small API changes for training/inference from a script
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- Some fixes to WandB integration ad csv saving after training
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- Some fixes to WandB integration and csv saving after training
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napari_cellseg3d/__init__.py

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"""napari-cellseg3d - napari plugin for cell segmentation."""
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__version__ = "0.2.0post1"
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__version__ = "0.2.1"

napari_cellseg3d/code_models/instance_segmentation.py

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@@ -418,15 +418,10 @@ def clear_small_objects(image, threshold, is_file_path=False):
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if is_file_path:
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image = imread(image)
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# print(threshold)
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labeled = label(image)
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result = remove_small_objects(labeled, threshold)
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# print(np.sum(labeled))
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# print(np.sum(result))
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if np.sum(labeled) == np.sum(result):
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print("Warning : no objects were removed")
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napari_cellseg3d/code_plugins/plugin_helper.py

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@@ -44,7 +44,7 @@ def __init__(self, viewer: "napari.viewer.Viewer"):
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self.logo_label.setToolTip("Open Github page")
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self.info_label = ui.make_label(
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f"You are using napari-cellseg3d v.{'0.2.0post1'}\n\n"
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f"You are using napari-cellseg3d v.{'0.2.1'}\n\n"
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f"Plugin for cell segmentation developed\n"
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f"by the Mathis Lab of Adaptive Motor Control\n\n"
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f"Code by :\nCyril Achard\nMaxime Vidal\nJessy Lauer\nMackenzie Mathis\n"

napari_cellseg3d/code_plugins/plugin_model_inference.py

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# Whenever a model is selected, set the default threshold from the model file
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model_name = self.model_choice.currentText()
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threshold = config.MODEL_LIST[model_name].default_threshold
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print(threshold)
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self.thresholding_slider.slider_value = threshold * 100
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def _build(self):

setup.cfg

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[metadata]
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name = napari_cellseg3d
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version = 0.2.0post1
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version = 0.2.1
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[options]
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packages = find:

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