Merge branch 'main' into set_3d_checkbox

.github/workflows/test_and_deploy.yml

@@ -17,27 +17,26 @@ on:
       - main
   workflow_dispatch:
 
+concurrency:
+  group: ${{ github.workflow }}-${{ github.ref }}
+  cancel-in-progress: true
+
 jobs:
   test:
     name: ${{ matrix.platform }} ${{ matrix.python-version }}
     runs-on: ${{ matrix.platform }}
-    defaults:
-      run:
-        shell: bash -l {0}
     strategy:
       fail-fast: false
       matrix:
-        platform: [ubuntu-latest]#, macos-latest, windows-latest]
-        python-version: ["3.9", "3.10", "3.11"]
-        backend: [pyqt5]
+        platform: [ubuntu-latest, macos-latest, windows-latest]
+        python-version: ["3.9", "3.10", "3.11", "3.12"]
 
     steps:
       - uses: actions/checkout@v4
-      - uses: conda-incubator/setup-miniconda@v2
+
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v5
         with:
-          miniconda-version: "latest"
-          channels: conda-forge
-          channel-priority: strict
           python-version: ${{ matrix.python-version }}
 
       - uses: tlambert03/setup-qt-libs@v1
@@ -51,18 +50,14 @@ jobs:
       - name: Install dependencies
         run: |
           python -m pip install --upgrade pip
-          python -m pip install --upgrade setuptools tox tox-conda tox-gh-actions
+          python -m pip install --upgrade setuptools tox tox-gh-actions
 
       - name: Test with tox
-        uses: aganders3/headless-gui@v1.2
+        uses: aganders3/headless-gui@v2
         with:
-          shell: bash -el {0}
           run: python -m tox
         env:
           PLATFORM: ${{ matrix.platform }}
-          PYTHON: ${{ matrix.python-version }}
-          PYVISTA_OFF_SCREEN: True
-          BACKEND: ${{ matrix.backend }}
 
       - name: Codecov
         uses: codecov/codecov-action@v3

cellpose_napari/_dock_widget.py

@@ -73,6 +73,8 @@ def run_cellpose(image, model_type, custom_model, channels, channel_axis, diamet
             CP = models.CellposeModel(pretrained_model=custom_model, gpu=True)
         else:
             CP = models.CellposeModel(model_type=model_type, gpu=True)
+
+        print(cellprob_threshold, flow_threshold)
         masks, flows_orig, _ = CP.eval(image, 
                                     channels=channels, 
                                     channel_axis=channel_axis,
@@ -105,22 +107,16 @@ def compute_diameter(image, channels, model_type):
 
     @thread_worker 
     def compute_masks(masks_orig, flows_orig, cellprob_threshold, flow_threshold):
-        import cv2
-        from cellpose.utils import fill_holes_and_remove_small_masks
-        from cellpose.dynamics import get_masks
-        from cellpose.transforms import resize_image
+        from cellpose.dynamics import resize_and_compute_masks
 
-        #print(flows_orig[3].shape, flows_orig[2].shape, masks_orig.shape)
         flow_threshold = (31.0 - flow_threshold) / 10.
         if flow_threshold==0.0:
             flow_threshold = 0.0
             logger.debug('flow_threshold=0 => no masks thrown out due to model mismatch')
         logger.debug(f'computing masks with cellprob_threshold={cellprob_threshold}, flow_threshold={flow_threshold}')
-        maski = get_masks(flows_orig[3].copy(), iscell=(flows_orig[2] > cellprob_threshold),
-                        flows=flows_orig[1], threshold=flow_threshold*(masks_orig.ndim<3))
-        maski = fill_holes_and_remove_small_masks(maski)
-        maski = resize_image(maski, masks_orig.shape[-2], masks_orig.shape[-1],
-                                        interpolation=cv2.INTER_NEAREST)
+        maski, _ = resize_and_compute_masks(flows_orig[1], cellprob=flows_orig[2], cellprob_threshold=cellprob_threshold,
+                        flow_threshold=flow_threshold, resize=(masks_orig.shape[-2], masks_orig.shape[-1]))
+
         return maski 
 
     @magicgui(

tests/test_plugin.py

@@ -1,14 +1,11 @@
 import os
-import sys
 from pathlib import Path
 from math import isclose
 from typing import Callable
 
-import cellpose_napari
 import napari
 import pytest
 import torch # for ubuntu tests on CI, see https://github.com/pytorch/pytorch/issues/75912
-from cellpose_napari._dock_widget import widget_wrapper
 
 # this is your plugin name declared in your napari.plugins entry point
 PLUGIN_NAME = "cellpose-napari"
@@ -17,6 +14,14 @@
 
 SAMPLE = Path(__file__).parent / "sample.tif"
 
+@pytest.fixture(autouse=True)
+def patch_mps_on_CI(monkeypatch):
+    # https://github.com/actions/runner-images/issues/9918
+    if os.getenv('CI'):
+        monkeypatch.setattr("torch.backends.mps.is_available", lambda: False)
+        monkeypatch.setattr("cellpose.core.assign_device", lambda **kwargs: (torch.device("cpu"), False))
+
+
 @pytest.fixture
 def viewer_widget(make_napari_viewer: Callable[..., napari.Viewer]):
     viewer = make_napari_viewer()
@@ -32,11 +37,7 @@ def test_basic_function(qtbot, viewer_widget):
     viewer.open_sample(PLUGIN_NAME, 'rgb_2D')
     viewer.layers[0].data = viewer.layers[0].data[0:128, 0:128]
 
-    #if os.getenv("CI"):
-    #    return
-        # actually running cellpose like this takes too long and always timesout on CI
-        # need to figure out better strategy
-
+    widget.model_type.value = "cyto3"
     widget()  # run segmentation with all default parameters
 
     def check_widget():
@@ -47,10 +48,9 @@ def check_widget():
     assert len(viewer.layers) == 5
     assert "cp_masks" in viewer.layers[-1].name
 
-    # check that the segmentation was proper, should yield 11 cells
+    # check that the segmentation was proper, cyto3 yields 10 cells
     assert viewer.layers[-1].data.max() == 10
 
-@pytest.mark.skipif(sys.platform.startswith('linux'), reason="ubuntu stalls with two cellpose tests")
 def test_compute_diameter(qtbot, viewer_widget):
     viewer, widget = viewer_widget
     viewer.open_sample(PLUGIN_NAME, 'rgb_2D')
@@ -63,9 +63,10 @@ def test_compute_diameter(qtbot, viewer_widget):
     with qtbot.waitSignal(widget.diameter.changed, timeout=60_000) as blocker:
         widget.compute_diameter_button.changed(None)
 
-    assert isclose(float(widget.diameter.value), 24.1, abs_tol=10**-1)
+    # local on macOS with MPS, get 20.37, with CPU-only it's 20.83, same as CI
+    # so choosing a target that works for both
+    assert isclose(float(widget.diameter.value), 20.6, abs_tol=0.3)
 
-@pytest.mark.skipif(sys.platform.startswith('linux'), reason="ubuntu stalls with >1 cellpose tests")
 def test_3D_segmentation(qtbot,  viewer_widget):
     viewer, widget = viewer_widget
     # by default the widget loads with `process_3D` set to False
@@ -75,6 +76,7 @@ def test_3D_segmentation(qtbot,  viewer_widget):
     # check that 3D processing is set correctly after opening a 3D image
     assert widget.process_3D.value == True
 
+    widget.model_type.value = "cyto3"
     widget()  # run segmentation with all default parameters
 
     def check_widget():
@@ -85,5 +87,5 @@ def check_widget():
     assert len(viewer.layers) == 5
     assert "cp_masks" in viewer.layers[-1].name
 
-    # check that the segmentation was proper, should yield 7 cells
-    assert viewer.layers[-1].data.max() == 7
+    # check that the segmentation was proper, `cyto3` should yield 9 cells
+    assert viewer.layers[-1].data.max() == 9

tox.ini

@@ -1,14 +1,15 @@
 # For more information about tox, see https://tox.readthedocs.io/en/latest/
 [tox]
-envlist = py{38,39,310}-{linux,macos,windows}
+envlist = py{39,310,311,312}-{linux,macos,windows}
 isolated_build=true
 toxworkdir = /tmp/.tox
 
 [gh-actions]
 python =
-    3.8: py38
     3.9: py39
     3.10: py310
+    3.11: py311
+    3.12: py312
 
 [gh-actions:env]
 PLATFORM =