Install dependencies for display testing

.github/workflows/continuous-integration.yml

@@ -21,7 +21,7 @@ jobs:
     env:
       OS: ${{ matrix.os }}
       PYTHON: ${{ matrix.python-version }}
-
+      DISPLAY: ':99.0'
     steps:
     - uses: actions/checkout@main
     - name: Set up Python ${{ matrix.python-version }}
@@ -30,19 +30,26 @@ jobs:
         python-version: ${{ matrix.python-version }}
     - name: Install dependencies
       run: |
+        sudo apt-get install --no-install-recommends libyaml-dev libegl1-mesa libxkbcommon-x11-0 libxcb-icccm4 libxcb-image0 libxcb-keysyms1 libxcb-randr0 libxcb-render-util0 libxcb-xinerama0 libxcb-shape0 libxcb-cursor0 xserver-xephyr xvfb
         python -m pip install --upgrade pip
-        pip install flake8 pytest pytest-cov ipython
+        pip install flake8 pytest pytest-cov pytest-qt pytest-xvfb ipython anyio
     - name: Lint with flake8
       run: |
         # stop the build if there are Python syntax errors or undefined names
         flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics
         # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide
         flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
-    - name: Test and generate coverage report
+    - uses: tlambert03/setup-qt-libs@v1
+    - name: Install plantcv-annotate
       # Run coverage analysis on pytest tests
       run: |
         pip install .
-        py.test --cov-report=xml --cov=./
+        pip uninstall -y opencv-python
+        pip install opencv-python-headless
+    - name: Tests
+      uses: aganders3/headless-gui@v2
+      with:
+        run: pytest --cov-report=xml --cov=./
     - name: Upload coverage to Deepsource
       uses: deepsourcelabs/test-coverage-action@master
       with:

plantcv/annotate/__init__.py

@@ -0,0 +1,5 @@
+from plantcv.annotate.napari_open import napari_open
+from plantcv.annotate.napari_classes import napari_classes
+
+__all__ = ["napari_open",
+           "napari_classes"]

plantcv/annotate/napari_classes.py

@@ -0,0 +1,28 @@
+# Get Napari Keys
+
+import re
+
+
+def napari_classes(viewer):
+    """
+    get names of napari keys
+    Inputs:
+    viewer  = napari viewer object
+    Returns:
+    classes  = napari class value names
+    :param viewer: napari.viewer.Viewer
+    :return labels: numpy.ndarray, list
+    """
+    keylist = list(viewer.layers)
+    keylist = ''.join(str(keylist))
+    keylist = keylist.split(',')
+
+    classes = []
+    for x in keylist:
+        if re.search('Image layer', x):
+            pass
+        else:
+            y = x.split(" ")
+            classes.append(y[3].strip("\'"))
+
+    return classes

plantcv/annotate/napari_open.py

@@ -0,0 +1,34 @@
+# Use Napari to Label
+
+import cv2
+import numpy as np
+from skimage.color import label2rgb
+
+
+def napari_open(img, viewer):
+    """
+    open img in napari and label classes
+    Inputs:
+    img  = img  (grayimg, rgbimg, or hyperspectral image array data e.g.
+    hyperspectraldata.array_data)
+    show = if show is True the viewer is launched. This opetion is useful for
+    running tests without triggering the viewer.
+    Returns:
+    viewer  = napari viewer object
+    :param img: numpy.ndarray
+    :return viewer: napari viewer object
+    """
+    shape = np.shape(img)
+    if len(shape) == 2:
+        colorful = label2rgb(img)
+        img = (255*colorful).astype(np.uint8)
+        img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+    if len(shape) == 3:
+        if shape[2] == 3:
+            img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+        if shape[2] > 3:
+            img = img.transpose(2, 0, 1)
+
+    viewer.add_image(img)
+
+    return viewer

pyproject.toml

@@ -11,6 +11,8 @@ dynamic = ["version"]
 dependencies = [
     "plantcv",
     "matplotlib",
+    "napari",
+    "PyQt5"
 ]
 requires-python = ">=3.6"
 authors = [
@@ -25,7 +27,11 @@ classifiers = [
     "License :: OSI Approved :: Mozilla Public License 2.0 (MPL 2.0)",
     "Intended Audience :: Science/Research",
 ]
-
+[project.optional-dependencies]
+test = [
+    "pytest",
+    "pytest-qt"
+]
 [project.urls]
 Homepage = "https://plantcv.org"
 Documentation = "https://plantcv.readthedocs.io"

tests/conftest.py

@@ -1,4 +1,30 @@
+import pytest
 import matplotlib
+import os
+
 
 # Disable plotting
 matplotlib.use("Template")
+
+
+class TestData:
+    def __init__(self):
+        """Initialize simple variables."""
+        # Test data directory
+        self.datadir = os.path.join(os.path.dirname(os.path.abspath(__file__)),
+                                    "testdata")
+        # RGB image
+        filename_rgb = "setaria_small_plant_rgb.png"
+        self.small_rgb_img = os.path.join(self.datadir, filename_rgb)
+        # Kmeans Clustered Gray image
+        filename_kmeans = "silphium_seed_labeled_example.png"
+        self.kmeans_seed_gray_img = os.path.join(self.datadir, filename_kmeans)
+        # Small Hyperspectral image
+        filename_hyper = "corn-kernel-hyperspectral.raw"
+        self.envi_sample_data = os.path.join(self.datadir, filename_hyper)
+
+
+@pytest.fixture(scope="session")
+def test_data():
+    """Test data object for the main PlantCV package."""
+    return TestData()

tests/test_annotate.py

@@ -1,7 +1,18 @@
-from plantcv import annotate as an
+import numpy as np
+from plantcv.annotate.napari_classes import napari_classes
 
 
-def test_annotate():
+def test_napari_classes(make_napari_viewer):
     """PlantCV Test"""
-    assert an.__name__ == "plantcv.annotate"
-
+    img = np.zeros((100, 100, 3), dtype=np.uint8)
+    viewer = make_napari_viewer(show=False)
+    viewer.add_image(img)
+    coor = [(25, 25), (50, 50)]
+    viewer.add_image(img)
+    viewer.add_points(np.array(coor), symbol="o", name="total",
+                      face_color="red", size=30)
+    viewer.add_points(np.array(coor), symbol="o", name="test",
+                      face_color="red", size=30)
+    keys = napari_classes(viewer)
+
+    assert keys == ['total', 'test']