diff --git a/.coveragerc b/.coveragerc
new file mode 100644
index 0000000..4c3586e
--- /dev/null
+++ b/.coveragerc
@@ -0,0 +1,4 @@
+[run]
+omit = 
+    config.py
+    config-3.py
diff --git a/.github/workflows/continuous-integration.yml b/.github/workflows/continuous-integration.yml
index e0904dc..f64c7e5 100644
--- a/.github/workflows/continuous-integration.yml
+++ b/.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 +30,27 @@ jobs:
         python-version: ${{ matrix.python-version }}
     - name: Install dependencies
       run: |
+        sudo apt-get update
+        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:
diff --git a/docs/Points.md b/docs/Points.md
index a1fd3a4..0d1d169 100644
--- a/docs/Points.md
+++ b/docs/Points.md
@@ -1,6 +1,6 @@
 ## Interactive Point Annotation Tool
 
-Using [Jupyter Notebooks](jupyter.md) it is possible to interactively click to collect coordinates from an image, which can be used in various downstream applications. Left click on the image to collect a point. Right click removes the
+Using [Jupyter Notebooks](https://plantcv.readthedocs.io/en/stable/jupyter/) it is possible to interactively click to collect coordinates from an image, which can be used in various downstream applications. Left click on the image to collect a point. Right click removes the
 closest collected point.
 
 **plantcv.annotate.Points**(*img, figsize=(12,6), label="dafault"*)
diff --git a/docs/img/documentation_images/napari_join_labels/1_labeled_mask.png b/docs/img/documentation_images/napari_join_labels/1_labeled_mask.png
new file mode 100644
index 0000000..f6df4db
Binary files /dev/null and b/docs/img/documentation_images/napari_join_labels/1_labeled_mask.png differ
diff --git a/docs/img/documentation_images/napari_label_classes/napari_label_classes.png b/docs/img/documentation_images/napari_label_classes/napari_label_classes.png
new file mode 100644
index 0000000..1b63380
Binary files /dev/null and b/docs/img/documentation_images/napari_label_classes/napari_label_classes.png differ
diff --git a/docs/img/documentation_images/napari_open/napari_open.png b/docs/img/documentation_images/napari_open/napari_open.png
new file mode 100644
index 0000000..523fe02
Binary files /dev/null and b/docs/img/documentation_images/napari_open/napari_open.png differ
diff --git a/docs/napari_classes.md b/docs/napari_classes.md
new file mode 100644
index 0000000..b98966f
--- /dev/null
+++ b/docs/napari_classes.md
@@ -0,0 +1,32 @@
+## Open Image with Napari
+
+Get class names from Napari Viewer Object.
+
+**plantcv.annotate.napari_classes**(*viewer*)
+
+**returns** list of napari classes
+
+- **Parameters:**
+    - viewer - Napari viewer object
+
+- **Context:**
+    - Get names of Napari classes. This is mainly an internal function but can be useful in other context.
+
+- **Example use:**
+    - Get names of Napari classes/labels. 
+
+
+```python
+import plantcv.plantcv as pcv 
+import plantcv.annotate as pcvan
+
+# Create an instance of the Points class
+img, path, name = pcv.readimage("./grayimg.png")
+
+viewer = pcvan.napari_label_classes(img=img, classes=['background', 'wing', 'seed'])
+
+classes = pcvan.napari_classes(viewer)
+
+```
+
+**Source Code:** [Here](https://github.com/danforthcenter/plantcv-annotate/blob/main/plantcv/annotate/napari_classes.py)
diff --git a/docs/napari_join_labels.md b/docs/napari_join_labels.md
new file mode 100644
index 0000000..b8cd44e
--- /dev/null
+++ b/docs/napari_join_labels.md
@@ -0,0 +1,45 @@
+## Join Labels with Napari
+
+This function joins classes with the same label. This function would be run after classes are labeled with napari_label_classes.
+
+**plantcv.annotate.napari_join_labels*(*img, viewer*)
+
+**returns** relabeled mask, dictionary of masks for each class
+
+- **Parameters:**
+    - img - image data (compatible with gray, RGB, and hyperspectral data. If data is hyperspecral it should be the array e.g. hyperspectral.array_data)
+    - viewer - viewer with labeled classes. If no points are selected for a class,
+        data without labels will default to this class when napari_join_labels
+        is run. If all classes have points labeled, any clusters not labeled
+        will default to the last class in the list if napari_join_labels is
+        run.
+
+- **Context:**
+    - This function would be run after labeling classes in Napari is complete. 
+
+- **Example use:**
+    - Joining classes labeled as the same, for example for joining classes from output of kmeans clustering
+
+
+```python
+import plantcv.plantcv as pcv 
+import plantcv.annotate as pcvan
+import napari
+
+# Create an instance of the Points class
+img, path, name = pcv.readimage("./grayimg.png")
+
+viewer = pcvan.napari_label_classes(img=img, ['background', 'wing','seed'])
+
+# Should open interactive napari viewer
+
+labeledmask, mask_dict = pcvan.napari_join_lables(img=img, viewer=viewer)
+
+```
+
+![Screenshot](img/documentation_images/napari_label_classes/napari_label_classes.png)
+
+![Screenshot](img/documentation_images/napari_join_labels/1_labeled_mask.png)
+
+
+**Source Code:** [Here](https://github.com/danforthcenter/plantcv-annotate/blob/main/plantcv/annotate/napari_label_classes.py)
diff --git a/docs/napari_label_classes.md b/docs/napari_label_classes.md
new file mode 100644
index 0000000..6b112af
--- /dev/null
+++ b/docs/napari_label_classes.md
@@ -0,0 +1,43 @@
+## Label Image with Napari
+
+This function opens an image in Napari and then defines a set of classes to label. A random shape label is assigned to each class. 
+Image can be annotated as long as viewer is open. 
+
+**plantcv.annotate.napari_label_classes*(*img, classes, show=True*)
+
+**returns** napari viewer object
+
+- **Parameters:**
+    - img - image data (compatible with gray, RGB, and hyperspectral data. If data is hyperspecral it should be the array e.g. hyperspectral.array_data)
+    - classes - list of classes to label. If no points are selected for a class,
+        data without labels will default to this class when napari_join_labels
+        is run. If all classes have points labeled, any clusters not labeled
+        will default to the last class in the list if napari_join_labels is
+        run.
+    - show - if show = True, viewer is launched. False setting is useful for test purposes.
+
+- **Context:**
+    - Adding class labels to images. Works best on an image that has objects segmented/classified with contours/clusters labeled with values (e.g. labeled mask, output of kmeans clustering).
+
+- **Example use:**
+    - Labeling output of kmeans clustering into classes. Labeling points.
+
+
+```python
+import plantcv.plantcv as pcv 
+import plantcv.annotate as pcvan
+import napari
+
+# Create an instance of the Points class
+img, path, name = pcv.readimage("./grayimg.png")
+
+viewer = pcvan.napari_label_classes(img=img, classes=['background', 'wing','seed'])
+
+# Should open interactive napari viewer
+
+```
+
+![Screenshot](img/documentation_images/napari_label_classes/napari_label_classes.png)
+
+
+**Source Code:** [Here](https://github.com/danforthcenter/plantcv-annotate/blob/main/plantcv/annotate/napari_label_classes.py)
diff --git a/docs/napari_open.md b/docs/napari_open.md
new file mode 100644
index 0000000..c699a85
--- /dev/null
+++ b/docs/napari_open.md
@@ -0,0 +1,36 @@
+## Open Image with Napari
+
+Open image data (e.g. RGB, gray, hyperspectral) with an interactive Napari viewer. If a gray image is opened, the image will be pseudocolored for better visualization.
+
+**plantcv.annotate.napari_open**(*img, show=True*)
+
+**returns** napari viewer object
+
+- **Parameters:**
+    - img - image data (compatible with gray, RGB, and hyperspectral data. If data is hyperspecral it should be the array e.g. hyperspectral.array_data)
+    - show - if show = True, viewer is launched. False setting is useful for test purposes.
+
+- **Context:**
+    - Used to open image data with Napari.
+
+- **Example use:**
+    - Open image data to annotate it with other Napari functions (e.g. napari_label_classes)
+
+
+```python
+import plantcv.plantcv as pcv 
+import plantcv.annotate as pcvan
+
+# Create an instance of the Points class
+img, path, name = pcv.readimage("./grayimg.png")
+
+viewer = pcvan.napari_open(img=img)
+
+# Should open interactive napari viewer
+
+```
+
+![Screenshot](img/documentation_images/napari_open/napari_open.png)
+
+
+**Source Code:** [Here](https://github.com/danforthcenter/plantcv-annotate/blob/main/plantcv/annotate/napari_open.py)
diff --git a/environment.yml b/environment.yml
new file mode 100644
index 0000000..a6d4838
--- /dev/null
+++ b/environment.yml
@@ -0,0 +1,33 @@
+# run: conda env create --file environment.yml
+# optionally, change channel name with -n {plantcv-dev}
+name: plantcv
+dependencies:
+  - python=3.10
+  - matplotlib>=1.5
+  - numpy>=1.11
+  - pandas
+  - python-dateutil
+  - scipy
+  - scikit-image>=0.19
+  - scikit-learn
+  - dask
+  - dask-jobqueue
+  - opencv
+  - statsmodels
+  - xarray>=2022.11.0
+  - mkdocs
+  - pytest
+  - pytest-cov
+  - flake8
+  - ipympl
+  - nodejs
+  - jupyterlab
+  - altair
+  - vl-convert-python
+  - napari
+  - pyqt
+  - pytest-qt
+
+channels:
+  - conda-forge
+  - defaults
diff --git a/mkdocs.yml b/mkdocs.yml
index 649a459..eff0192 100644
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -17,6 +17,10 @@ nav:
     - 'Adding/Editing Documentation': documentation.md
   - 'PlantCV Namespace':
     - 'Annotation Tools':
+      - Napari Classes: napari_classes.md
+      - Napari Join: napari_join_labels.md
+      - Napari Label: napari_label_classes.md
+      - Napari Open: napari_open.md
       - Points: Points.md
       - Get Centroids: get_centroids.md
 markdown_extensions:
diff --git a/plantcv/annotate/__init__.py b/plantcv/annotate/__init__.py
index 2c3ef6e..395de61 100644
--- a/plantcv/annotate/__init__.py
+++ b/plantcv/annotate/__init__.py
@@ -1,11 +1,19 @@
 from importlib.metadata import version
 from plantcv.annotate.classes import Points
 from plantcv.annotate.get_centroids import get_centroids
+from plantcv.annotate.napari_classes import napari_classes
+from plantcv.annotate.napari_open import napari_open
+from plantcv.annotate.napari_label_classes import napari_label_classes
+from plantcv.annotate.napari_join_labels import napari_join_labels
 
 # Auto versioning
 __version__ = version("plantcv-annotate")
 
 __all__ = [
     "Points",
-    "get_centroids"
+    "get_centroids",
+    "napari_classes",
+    "napari_open",
+    "napari_label_classes",
+    "napari_join_labels"
     ]
diff --git a/plantcv/annotate/napari_classes.py b/plantcv/annotate/napari_classes.py
new file mode 100755
index 0000000..77067ff
--- /dev/null
+++ b/plantcv/annotate/napari_classes.py
@@ -0,0 +1,31 @@
+# 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
diff --git a/plantcv/annotate/napari_join_labels.py b/plantcv/annotate/napari_join_labels.py
new file mode 100755
index 0000000..1848258
--- /dev/null
+++ b/plantcv/annotate/napari_join_labels.py
@@ -0,0 +1,100 @@
+# Use Napari to Label
+
+import numpy as np
+import os
+from plantcv.plantcv.warn import warn
+from plantcv.annotate import napari_classes
+from plantcv.plantcv import params
+from plantcv.plantcv._debug import _debug
+from skimage.color import label2rgb
+
+
+def napari_join_labels(img, viewer):
+    """
+    Join classes with the same label
+
+    Inputs:
+    img  = img  (grayimg, rgbimg, or hyperspectral image array data
+        e.g. hyperspectraldata.array_data). Adding labels works best on an
+        image that has objects segmented/classified with contours/clusters
+        labeled with values (e.g. labeled mask, output of kmeans clustering).
+    viewer = Napari Viewer with classes labeled (e.g viewer from
+        napari_label_classes)
+    show = if show is True the viewer is launched. This option is useful for
+    running tests without triggering the viewer.
+
+    Returns:
+    labeled_img  = labeled image
+    mask_dict   = dictionary of masks; mask for each class
+
+    :param img: numpy.ndarray
+    :param viewer: Napari Viewer object
+    :return labeled_img: numpy.ndarray
+    :return mask_dict: dict of numpy.ndarray
+
+    """
+    classes = napari_classes(viewer)
+    lastclassvalue = len(classes)
+
+    allmask = np.zeros((np.shape(img)))
+    maskdict = {}
+    valuesused = []
+    classvalue = []
+
+    for i, classname in enumerate(classes):
+        data = viewer.layers[str(classname)].data
+
+        if len(data) == 0:
+            classfinal = np.zeros((np.shape(img)))
+            classfinal = np.where(allmask == 0, classfinal == 0,
+                                  classfinal == 255)
+            totalmask = (classfinal.astype(int))*(i+1)
+            dictmask = classfinal.astype(int)
+            key = str(classname)
+            keylayer = key+"_layer"
+            maskdict.update({key: dictmask})
+            allmask = np.add(allmask, totalmask)
+            viewer.add_labels(dictmask, blending='additive', name=keylayer)
+        else:
+            classmask = np.zeros((np.shape(img)))
+            classmask1 = np.zeros((np.shape(img)))
+            classfinal = np.zeros((np.shape(img)))
+            for point in data:
+                x = int(point[0])
+                y = int(point[1])
+                value = img[x, y]
+                if value in valuesused:
+                    index = np.where(valuesused == value)[0]
+                    if classvalue[index] != classname:
+                        warning = ("A cluster in "+str(classname) +
+                                   " has been previously labeled as " +
+                                   str(classvalue[index]) +
+                                   ".Check point at position "+str(x)+"," +
+                                   str(y))
+                        warn(warning)
+                valuesused = np.append(valuesused, value)
+                classvalue = np.append(classvalue, classname)
+                classmask[img == value] = 1
+                classmask1 = np.add(classmask, classmask1)
+            classfinal = np.where(classmask1 != 0, classfinal == 0,
+                                  classfinal == 255)
+            totalmask = (classfinal.astype(int))*(i+1)
+            dictmask = classfinal.astype(int)
+            key = str(classname)
+            keylayer = key+"_layer"
+            maskdict.update({key: dictmask})
+            allmask[totalmask == (i+1)] = i+1
+            viewer.add_labels(dictmask, blending='additive', name=keylayer)
+
+    # set any zero values to last class value
+    allmask[allmask == 0] = lastclassvalue
+    if params.debug == 'print':
+        colorful = label2rgb(allmask)
+        outputimg = (255*colorful).astype(np.uint8)
+        _debug(visual=outputimg, filename=os.path.join(params.debug_outdir,
+                                                       str(params.device) +
+                                                       '_labeled_mask.png'))
+    else:
+        _debug(visual=allmask)
+
+    return allmask, maskdict
diff --git a/plantcv/annotate/napari_label_classes.py b/plantcv/annotate/napari_label_classes.py
new file mode 100755
index 0000000..81e37dd
--- /dev/null
+++ b/plantcv/annotate/napari_label_classes.py
@@ -0,0 +1,44 @@
+# Use Napari to Label
+
+import numpy as np
+import random
+from plantcv.annotate import napari_open
+
+
+def napari_label_classes(img, classes, show=True):
+    """
+    open img in napari and label classes
+
+    Inputs:
+    img  = img  (grayimg, rgbimg, or hyperspectral image array data
+        e.g. hyperspectraldata.array_data). Adding labels works best on an
+        image that has objects segmented/classified with contours/clusters
+        labeled with values (e.g. labeled mask, output of kmeans clustering).
+    classes = list of labels or classes. If no points are selected for a class,
+        data without labels will default to this class when napari_join_labels
+        is run. If all classes have points labeled, any clusters not labeled
+        will default to the last class in the list when napari_join_labels is
+        run.
+    show = if show is True the viewer is launched. This option is useful for
+    running tests without triggering the viewer.
+
+    Returns:
+    viewer  = Napari viewer object
+
+    :param img: numpy.ndarray
+    :param classes: list
+    :return viewer: napari viewer object
+
+    """
+    showcall = show
+    viewer = napari_open(img, show=showcall)
+
+    symbols = ['arrow', 'clobber', 'cross', 'diamond', 'disc', 'hbar', 'ring',
+               'square', 'star', 'tailed_arrow', 'triangle_down',
+               'triangle_up', 'vbar']
+
+    for x in classes:
+        viewer.add_points(np.array([]), name=x, symbol=random.choice(symbols),
+                          face_color='white', size=10)
+
+    return viewer
diff --git a/plantcv/annotate/napari_open.py b/plantcv/annotate/napari_open.py
new file mode 100755
index 0000000..59fa317
--- /dev/null
+++ b/plantcv/annotate/napari_open.py
@@ -0,0 +1,39 @@
+# Use Napari to Label
+
+import cv2
+import numpy as np
+from skimage.color import label2rgb
+import napari
+
+
+def napari_open(img, show=True):
+    """
+    open img in napari
+
+    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 option 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)
+    showcall = show
+    viewer = napari.Viewer(show=showcall)
+    viewer.add_image(img)
+    return viewer
diff --git a/pyproject.toml b/pyproject.toml
index f0e393e..5abfaf1 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -11,6 +11,8 @@ dynamic = ["version"]
 dependencies = [
     "plantcv",
     "matplotlib",
+    "napari",
+    "PyQt5"
 ]
 requires-python = ">=3.6"
 authors = [
@@ -30,6 +32,7 @@ classifiers = [
 test = [
     "pytest",
     "pytest-cov",
+    "pytest-qt"
 ]
 
 [project.urls]
diff --git a/tests/conftest.py b/tests/conftest.py
index 1b83096..4023056 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -2,6 +2,7 @@
 import pytest
 import matplotlib
 
+
 # Disable plotting
 matplotlib.use("Template")
 
@@ -19,8 +20,13 @@ def __init__(self):
         self.small_bin_img = os.path.join(self.datadir, "setaria_small_plant_mask.png")
         # Text file with tuple coordinates (by group label)
         self.pollen_coords = os.path.join(self.datadir, "points_file_import.coords")
+        # Kmeans Clustered Gray image
+        self.kmeans_seed_gray_img = os.path.join(self.datadir, "silphium_seed_labeled_example.png")
+        # Small Hyperspectral image
+        self.envi_sample_data = os.path.join(self.datadir, "corn-kernel-hyperspectral.raw")
+
 
 @pytest.fixture(scope="session")
 def test_data():
     """Test data object for the main PlantCV package."""
-    return TestData()
\ No newline at end of file
+    return TestData()
diff --git a/tests/test_annotate.py b/tests/test_annotate.py
deleted file mode 100644
index 1554fa1..0000000
--- a/tests/test_annotate.py
+++ /dev/null
@@ -1,7 +0,0 @@
-from plantcv import annotate as an
-
-
-def test_annotate():
-    """PlantCV Test"""
-    assert an.__name__ == "plantcv.annotate"
-    
\ No newline at end of file
diff --git a/tests/test_annotate_points.py b/tests/test_annotate_points.py
index f3b91e1..c74769b 100644
--- a/tests/test_annotate_points.py
+++ b/tests/test_annotate_points.py
@@ -1,5 +1,5 @@
 """Tests for annotate.Points."""
-import os 
+import os
 import cv2
 import matplotlib
 from plantcv.annotate.classes import Points
@@ -47,6 +47,7 @@ def test_points(test_data):
 
     assert drawer_rgb.coords["default"][0] == point1
 
+
 def test_points_print_coords(test_data, tmpdir):
     """Test for plantcv-annotate."""
     cache_dir = tmpdir.mkdir("cache")
@@ -71,10 +72,11 @@ def test_points_print_coords(test_data, tmpdir):
     e2.xdata, e2.ydata = (300, 200)
     drawer_rgb.onclick(e2)
 
-    # Save collected coords out 
+    # Save collected coords out
     drawer_rgb.print_coords(filename)
     assert os.path.exists(filename)
 
+
 def test_points_import_list(test_data):
     """Test for plantcv-annotate."""
     # Read in a test image
@@ -82,13 +84,15 @@ def test_points_import_list(test_data):
     # initialize interactive tool
     drawer_rgb = Points(img, figsize=(12, 6), label="default")
     totalpoints1 = [(158, 531), (361, 112), (500, 418), (269.25303806488864, 385.69839981447126),
-                  (231.21964288863632, 445.995245825603), (293.37177646934134, 448.778177179963), (240.49608073650273, 277.1640769944342), 
-                  (279.4571196975417, 240.05832560296852), (77.23077461405376, 165.84682282003712), (420, 364),
-                  (509.5127783246289, 353.2308673469388), (527.1380102355752, 275.3087894248609), (445.50535717435065, 138.94515306122452)]
+                    (231.21964288863632, 445.995245825603), (293.37177646934134, 448.778177179963),
+                    (240.49608073650273, 277.1640769944342), (279.4571196975417, 240.05832560296852),
+                    (77.23077461405376, 165.84682282003712), (420, 364), (509.5127783246289, 353.2308673469388),
+                    (527.1380102355752, 275.3087894248609), (445.50535717435065, 138.94515306122452)]
     drawer_rgb.import_list(coords=totalpoints1, label="imported")
 
     assert len(drawer_rgb.coords["imported"]) == 13
 
+
 def test_points_import_list_warn(test_data):
     """Test for plantcv-annotate."""
     # Read in a test image
@@ -100,15 +104,17 @@ def test_points_import_list_warn(test_data):
 
     assert len(drawer_rgb.coords["default"]) == 0
 
+
 def test_points_import_file(test_data):
     """Test for plantcv-annotate."""
     img = cv2.imread(test_data.small_rgb_img)
     counter = Points(img, figsize=(8, 6))
-    file  = test_data.pollen_coords
+    file = test_data.pollen_coords
     counter.import_file(file)
 
     assert counter.count['total'] == 70
 
+
 def test_points_view(test_data):
     """Test for plantcv-annotate."""
     # Read in a test grayscale image
@@ -133,12 +139,13 @@ def test_points_view(test_data):
 
     assert str(drawer_rgb.fig) == "Figure(1200x600)"
 
+
 def test_points_view_warn(test_data):
     """Test for plantcv-annotate."""
     # Read in a test grayscale image
     img = cv2.imread(test_data.small_rgb_img)
 
-    # initialize interactive tool, implied default label and "r" color 
+    # initialize interactive tool, implied default label and "r" color
     drawer_rgb = Points(img, figsize=(12, 6))
 
     # simulate mouse clicks, event 1=left click to add point
diff --git a/tests/test_napari_classes.py b/tests/test_napari_classes.py
new file mode 100644
index 0000000..f4050a9
--- /dev/null
+++ b/tests/test_napari_classes.py
@@ -0,0 +1,18 @@
+import numpy as np
+from plantcv.annotate import napari_classes
+
+
+def test_napari_classes(make_napari_viewer):
+    """Test for PlantCV.Annotate"""
+    # Read in test data
+    viewer = make_napari_viewer(show=False)
+    img = np.zeros((100, 100))
+    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']
diff --git a/tests/test_napari_join_labels.py b/tests/test_napari_join_labels.py
new file mode 100644
index 0000000..269465d
--- /dev/null
+++ b/tests/test_napari_join_labels.py
@@ -0,0 +1,79 @@
+import numpy as np
+from plantcv.annotate.napari_open import napari_open
+from plantcv.annotate.napari_label_classes import napari_label_classes
+from plantcv.plantcv import readimage
+from plantcv.annotate.napari_join_labels import napari_join_labels
+from plantcv.plantcv import params
+
+
+def test_napari_join_labels(test_data):
+    """Test for PlantCV.Annotate"""
+    # Read in test data
+    img, _, _ = readimage(test_data.kmeans_seed_gray_img)
+    viewer = napari_label_classes(img, ["seed"], show=False)
+    labeled, _ = napari_join_labels(img, viewer)
+
+    assert np.shape(labeled) == (576, 537)
+
+
+def test_napari_join_allclass(test_data):
+    """Test for PlantCV.Annotate"""
+    # Read in test data
+    img, _, _ = readimage(test_data.kmeans_seed_gray_img)
+    viewer = napari_open(img, show=False)
+    background = [(54, 143), (77, 246)]
+    viewer.add_points(np.array(background), symbol="o", name='background',
+                      face_color="red", size=1)
+    wing = [(275, 54)]
+    viewer.add_points(np.array(wing), symbol="o", name='wing',
+                      face_color="red", size=1)
+    seed = [(280, 218)]
+    viewer.add_points(np.array(seed), symbol="o", name='seed',
+                      face_color="red", size=1)
+
+    labeled, _ = napari_join_labels(img, viewer)
+
+    assert np.shape(labeled) == (576, 537)
+
+
+def test_napari_join_warn(test_data):
+    """Test for PlantCV.Annotate"""
+    # Read in test data
+    img, _, _ = readimage(test_data.kmeans_seed_gray_img)
+    viewer = napari_open(img, show=False)
+    background = [(54, 143), (77, 246)]
+    viewer.add_points(np.array(background), symbol="o", name='background',
+                      face_color="red", size=1)
+    wing = [(275, 54)]
+    viewer.add_points(np.array(wing), symbol="o", name='wing',
+                      face_color="red", size=1)
+    seed = [(275, 54)]
+    viewer.add_points(np.array(seed), symbol="o", name='seed',
+                      face_color="red", size=1)
+
+    labeled, _ = napari_join_labels(img, viewer)
+
+    assert np.shape(labeled) == (576, 537)
+
+
+def test_napari_join_print(test_data, tmpdir):
+    """Test for PlantCV.Annotate"""
+    params.debug = 'print'
+    cache_dir = tmpdir.mkdir("cache")
+    params.debug_outdir = cache_dir
+    # Read in test data
+    img, _, _ = readimage(test_data.kmeans_seed_gray_img)
+    viewer = napari_open(img, show=False)
+    background = [(54, 143), (77, 246)]
+    viewer.add_points(np.array(background), symbol="o", name='background',
+                      face_color="red", size=1)
+    wing = [(280, 218)]
+    viewer.add_points(np.array(wing), symbol="o", name='wing',
+                      face_color="red", size=1)
+    seed = [(275, 54)]
+    viewer.add_points(np.array(seed), symbol="o", name='seed',
+                      face_color="red", size=1)
+
+    labeled, _ = napari_join_labels(img, viewer)
+
+    assert np.shape(labeled) == (576, 537)
diff --git a/tests/test_napari_label_classes.py b/tests/test_napari_label_classes.py
new file mode 100644
index 0000000..ca49b8f
--- /dev/null
+++ b/tests/test_napari_label_classes.py
@@ -0,0 +1,15 @@
+import numpy as np
+from plantcv.annotate import napari_label_classes
+from plantcv.plantcv import readimage
+
+
+def test_napari_label_classes_gray(test_data):
+    """Test for PlantCV.Annotate"""
+    # Read in test data
+    img, _, _ = readimage(test_data.kmeans_seed_gray_img)
+    viewer = napari_label_classes(img, ['seed'], show=False)
+    coor = [(25, 25)]
+    viewer.add_points(np.array(coor), symbol="o", name='background',
+                      face_color="red", size=1)
+
+    assert len(viewer.layers['background'].data) == 1
diff --git a/tests/test_napari_open.py b/tests/test_napari_open.py
new file mode 100644
index 0000000..cfb9d25
--- /dev/null
+++ b/tests/test_napari_open.py
@@ -0,0 +1,40 @@
+import numpy as np
+from plantcv.annotate import napari_open
+from plantcv.plantcv import readimage
+
+
+def test_napari_open_rgb(test_data):
+    """Test for PlantCV.Annotate"""
+    # Read in test data
+    img, _, _ = readimage(test_data.small_rgb_img)
+    viewer = napari_open(img, show=False)
+    coor = [(25, 25), (50, 50)]
+    viewer.add_points(np.array(coor), symbol="o", name="total",
+                      face_color="red", size=1)
+
+    assert len(viewer.layers['total'].data) == 2
+
+
+def test_napari_open_gray(test_data):
+    """Test for PlantCV.Annotate"""
+    # Read in test data
+    img, _, _ = readimage(test_data.kmeans_seed_gray_img)
+    viewer = napari_open(img, show=False)
+    coor = [(25, 25), (50, 50)]
+    viewer.add_points(np.array(coor), symbol="o", name="total",
+                      face_color="red", size=1)
+
+    assert len(viewer.layers['total'].data) == 2
+
+
+def test_napari_open_envi(test_data):
+    """Test for PlantCV.Annotate"""
+    # Read in test data
+    img = readimage(test_data.envi_sample_data, mode='envi')
+    img = img.array_data
+    viewer = napari_open(img, show=False)
+    coor = [(25, 25), (50, 50)]
+    viewer.add_points(np.array(coor), symbol="o", name="total",
+                      face_color="red", size=1)
+
+    assert len(viewer.layers['total'].data) == 2
diff --git a/tests/testdata/corn-kernel-hyperspectral.hdr b/tests/testdata/corn-kernel-hyperspectral.hdr
new file mode 100644
index 0000000..6142bc5
--- /dev/null
+++ b/tests/testdata/corn-kernel-hyperspectral.hdr
@@ -0,0 +1,591 @@
+ENVI
+; this file was created using PlantCV version 3.14.1+743.gff91bfd
+; original file: 4-22-22_right_same_B73
+interleave = bil
+samples = 43
+lines = 31
+bands = 580
+data type = 12
+wavelength units = nm
+wavelength = {
+366.551,
+367.656,
+368.76,
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+}
\ No newline at end of file
diff --git a/tests/testdata/corn-kernel-hyperspectral.raw b/tests/testdata/corn-kernel-hyperspectral.raw
new file mode 100644
index 0000000..1ba7ed8
Binary files /dev/null and b/tests/testdata/corn-kernel-hyperspectral.raw differ
diff --git a/tests/testdata/silphium_seed_labeled_example.png b/tests/testdata/silphium_seed_labeled_example.png
new file mode 100644
index 0000000..fc4dcc6
Binary files /dev/null and b/tests/testdata/silphium_seed_labeled_example.png differ