remove usage of opencv-python entirely

.github/workflows/ci.yml

@@ -73,12 +73,6 @@ jobs:
           - toxenv: test-numpy120
             os: ubuntu-latest
             python-version: '3.8'
-          - toxenv: test-opencv-xdist
-            os: ubuntu-latest
-            python-version: '3.10'
-          - toxenv: test-scikitimage-xdist
-            os: ubuntu-latest
-            python-version: '3.10'
           - toxenv: test-jwst-xdist-cov
             os: ubuntu-latest
             python-version: '3.x'

pyproject.toml

@@ -13,7 +13,9 @@ classifiers = [
 ]
 dependencies = [
     'astropy >=5.0.4',
+    'scikit-image',
     'scipy >=1.6.0',
+    'shapely',
     'numpy >=1.17',
 ]
 dynamic = ['version']
@@ -35,13 +37,6 @@ test = [
     'pytest-doctestplus',
     'pytest-openfiles >=0.5.0',
 ]
-ellipse = [
-    'scikit-image',
-    'shapely',
-]
-opencv = [
-    'opencv-python>=4.6.0.66',
-]
 
 [project.urls]
 'repository' = 'https://github.com/spacetelescope/stcal'

src/stcal/jump/jump.py

@@ -9,25 +9,11 @@
 from . import constants
 from . import twopoint_difference as twopt
 
-ELLIPSE_PACKAGE = None
-try:
-    import cv2 as cv
-
-    ELLIPSE_PACKAGE = 'opencv-python'
-except (ImportError, ModuleNotFoundError):
-    try:
-        import shapely.geometry
-        import skimage.draw
-        import skimage.measure
-
-        from .circle import Circle
-
-        ELLIPSE_PACKAGE = 'scikit-image'
-        ELLIPSE_PACKAGE_WARNING = '`opencv-python` not installed; ' \
-                                  'using `scikit-image` + `shapely` for ellipse construction'
-    except (ImportError, ModuleNotFoundError):
-        ELLIPSE_PACKAGE_WARNING = 'an image processing package (either `opencv-python` or `scikit-image` + `shapely`)' \
-                                  'must be installed in order to use ellipses'
+import shapely.geometry
+import skimage.draw
+import skimage.measure
+
+from .circle import Circle
 
 log = logging.getLogger(__name__)
 log.setLevel(logging.DEBUG)
@@ -413,14 +399,9 @@ def extend_snowballs(plane, snowballs, sat_flag, jump_flag, expansion=1.5):
         center = (round(ceny), round(cenx))
         extend_radius = round(jump_radius * expansion)
         color = (0, 0, 4)
-        if ELLIPSE_PACKAGE == 'opencv-python':
-            image = cv.circle(image, center, extend_radius, color, -1)
-        elif ELLIPSE_PACKAGE == 'scikit-image':
-            warnings.warn(ELLIPSE_PACKAGE_WARNING)
-            disk = skimage.draw.disk(center, extend_radius)
-            image[disk] = color
-        else:
-            raise ModuleNotFoundError(ELLIPSE_PACKAGE_WARNING)
+        warnings.warn(ELLIPSE_PACKAGE_WARNING)
+        disk = skimage.draw.disk(center, extend_radius)
+        image[disk] = color
         jump_circle = image[:, :, 2]
         saty, satx = np.where(sat_pix == 2)
         jump_circle[saty, satx] = 0
@@ -452,14 +433,9 @@ def extend_ellipses(plane, ellipses, sat_flag, jump_flag, expansion=1.1):
         center = (round(ceny), round(cenx))
         axes = (round(axis1 / 2), round(axis2 / 2))
         color = (0, 0, 4)
-        if ELLIPSE_PACKAGE == 'opencv-python':
-            image = cv.ellipse(image, center, axes, alpha, 0, 360, color, -1)
-        elif ELLIPSE_PACKAGE == 'scikit-image':
-            warnings.warn(ELLIPSE_PACKAGE_WARNING)
-            ellipse = skimage.draw.ellipse(*center, *axes, rotation=alpha)
-            image[ellipse] = color
-        else:
-            raise ModuleNotFoundError(ELLIPSE_PACKAGE_WARNING)
+        warnings.warn(ELLIPSE_PACKAGE_WARNING)
+        ellipse = skimage.draw.ellipse(*center, *axes, rotation=alpha)
+        image[ellipse] = color
         jump_ellipse = image[:, :, 2]
         saty, satx = np.where(sat_pix == 2)
         jump_ellipse[saty, satx] = 0
@@ -471,16 +447,9 @@ def find_circles(dqplane, bitmask, min_area):
     # Using an input DQ plane this routine will find the groups of pixels with at least the minimum
     # area and return a list of the minimum enclosing circle parameters.
     pixels = np.bitwise_and(dqplane, bitmask)
-    if ELLIPSE_PACKAGE == 'opencv-python':
-        contours, hierarchy = cv.findContours(pixels, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE)
-        bigcontours = [con for con in contours if cv.contourArea(con) >= min_area]
-        circles = [cv.minEnclosingCircle(con) for con in bigcontours]
-    elif ELLIPSE_PACKAGE == 'scikit-image':
-        contours = [shapely.geometry.Polygon(con) for con in skimage.measure.find_contours(pixels)]
-        bigcontours = [con for con in contours if con.area > min_area]
-        circles = [Circle.from_points(numpy.stack(con.exterior.xy, axis=1)) for con in bigcontours]
-    else:
-        raise ModuleNotFoundError(ELLIPSE_PACKAGE_WARNING)
+    contours = [shapely.geometry.Polygon(con) for con in skimage.measure.find_contours(pixels)]
+    bigcontours = [con for con in contours if con.area > min_area]
+    circles = [Circle.from_points(numpy.stack(con.exterior.xy, axis=1)) for con in bigcontours]
     return circles
 
 
@@ -489,29 +458,20 @@ def find_ellipses(dqplane, bitmask, min_area):
     # area and return a list of the minimum enclosing ellipse parameters.
     pixels = np.bitwise_and(dqplane, bitmask)
 
-    if ELLIPSE_PACKAGE == 'opencv-python':
-        contours, hierarchy = cv.findContours(pixels, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE)
-        bigcontours = [con for con in contours if cv.contourArea(con) > min_area]
-        # minAreaRect is used becuase fitEllipse requires 5 points and it is possible to have a contour
-        # with just 4 points.
-        ellipses = [cv.minAreaRect(con) for con in bigcontours]
-    elif ELLIPSE_PACKAGE == 'scikit-image':
-        contours = [shapely.geometry.Polygon(con) for con in skimage.measure.find_contours(pixels)]
-        bigcontours = [con for con in contours if con.area > min_area]
-        rectangles = [
-            numpy.flip(numpy.stack(con.minimum_rotated_rectangle.exterior.xy, axis=1), axis=1)
-            for con in bigcontours
-        ]
-        ellipses = [
-            (
-                numpy.mean(rectangle[[0, 2], :], axis=0),
-                numpy.hypot(*numpy.diff(rectangle[[0, 1, 2], :], axis=0)),
-                numpy.degrees(numpy.arctan2(*numpy.flip(numpy.diff(rectangle[[3, 0], :], axis=0)[0])))
-            )
-            for rectangle in rectangles
-        ]
-    else:
-        raise ModuleNotFoundError(ELLIPSE_PACKAGE_WARNING)
+    contours = [shapely.geometry.Polygon(con) for con in skimage.measure.find_contours(pixels)]
+    bigcontours = [con for con in contours if con.area > min_area]
+    rectangles = [
+        numpy.flip(numpy.stack(con.minimum_rotated_rectangle.exterior.xy, axis=1), axis=1)
+        for con in bigcontours
+    ]
+    ellipses = [
+        (
+            numpy.mean(rectangle[[0, 2], :], axis=0),
+            numpy.hypot(*numpy.diff(rectangle[[0, 1, 2], :], axis=0)),
+            numpy.degrees(numpy.arctan2(*numpy.flip(numpy.diff(rectangle[[3, 0], :], axis=0)[0])))
+        )
+        for rectangle in rectangles
+    ]
 
     return ellipses
 

tox.ini

@@ -46,15 +46,11 @@ description =
     run tests
     jwst: of JWST pipeline
     romancal: of Romancal pipeline
-    opencv: requiring opencv-python
-    scikitimage: requiring scikit-image
     warnings: treating warnings as errors
     cov: with coverage
     xdist: using parallel processing
 extras =
     test
-    scikitimage: ellipse
-    opencv: opencv
 deps =
     xdist: pytest-xdist
     jwst: jwst[test] @ git+https://github.com/spacetelescope/jwst.git
@@ -79,7 +75,6 @@ commands =
     jwst: --pyargs jwst --ignore-glob=timeconversion --ignore-glob=associations --ignore-glob=scripts \
     romancal: --pyargs romancal \
     cov: --cov=. --cov-config=pyproject.toml --cov-report=term-missing --cov-report=xml \
-    opencv,scikitimage: -- tests/test_jump.py \
     {posargs}
 
 [testenv:build-docs]