deepsource

Author: joshqsumner

.github/workflows/continuous-integration.yml

@@ -36,4 +36,13 @@ jobs:
       # Run coverage analysis on pytest tests
       run: |
         pip install .
-        py.test --cov-report=xml --cov=./
+        py.test --cov-report=xml --cov=./
+    - name: Upload coverage to Deepsource
+      if: ${{ matrix.python-version == '3.13' }}
+      uses: deepsourcelabs/test-coverage-action@master
+      with:
+        key: python
+        coverage-file: coverage.xml
+        dsn: ${{ secrets.DEEPSOURCE_DSN }}
+      env:
+        DEEPSOURCE_DSN: ${{ secrets.DEEPSOURCE_DSN }}

littlecv/littlecv/analyze_size.py

@@ -1,5 +1,4 @@
 """Analyzes the shape and size of objects and outputs data."""
-import os
 import cv2
 import numpy as np
 from littlecv.littlecv.outputs import Outputs
@@ -53,8 +52,6 @@ def _analyze_size(img, mask, label):
     total_edge_length = 0
     width = 0
     height = 0
-    caliper_length = 0
-    longest_path = 0
     cmx = 0
     cmy = 0
     hull_vertices = 0

littlecv/littlecv/fill.py

@@ -1,6 +1,5 @@
 # Object fill device
 
-import numpy as np
 import numpy as np
 from littlecv.littlecv.plot_image import plot_image
 from skimage.morphology import remove_small_objects

littlecv/littlecv/outputs.py

@@ -7,7 +7,7 @@ def __init__(self):
         self.observations = {}
         self.metadata = {}
 
-     # Method to add observation to outputs
+    # Method to add observation to outputs
     def add_observation(self, sample, variable, trait, method, scale, datatype, value, label):
         """Keyword arguments/parameters:
         sample       = Sample name. Used to distinguish between multiple samples

littlecv/littlecv/plot_image.py

@@ -5,12 +5,10 @@
 from matplotlib import pyplot as plt
 
 
-def plot_image(img, cmap=None, plot=True, **kwargs):
-    """
-    Plot an image to the screen.
+def plot_image(img, plot=True, **kwargs):
+    """Plot an image to the screen.
 
     :param img: numpy.ndarray, ggplot, xarray.core.dataarray.DataArray
-    :param cmap: str
     :param plot: bool, make a plot
                (defaults True, only used internally in place of pcv.params.debug)
     :param kwargs: key-value arguments to xarray.plot method

littlecv/littlecv/readimage.py

@@ -1,7 +1,6 @@
 # Read image
 import os
 import cv2
-import numpy as np
 from littlecv.littlecv.plot_image import plot_image
 
 
@@ -19,11 +18,10 @@ def readimage(filename, plot=True):
     path     = str, path to image file
     img_name = str, name of image file
     """
-
     img = cv2.imread(filename, -1)
     # Split path from filename
     path, img_name = os.path.split(filename)
     # we are always going to debug in this dummy version
     plot_image(img, plot=plot)
-    
+
     return img, path, img_name

littlecv/littlecv/rgb2gray_lab.py

@@ -1,4 +1,3 @@
-import os
 import cv2
 from littlecv.littlecv.plot_image import plot_image
 
@@ -16,7 +15,7 @@ def rgb2gray_lab(rgb_img, channel, plot=True):
         color subchannel (l = lightness, a = green-magenta, b = blue-yellow)
     plot    : bool
         lazy version of pcv.params.debug
-    
+
     Returns
     -------
     numpy.ndarray
@@ -25,9 +24,6 @@ def rgb2gray_lab(rgb_img, channel, plot=True):
     # Convert RGB to LAB and return the specified subchannel as a gray image
     gray_img = _rgb2lab(rgb_img=rgb_img, channel=channel)
 
-    # The allowable channel inputs are l, a or b
-    names = {"l": "lightness", "a": "green-magenta", "b": "blue-yellow"}
-
     plot_image(gray_img, plot=plot)
 
     return gray_img

tests/test_littlecv.py

@@ -1,5 +1,4 @@
 import os
-import cv2
 import matplotlib
 import numpy as np
 from littlecv import littlecv as lcv