Update test_digital_image_processing.py

Author: lighting9999

digital_image_processing/test_digital_image_processing.py

@@ -5,6 +5,7 @@
 import numpy as np
 from cv2 import COLOR_BGR2GRAY, cvtColor, imread
 from numpy import array, uint8
+from os import getenv
 from PIL import Image
 
 from digital_image_processing import change_contrast as cc
@@ -19,21 +20,23 @@
 from digital_image_processing.filters import sobel_filter as sob
 from digital_image_processing.resize import resize as rs
 
-img = imread(r"digital_image_processing/image_data/lena_small.jpg")
+# Define common image paths
+LENA_SMALL_PATH = "digital_image_processing/image_data/lena_small.jpg"
+LENA_PATH = "digital_image_processing/image_data/lena.jpg"
+
+img = imread(LENA_SMALL_PATH)
 gray = cvtColor(img, COLOR_BGR2GRAY)
 
 
 # Test: convert_to_negative()
 def test_convert_to_negative():
     negative_img = cn.convert_to_negative(img)
-    # assert negative_img array for at least one True
     assert negative_img.any()
 
 
 # Test: change_contrast()
 def test_change_contrast():
-    with Image.open("digital_image_processing/image_data/lena_small.jpg") as img:
-        # Work around assertion for response
+    with Image.open(LENA_SMALL_PATH) as img:
         assert str(cc.change_contrast(img, 110)).startswith(
             "<PIL.Image.Image image mode=RGB size=100x100 at"
         )
@@ -42,17 +45,14 @@ def test_change_contrast():
 # canny.gen_gaussian_kernel()
 def test_gen_gaussian_kernel():
     resp = canny.gen_gaussian_kernel(9, sigma=1.4)
-    # Assert ambiguous array
     assert resp.all()
 
 
 # canny.py
 def test_canny():
-    canny_img = imread("digital_image_processing/image_data/lena_small.jpg", 0)
-    # assert ambiguous array for all == True
+    canny_img = imread(LENA_SMALL_PATH, 0)
     assert canny_img.all()
     canny_array = canny.canny(canny_img)
-    # assert canny array for at least one True
     assert canny_array.any()
 
 
@@ -83,52 +83,30 @@ def test_sepia():
     assert sepia.all()
 
 
-def test_burkes(file_path: str = "digital_image_processing/image_data/lena_small.jpg"):
-    burkes = bs.Burkes(imread(file_path, 1), 120)
-    burkes.process()
-    assert burkes.output_img.any()
+def test_burkes():
+    burkes_img = bs.Burkes(imread(LENA_SMALL_PATH, 1), 120)
+    burkes_img.process()
+    assert burkes_img.output_img.any()
 
 
-def test_nearest_neighbour(
-    file_path: str = "digital_image_processing/image_data/lena_small.jpg",
-):
-    nn = rs.NearestNeighbour(imread(file_path, 1), 400, 200)
-    nn.process()
-    assert nn.output.any()
+def test_nearest_neighbour():
+    nn_img = rs.NearestNeighbour(imread(LENA_SMALL_PATH, 1), 400, 200)
+    nn_img.process()
+    assert nn_img.output.any()
 
 
 def test_local_binary_pattern():
-    # pull request 10161 before:
-    # "digital_image_processing/image_data/lena.jpg"
-    # after: "digital_image_processing/image_data/lena_small.jpg"
-
-    from os import getenv  # Speed up our Continuous Integration tests
-
-    file_name = "lena_small.jpg" if getenv("CI") else "lena.jpg"
-    file_path = f"digital_image_processing/image_data/{file_name}"
-
-    # Reading the image and converting it to grayscale
+    # Use smaller image in CI environment for faster tests
+    file_path = LENA_SMALL_PATH if getenv("CI") else LENA_PATH
     image = imread(file_path, 0)
 
-    # Test for get_neighbors_pixel function() return not None
-    x_coordinate = 0
-    y_coordinate = 0
-    center = image[x_coordinate][y_coordinate]
-
-    neighbors_pixels = lbp.get_neighbors_pixel(
-        image, x_coordinate, y_coordinate, center
-    )
-
+    # Test get_neighbors_pixel function
+    neighbors_pixels = lbp.get_neighbors_pixel(image, 0, 0, image[0][0])
     assert neighbors_pixels is not None
 
-    # Test for local_binary_pattern function()
-    # Create a numpy array as the same height and width of read image
+    # Test local_binary_pattern function
     lbp_image = np.zeros((image.shape[0], image.shape[1]))
-
-    # Iterating through the image and calculating the local binary pattern value
-    # for each pixel.
     for i in range(image.shape[0]):
         for j in range(image.shape[1]):
             lbp_image[i][j] = lbp.local_binary_value(image, i, j)
-
     assert lbp_image.any()