Merge pull request #64 from UBC-MDS/grayscale_function

Grayscale function

src/imagenie/grayscale.py

@@ -12,34 +12,24 @@ def grayscale(image):
     Returns:
     -------
     ndarray
-        The grayscale image as a 2D NumPy array.
+        The grayscale image as a 2D NumPy array (dtype=uint8).
 
     Raises:
     ------
     TypeError
         If the input is not a NumPy array.
     ValueError
         If the input is not a 2D or 3D NumPy array, or if the 3D array does not have 3 channels.
-
-    Examples:
-    ---------
-    Convert an RGB image to grayscale:
-    >>> gray_image = grayscale(image)
     """
-    # Ensure the input is a valid NumPy array
     if not isinstance(image, np.ndarray):
         raise TypeError("The input image must be a NumPy array.")
-
-    # Handle already grayscale (2D) images
     if image.ndim == 2:
         return image
-
-    # Handle RGB images (3D)
     elif image.ndim == 3:
         if image.shape[-1] != 3:
             raise ValueError("The input image must have 3 channels in the last dimension for RGB.")
-        # Use weighted average to convert to grayscale
-        return np.dot(image[..., :3], [0.2989, 0.5870, 0.1140])
-
+        # Convert to grayscale with rounding and cast to uint8
+        return np.round(np.dot(image[..., :3], [0.2989, 0.5870, 0.1140])).astype(np.uint8)
     else:
         raise ValueError("The input image must be a 2D or 3D NumPy array.")
+

tests/test_grayscale.py

@@ -1,5 +1,8 @@
 import unittest
 import numpy as np
+import sys
+import os
+sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '../src')))
 from imagenie.grayscale import grayscale 
 
 def test_grayscale():
@@ -54,3 +57,4 @@ def test_grayscale():
 if __name__ == "__main__":
     test_grayscale()
     print("All tests passed.")
+