[pre-commit.ci] pre-commit autoupdate (#9013)

* [pre-commit.ci] pre-commit autoupdate

updates:
- [github.com/astral-sh/ruff-pre-commit: v0.0.285 → v0.0.286](https://github.com/astral-sh/ruff-pre-commit/compare/v0.0.285...v0.0.286)
- [github.com/tox-dev/pyproject-fmt: 0.13.1 → 1.1.0](https://github.com/tox-dev/pyproject-fmt/compare/0.13.1...1.1.0)

* updating DIRECTORY.md

* Fis ruff rules PIE808,PLR1714

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: github-actions <${GITHUB_ACTOR}@users.noreply.github.com>
Co-authored-by: Christian Clauss <cclauss@me.com>

digital_image_processing/filters/bilateral_filter.py

@@ -31,8 +31,8 @@ def get_slice(img: np.ndarray, x: int, y: int, kernel_size: int) -> np.ndarray:
 def get_gauss_kernel(kernel_size: int, spatial_variance: float) -> np.ndarray:
     # Creates a gaussian kernel of given dimension.
     arr = np.zeros((kernel_size, kernel_size))
-    for i in range(0, kernel_size):
-        for j in range(0, kernel_size):
+    for i in range(kernel_size):
+        for j in range(kernel_size):
             arr[i, j] = math.sqrt(
                 abs(i - kernel_size // 2) ** 2 + abs(j - kernel_size // 2) ** 2
             )

digital_image_processing/filters/convolve.py

@@ -11,8 +11,8 @@ def im2col(image, block_size):
     dst_width = rows - block_size[0] + 1
     image_array = zeros((dst_height * dst_width, block_size[1] * block_size[0]))
     row = 0
-    for i in range(0, dst_height):
-        for j in range(0, dst_width):
+    for i in range(dst_height):
+        for j in range(dst_width):
             window = ravel(image[i : i + block_size[0], j : j + block_size[1]])
             image_array[row, :] = window
             row += 1

digital_image_processing/filters/local_binary_pattern.py

@@ -71,8 +71,8 @@ if __name__ == "__main__":
 
     # Iterating through the image and calculating the
     # local binary pattern value for each pixel.
-    for i in range(0, image.shape[0]):
-        for j in range(0, image.shape[1]):
+    for i in range(image.shape[0]):
+        for j in range(image.shape[1]):
             lbp_image[i][j] = local_binary_value(image, i, j)
 
     cv2.imshow("local binary pattern", lbp_image)

digital_image_processing/test_digital_image_processing.py

@@ -118,8 +118,8 @@ def test_local_binary_pattern():
 
     # Iterating through the image and calculating the local binary pattern value
     # for each pixel.
-    for i in range(0, image.shape[0]):
-        for j in range(0, image.shape[1]):
+    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()