TheAlgorithms/Python · error · ValueError

ksize must be in {tuple(kernels)}

Error message

ksize must be in {tuple(kernels)}

What it means

Raised by the laplacian_filter function in digital_image_processing/filters/laplacian_filter.py:57 when `ksize` is not one of the keys of the kernels dict — this implementation provides pre-built Laplacian kernels of size 1, 3, 5, and 7 only. The chosen kernel is then applied with cv2.filter2D using CV_64F depth, so even-sized or other odd sizes were simply not authored.

Source

Thrown at digital_image_processing/filters/laplacian_filter.py:57

                [0, -1, -2, -1, 0],
                [0, 0, -1, 0, 0],
            ]
        ),
        7: np.array(
            [
                [0, 0, 0, -1, 0, 0, 0],
                [0, 0, -2, -3, -2, 0, 0],
                [0, -2, -7, -10, -7, -2, 0],
                [-1, -3, -10, 68, -10, -3, -1],
                [0, -2, -7, -10, -7, -2, 0],
                [0, 0, -2, -3, -2, 0, 0],
                [0, 0, 0, -1, 0, 0, 0],
            ]
        ),
    }
    if ksize not in kernels:
        msg = f"ksize must be in {tuple(kernels)}"
        raise ValueError(msg)

    # Apply the Laplacian kernel using convolution
    return filter2D(
        src, CV_64F, kernels[ksize], 0, borderType=BORDER_DEFAULT, anchor=(0, 0)
    )


if __name__ == "__main__":
    # read original image
    img = imread(r"../image_data/lena.jpg")

    # turn image in gray scale value
    gray = cvtColor(img, COLOR_BGR2GRAY)

    # Applying gaussian filter
    blur_image = gaussian_filter(gray, 3, sigma=1)

    # Apply multiple Kernel to detect edges

View on GitHub (pinned to f5988cc097)

Solutions

1. Restrict ksize to (1, 3, 5, 7) — mirror the tuple from the error message in your UI/config validation
2. Default to ksize=3 (or 1) when the user's value is unsupported
3. Catch ValueError at the config boundary and re-ask for a valid size

Example fix

// before
out = laplacian_filter(img, ksize=user_ksize)  # user_ksize=9 -> ValueError

# after
ksize = user_ksize if user_ksize in (1, 3, 5, 7) else 3
out = laplacian_filter(img, ksize)

ksize = ksize if ksize in (1, 3, 5, 7) else 3
out = laplacian_filter(img, ksize)

def is_supported_ksize(ksize: int) -> bool:
    return isinstance(ksize, int) and ksize in (1, 3, 5, 7)

try:
    out = laplacian_filter(img, ksize)
except ValueError:
    out = laplacian_filter(img, 3)

When it happens

Trigger: laplacian_filter(img, 2), laplacian_filter(img, 9), or passing cv2.LAPLACIAN_64F-style flags/enum values instead of a plain int size.

Common situations: Coming from cv2.Laplacian where ksize semantics differ, exposing ksize as a user config knob without a whitelist, or copy-pasting a ksize=9 from another pipeline.

Related errors

• level must be between -255.0 (black) and 255.0 (white)
• Factor value should be from 0 to {self.max_threshold}
• Destination width/height should be > 0
• number must be positive
• The value of input must be non-negative

AI-assisted analysis of TheAlgorithms/Python@f5988cc097 (2026-08-14). Data as JSON: /api/errors/3ad3df7dc2cc8464. Report an issue: GitHub.