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Imgdiff

Blendmodes Index / Blendmodes / Imgdiff

Auto-generated documentation for blendmodes.imgdiff module.

image_diff

Show source in imgdiff.py:119

Compare two images and return the difference as a value between 0 and 1, or if percentage: 0 and 100.

For example, a black and white image compared in 'RGB' mode would return a value of 100, which would then be checked if its between cmp_diff - tolerance and cmp_diff + tolerance

:param Image.Image img1in: image 1 to compare :param Image.Image img2in: image 2 to compare

Arguments

  • compare_mode str - how should the pillow images be compared? eg RGBA, RGB, L etc param bool percentage: are we comparing in percentage mode vs 0-1 mode?

Returns

Type: float value representing how different the images are

Example Use

>>> img1 = Image.new("RGB", (100, 100), "red")
>>> img2 = Image.new("RGB", (100, 100), "blue")
>>> res = image_diff(img1, img2, compare_mode="RGB")
>>> int(res)
33
>>> img1 = Image.new("RGB", (100, 100), "white")
>>> img2 = Image.new("RGB", (100, 100), "black")
>>> image_diff(img1, img2, compare_mode="RGB")
100.0
>>> img1 = Image.new("RGB", (100, 100), "red")
>>> img2 = Image.new("RGB", (100, 100), "blue")
>>> res = image_diff(img1, img2, compare_mode="L")
>>> int(res)
18

Signature

def image_diff(
    img1in: Image.Image,
    img2in: Image.Image,
    compare_mode: str = "RGBA",
    percentage: bool = True,
) -> float: ...

image_diff_array

Show source in imgdiff.py:163

Compare two images and return difference between 0, and 1. Supports both PIL Images and NumPy arrays.

Both images must be in the same mode/ shape

:param Image.Image | np.ndarray img1in: image 1 to compare :param Image.Image | np.ndarray img2in: image 2 to compare

Returns

Type: float value representing how different the images are. between 0, and 1

Example Use

>>> img1 = Image.new("RGB", (100, 100), "red")
>>> img2 = Image.new("RGB", (100, 100), "blue")
>>> res = image_diff(img1, img2)
>>> int(res)
25
>>> img1 = Image.new("RGB", (100, 100), "white")
>>> img2 = Image.new("RGB", (100, 100), "black")
>>> image_diff(img1, img2)
75.0

Signature

def image_diff_array(
    img1in: Image.Image | np.ndarray, img2in: Image.Image | np.ndarray
) -> float: ...

is_equal

Show source in imgdiff.py:76

Compare two images and return True/False if the image is within tolerance of the second image.

:param Image.Image img1in: image 1 to compare :param Image.Image img2in: image 2 to compare

Arguments

  • compare_mode str - how should the pillow images be compared? eg RGBA, RGB, L etc param float tolerance: what tolerance should we accept on any inequality? param bool percentage: are we comparing in percentage mode vs 0-1 mode?

Returns

Type: bool if the images are equal with a given tolerance

Example Use

>>> img1 = Image.new("RGB", (100, 100), "red")
>>> img2 = Image.new("RGB", (100, 100), "blue")
>>> is_equal(img1, img2, compare_mode="RGB", tolerance=1)
False
>>> img1 = Image.new("RGB", (100, 100), "white")
>>> img2 = Image.new("RGB", (100, 100), "black")
>>> is_equal(img1, img2, compare_mode="RGB", tolerance=1)
False
>>> img1 = Image.new("RGB", (100, 100), "red")
>>> img2 = Image.new("RGB", (100, 100), "blue")
>>> is_equal(img1, img2, compare_mode="L", tolerance=1)
False

Signature

def is_equal(
    img1in: Image.Image,
    img2in: Image.Image,
    compare_mode: str = "RGBA",
    tolerance: float = 0,
    percentage: bool = True,
) -> bool: ...

is_x_diff

Show source in imgdiff.py:25

Compare two images and return True/False if the image is within tolerance of cmp_diff.

For example, a black and white image compared in 'RGB' mode would return a value of 100, which would then be checked if its between cmp_diff - tolerance and cmp_diff + tolerance

:param Image.Image img1in: image 1 to compare :param Image.Image img2in: image 2 to compare

Arguments

  • compare_mode str - how should the pillow images be compared? eg RGBA, RGB, L etc
  • cmp_diff float - how 'unequal' should the images be? 0 for identical, 1 (or 100) for completely different (eg black + white in L mode) param float tolerance: what tolerance should we accept on the inequality? param bool percentage: are we comparing in percentage mode vs 0-1 mode?

Returns

Type: bool True/False if the images are within tolerance of cmp_diff.

Example Use

>>> img1 = Image.new("RGB", (100, 100), "red")
>>> img2 = Image.new("RGB", (100, 100), "blue")
>>> is_x_diff(img1, img2, compare_mode="RGB", cmp_diff=33, tolerance=1)
True
>>> img1 = Image.new("RGB", (100, 100), "white")
>>> img2 = Image.new("RGB", (100, 100), "black")
>>> is_x_diff(img1, img2, compare_mode="RGB", cmp_diff=100, tolerance=1)
True
>>> img1 = Image.new("RGB", (100, 100), "red")
>>> img2 = Image.new("RGB", (100, 100), "blue")
>>> is_x_diff(img1, img2, compare_mode="L", cmp_diff=18, tolerance=1)
True

Signature

def is_x_diff(
    img1in: Image.Image,
    img2in: Image.Image,
    compare_mode: str = "RGBA",
    cmp_diff: float = 0,
    tolerance: float = 0,
    percentage: bool = True,
) -> bool: ...