# pyright: reportUnusedImport=false
# ruff: noqa: F401
# Imports
from .common import Any, NDArray, check_image, cv2, np
# Functions
[docs]
def binary_threshold_image(image: NDArray[Any], threshold: float, ignore_dtype: bool = False) -> NDArray[Any]:
""" Apply binary threshold to an image.
Args:
image (NDArray[Any]): Image to threshold
threshold (float): Threshold value (between 0 and 1)
ignore_dtype (bool): Ignore the dtype check
Returns:
NDArray[Any]: Thresholded binary image
>>> ## Basic tests
>>> image = np.array([[100, 150, 200], [50, 125, 175], [25, 75, 225]])
>>> binary_threshold_image(image.astype(np.uint8), 0.5).tolist()
[[0, 255, 255], [0, 0, 255], [0, 0, 255]]
>>> np.random.seed(42)
>>> img = np.random.randint(0, 256, (4,4), dtype=np.uint8)
>>> thresholded = binary_threshold_image(img, 0.7)
>>> set(np.unique(thresholded).tolist()) <= {0, 255} # Should only contain 0 and 255
True
>>> rgb = np.random.randint(0, 256, (3,3,3), dtype=np.uint8)
>>> thresh_rgb = binary_threshold_image(rgb, 0.5)
>>> thresh_rgb.shape == rgb.shape
True
>>> set(np.unique(thresh_rgb).tolist()) <= {0, 255}
True
>>> ## Test invalid inputs
>>> binary_threshold_image("not an image", 0.5)
Traceback (most recent call last):
...
AssertionError: Image must be a numpy array
>>> binary_threshold_image(image.astype(np.uint8), "0.5")
Traceback (most recent call last):
...
AssertionError: threshold must be a number, got <class 'str'>
>>> binary_threshold_image(image.astype(np.uint8), 1.5)
Traceback (most recent call last):
...
AssertionError: threshold must be between 0 and 1, got 1.5
"""
# Check input data
check_image(image, ignore_dtype=ignore_dtype)
assert isinstance(threshold, float | int), f"threshold must be a number, got {type(threshold)}"
assert 0 <= threshold <= 1, f"threshold must be between 0 and 1, got {threshold}"
# Convert threshold from 0-1 range to 0-255 range
threshold_value: int = int(threshold * 255)
# Apply threshold
if len(image.shape) == 2:
# Grayscale image
binary: NDArray[Any] = cv2.threshold(image, threshold_value, 255, cv2.THRESH_BINARY)[1]
else:
# Color image - convert to grayscale first, then back to color
gray: NDArray[Any] = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
binary: NDArray[Any] = cv2.threshold(gray, threshold_value, 255, cv2.THRESH_BINARY)[1]
binary = cv2.cvtColor(binary, cv2.COLOR_GRAY2BGR)
return binary
