# Imports
from .common import Any, NDArray, check_image, cv2, np
# Functions
[docs]
def threshold_image(image: NDArray[Any], thresholds: list[float], ignore_dtype: bool = False) -> NDArray[Any]:
""" Apply multi-level threshold to an image.
Args:
image (NDArray[Any]): Image to threshold
threshold (list[float]): List of threshold values (between 0 and 1)
ignore_dtype (bool): Ignore the dtype check
Returns:
NDArray[Any]: Multi-level thresholded image
>>> ## Basic tests
>>> image = np.array([[100, 150, 200], [50, 125, 175], [25, 75, 225]])
>>> threshold_image(image.astype(np.uint8), [0.3, 0.6]).tolist()
[[85, 85, 170], [0, 85, 170], [0, 0, 170]]
>>> rgb = np.random.randint(0, 256, (3,3,3), dtype=np.uint8)
>>> thresh_rgb = threshold_image(rgb, [0.3, 0.6])
>>> thresh_rgb.shape == rgb.shape
True
>>> ## Test invalid inputs
>>> threshold_image("not an image", [0.5])
Traceback (most recent call last):
...
AssertionError: Image must be a numpy array
>>> threshold_image(image.astype(np.uint8), [1.5])
Traceback (most recent call last):
...
AssertionError: threshold values must be between 0 and 1, got [1.5]
"""
# Check input data
check_image(image, ignore_dtype=ignore_dtype)
assert all(0 <= t <= 1 for t in thresholds), f"threshold values must be between 0 and 1, got {thresholds}"
# Convert thresholds from 0-1 range to 0-255 range
threshold_values: list[int] = [int(t * 255) for t in sorted(thresholds)]
# Apply threshold
if len(image.shape) == 2:
# Grayscale image
result: NDArray[Any] = np.zeros_like(image)
for i, thresh in enumerate(threshold_values):
value: int = int(255 * (i + 1) / (len(threshold_values) + 1))
mask: NDArray[Any] = cv2.threshold(image, thresh, value, cv2.THRESH_BINARY)[1]
result = cv2.max(result, mask)
else:
# Color image - convert to grayscale first, then back to color
gray: NDArray[Any] = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
result: NDArray[Any] = np.zeros_like(gray)
for i, thresh in enumerate(threshold_values):
value: int = int(255 * (i + 1) / (len(threshold_values) + 1))
mask: NDArray[Any] = cv2.threshold(gray, thresh, value, cv2.THRESH_BINARY)[1]
result = cv2.max(result, mask)
result = cv2.cvtColor(result, cv2.COLOR_GRAY2BGR)
return result
