A small, typed helper for rectangular regions of interest (ROI) in NumPy images: one dataclass to crop, measure, move, and resize.
A 100×120 sample image (Gaussian spot plus noise, seed 0). Orange: roi; blue: the ROI
recentered on the brightest pixel of the crop and resized to 20×20. The values on the right are
the script's own output. Regenerate with python examples/readme_figure.py (needs matplotlib).
pip install roi-rectangleimport numpy as np
from roi_rectangle import RoiRectangle
image = np.arange(100 * 120).reshape(100, 120)
roi = RoiRectangle(y1=30, y2=80, x1=20, x2=70) # rows [30, 80), cols [20, 70)
print(roi.shape, roi.center, roi.area) # (50, 50) (45, 55) 2500
crop = roi.slice(image) # same as image[30:80, 20:70]
print(crop.shape) # (50, 50)
roi2 = roi.recenter((60, 40)).resize(10, 20) # methods return new ROIs
print(roi2) # RoiRectangle(y1=30, y2=50, x1=55, x2=65)
print(image[roi2.get_slices()].shape) # (20, 10)RoiRectangle(y1, y2, x1, x2) is a dataclass. Intervals are half-open: [y1, y2) and [x1, x2).
y2 or x2 may be None, meaning the region extends to the image edge on that axis.
A ValueError is raised if y2 < y1 or x2 < x1.
| Member | Description |
|---|---|
width, height, shape, area |
Size properties (shape is (height, width)); None for unbounded axes. |
center |
(x, y) center, rounded down; None if any axis is unbounded. |
move(dx, dy) |
New ROI shifted by (dx, dy). |
recenter((x, y)) |
New ROI of the same size centered at (x, y). |
resize(width, height) |
New ROI with the given size around the same center. |
slice(image) |
image[..., y1:y2, x1:x2]; works on stacks with leading axes. |
get_slices() |
(slice(y1, y2), slice(x1, x2)) for indexing. |
to_tuple(), from_tuple(t) |
Convert to/from (y1, y2, x1, x2). |
Coordinates are passed to NumPy unchanged: an ROI past the bottom or right edge is clipped by NumPy, while negative coordinates count from the end of the axis.
If you use this package in your work, please cite it using the metadata in CITATION.cff.
MIT. See LICENSE.