Tomni

Tomni is a python package that contains a collection of helper functions based on OpenCV and NumPy. It can be used for any python based computer vision or image analysis problem. The package simplifies the code and takes care of edge cages, everything from simplifying code like img_dim to compute optimization like labels2contours or illumination correction image processing. Tomni uses the image coordinates (same as OpenCV).

Tomni is created by CytoSMART.

The package was developed in-house to centralize the helper function for computer vision problems. In 2021, CytoSMART engineers turned it to open source, enabling researchers and educators to use it for free.

Getting Tomni

pip install tomni

License

Tomni is free for academic and educational use.

For commercial use please contact CytoSMART.

The name

The name Tomni is a combination of creator (Tom) and other CytoSMART product he was working on, the Omni. Tomni name was proposed by Denissa Daroţi, a former CytoSMART intern, who won a bet with her mentor by getting a (well deserved) 9/10 for her internship.

Features

Bounding box fitting (bbox fitting)
- Center bounding box fit
- Custom location box fit
Image helpers
- Get image dimensions
- Convert color of an image
Illumination correction
- Brightfield
- Fluorescence
Contour operations
- Get center
- Approximate circle by area
- Get roundness
- Get circularity
CytoSMART data format
- Tba
Json operation
- Add circularity property
- Scale object
- Translate object
Make a mask
- Ellipse
- Polygon
Polygon downsampling
- iterative downsampling
Shape fitting
- Rect around ellipse
Transformers of data format
- Contours to json
- Ellipse to json
- Json 2 contours
- Json 2 label
- Json 2 bbox
- Labels 2 contours
- Labels 2 lists of points
- Binary 2 contours

Examples

Diameter vs radius

Most geometric operation use functions from OpenCV

Some of these function return diameter and some radius of the circle. This is not consistent.

For example, the function cv2.minEnclosingCircle returns the center and radius of the circle. The function cv2.fitEllipse returns the center and the major and minor axes of the ellipse.

Min enclosing circle example

import cv2
import math
import numpy as np

points = np.array([[0, 0], [100, 0], [100, 100], [0, 100], [0, 0]], dtype=np.float32)

center, radius = cv2.minEnclosingCircle(points)
diameter = math.sqrt(50**2 + 50**2) 

print("Center:", center)
print("Major and Minor Axes:", radius)
print("Diameter calculated with Pythagoras formula", diameter)

this results in the following output:

Center: (50.0, 50.0)
Major and Minor Axes: 70.71077728271484
Diameter calculated with Pythagoras formula 70.71067811865476

Fit ellipse example

import cv2
import math
import numpy as np

# Generate some example points
points = np.array([[0, 0], [100, 0], [100, 100], [0, 100], [0, 0]], dtype=np.float32)

# Fit an ellipse to the points
ellipse = cv2.fitEllipse(points)

# Extract ellipse parameters
center, axes, angle = ellipse

diameter = math.sqrt(50**2 + 50**2) * 2

print("Center:", center)
print("Major and Minor Axes:", axes)
print("Diameter calculated with Pythagoras formula", diameter)