A pure Python implementation of the subpixel edge location algorithm from https://doi.org/10.1016/j.imavis.2012.10.005

The reference implementation can be found on from https://it.mathworks.com/matlabcentral/fileexchange/48908-accurate-subpixel-edge-location

pip install subpixel-edges

For a quick overview of the code functionalities, install the following packages first:

$ pip install subpixel-edges
$ pip install opencv-python
$ pip install matplotlib

Then go into the directory you want to use and copy the image you want to analyze (let's say lena.png). Now open a Python console and execute the following commands:

import cv2
import matplotlib.pyplot as plt

from subpixel_edges import subpixel_edges

# (optional) 
help(subpixel_edges) 

img = cv2.imread("lena.png")
img_gray = (cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)).astype(float)
edges = subpixel_edges(img_gray, 25, 0, 2)

plt.imshow(img)
plt.quiver(edges.x, edges.y, edges.nx, -edges.ny, scale=40)
plt.show()

git clone https://github.com/gravi-toni/subpixel-edges.git
pip install -e .

To run the tests (includes OpenCV):

pip install -e .[tests]

To run the examples (includes OpenCV):

pip install -e .[examples]