ArUco marker-based displacement measurement Python module

Perform displacement measurement using ArUco phisical markers captured with a still camera

Using this package

Download the repository

Simple examples

Here is a simple example on how to use the code:

import numpy as np
import os
from matplotlib.pyplot import show
from pyArUco import *

os.system('cls')
# Path of the video to analyze
path = file_explorer()

# Obtain matrix and frame rate information
video, fps = load_video(path)

# Detection parameters
mrks_pos, sample_frame, id_detected = arUCO_video_detection(video, adv_param=True, binarization=True, thresh=120, dilate=True)

# Marker ID to look for in the analyzed video
ID = 1

# Marker phisical length [mm]
dim_mm = 15

# Apply spatial calibration
relative_disp_mm, global_center_px, len_pixel = spatial_calibration(dim_mm,mrks_pos,ID)

# Save numpy array of displacement
np.save('data_%i'%ID, relative_disp_mm)

plot_disp(relative_disp_mm, fps, ID)
plt.show()

References:

Garrido-Jurado et al., Pattern Recognition 2016; Generation of fiducial marker dictionaries using Mixed Integer Linear Programming.

https://www.sciencedirect.com/science/article/pii/S0031320315003544

Tocci et al., IOP 2021; ArUco marker-based displacement measurement technique: uncertainty analysis.

https://iopscience.iop.org/article/10.1088/2631-8695/ac1fc7/meta