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Package for 3D reconstruction of Fringe Patterns captured using the Fringe Projection - Laser Induced Fluorescence technique.

Project description

Fringe Pattern to 3D python

This is a python package for applying phase demodulation and 3D reconstruction as post processing of Fringe Pattern (FP) images recorded using the Fringe Projection - Laser Induced Fluorescence (FP-LIF) technique. The package has been developed at the division of Combustion Physics at Lund University and a more detailed explanation of the technique is found in the article cited below. For any questions and code errors please contact adrian.roth@forbrf.lth.se.

Installation through pip

pip install fp23dpy

Usage

Either

python3 -m pf23dpy <FP-image>

or

fp23d <FP-image>

can be used that will by default write a 3D reconstruction GL Transmission Format file .glb that can be imported into most 3D modelling software, for example babylonjs. Other 3D file formats are supported with --ext <extension> flag such as .stl or obj. Use python -m pf23dpy -h for more information of the behaviour of the program.

Examples of a pending drop 3D structure is found in the example folder of the source code. To print example FP image in the examples directory run,

python example_drop.py

which will produce an FP image segmentation file and a calibration file as explained below. Then try,

python -m pf23dpy example_drop.png

open the produced reconstructed_example_drop.glb in a 3D modelling program.

Calibration

A calibration file can be used for each FP-LIF image, the program will try to calibrate from the given image but it is not as robust as doing it yourself. The calibration filename is either calibration_<FP-image-filename>.txt or calibration.txt where this calibration will be default for the whole directory. The file should include a JSON format object with the following attributes:

{
	"T":     float,		 # describing the fringe pattern period length of a plane 3D object
	"gamma": float,		 # float describing the angle in degrees of the fringe pattern in the image
	"theta": float,	 	 # the angle in degrees from the camera to the illumination direction (optional)
	"scale": float,  	 # scale of the image, number of pixels per meter (optional, will scale output to pixels otherwise)
	"phi":   float,	 	 # the rotation in degrees of the camera in spherical coordinates to the angle of the fringe pattern with a certain radius (optional)
	"Tlim":  list of floats  # suggestion of T limits to search within, will not always be respected (optional)
}

The script fp23d calibrate <calibration-image> can be used for easier calculation of T and theta from a calibration image.

Segmentation

If only parts of the image has the required Fringe Pattern lines, which is the case example drop, a segmentation of the image should be produced as found for the example drop. The segmented file should have filename segmented_<FP-image-filename>. If a single segmentation file should be used for all FP images in the same directory the segmentation file can be called segmentation.png. The file should have zero values for background pixels and non-zero for foreground pixels.

Citation

A. Roth and E. Berrocal. 3D surface reconstruction of liquid structures in sprays using structured illumination and phase demodulation. In International Laser and Spray Systems Conference (ILASS), 2019.

Bibtex

@inproceedings{Roth:2019,
author = {A. Roth and E. Berrocal},
title = {3{D} surface reconstruction of liquid structures in sprays using structured illumination and phase demodulation},
booktitle = {International Laser and Spray Systems Conference (ILASS)},
year = {2019},
}

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