Dataset for "Flat-field and colour correction for the Raspberry Pi camera module"

This repository contains the hardware (OpenSCAD/STL files) and build instructions, software (Python scripts and Arduino firmware), data analysis (iPython notebook), and manuscript describing how to calibrate the colour response of a Raspberry Pi camera module. It also includes the calibration images acquired during the preparation of the work.

Subjects:
Optics, photonics and lasers

Cite this dataset as:
Bowman, R., Stirling, J., Collins, J., Vodenicharski, B., 2020. Dataset for "Flat-field and colour correction for the Raspberry Pi camera module". Bath: University of Bath Research Data Archive. Available from: https://doi.org/10.15125/BATH-00764.

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Data

data.zip
application/zip (288MB)
Creative Commons: Attribution 4.0

Calibration images acquired with the apparatus.

Code

image_acquisition.zip
application/zip (12kB)
Software: GNU GPL 3.0

Code used to acquire the images on a Raspberry Pi

analysis.zip
application/zip (3MB)
Software: GNU GPL 3.0

Analysis and plotting code, in Python and iPython notebooks

picamera-1.13.1b0.zip
application/zip (35MB)
Software: GNU GPL 3.0

Snapshot of the source code of the modified picamera library required by this dataset. From https://github.com/rwb27/picamera/releases

picamera-1.13.1b0 … any(1).whl
application/zip (161kB)
Software: GNU GPL 3.0

Compiled Python "wheel" of the modified picamera library, from https://github.com/rwb27/picamera/releases

neopixel_driver.zip
application/zip (1kB)
Software: GNU GPL 3.0

Arduino firmware to drive the NeoPixel LED

recalibrate_utils.py
text/x-python (8kB)
Software: GNU GPL 3.0

Example code taken from the OpenFlexure Microscope software, showing flat-field calibration of the Raspberry Pi camera module.

GitLab repository with the dynamic version of this data

Github repository containing the forked "picamera" library used in the paper

Creators

Richard Bowman
University of Bath

Joel Collins
University of Bath

Boyko Vodenicharski
University of Cambridge

Contributors

University of Bath
Rights Holder

Documentation

Data collection method:

Images were acquired using a Raspberry Pi and camera module, controlled by the included Python scripts.

Technical details and requirements:

A Python 3 environment with numpy, scipy, pillow, and other libraries as detailed in the ipython notebook. The acquisition code will only run on a Raspberry Pi computer with the forked picamera library as described in the manuscript.

Additional information:

- `analysis` contains the data analysis code. - `data` contains the images that we used for the graphs in the manuscript. - `neopixel_driver` is the arduino firmware. - `image_acquisition` includes the Python code that acquired the images and controlled the neopixel. - `calibration_jig` contains the printable files, source OpenSCAD files, and assembly instructions for the calibration jig. - `colour_test_sheet` contains source Inkscape SVG files and PDF renders of the test target used in the experiments. - `manuscript` contains the source files for the manuscript.

Documentation Files

calibration_jig.zip
application/zip (44MB)
Creative Commons: Attribution 4.0

Assembly instructions for the calibration jig used in the paper.

colour_test_sheet.zip
application/zip (13kB)
Creative Commons: Attribution 4.0

The colour test target images used in the accompanying paper.

README.md
text/plain (1kB)
Creative Commons: Attribution 4.0

Readme file, in MarkDown format

calibration_jig_combined.pdf
application/pdf (22MB)
Creative Commons: Attribution 4.0

A compiled PDF version of the assembly instructions for the calibration jig. This was generated from the files contained in calibration_jig.zip, which is also where the STL files can be found. An interactive HTML version of these instructions is maintained at https://bath_open_instrumentation_group.gitlab.io/picamera_cra_compensation/

Additional Metadata

okh-calibration_jig.yml
text/plain (4kB)
Creative Commons: Attribution 4.0

Open Know-How manifest for the calibration jig

Funders

Engineering and Physical Sciences Research Council
https://doi.org/10.13039/501100000266

GCRF - Open Lab Instrumentation
EP/P029426/1

Engineering and Physical Sciences Research Council
https://doi.org/10.13039/501100000266

Detailed Malaria Diagnostics with Intelligent Microscopy
EP/R013969/1

Engineering and Physical Sciences Research Council
https://doi.org/10.13039/501100000266

Automated microscopy for high-throughput malaria research.
EP/R011443/1

UR Fellowship - Robotic microscopy for globally accessible science & healthcare
URF\R1\180153

Robotic microscopy for globally accessible science and healthcare
RGF\EA\181034

Publication details

Publication date: 2 April 2020
by: University of Bath

Version: 1

DOI: https://doi.org/10.15125/BATH-00764

URL for this record: https://researchdata.bath.ac.uk/id/eprint/764

Related papers and books

Bowman, R. W., Vodenicharski, B., Collins, J. T., and Stirling, J., 2020. Flat-Field and Colour Correction for the Raspberry Pi Camera Module. Journal of Open Hardware, 4(1). Available from: https://doi.org/10.5334/joh.20.

Contact information

Please contact the Research Data Service in the first instance for all matters concerning this item.

Departments:

Faculty of Science
Physics

Research Centres & Institutes
Centre for Photonics and Photonic Materials