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.
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.
Export
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
Julian Stirling
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 (EPSRC)
https://doi.org/10.13039/501100000266
Open Lab Instrumentation
EP/P029426/1
Engineering and Physical Sciences Research Council (EPSRC)
https://doi.org/10.13039/501100000266
Detailed Malaria Diagnostics with Intelligent Microscopy
EP/R013969/1
Engineering and Physical Sciences Research Council (EPSRC)
https://doi.org/10.13039/501100000266
Automated microscopy for high-throughput malaria research.
EP/R011443/1
Royal Society
https://doi.org/10.13039/501100000288
UR Fellowship - Robotic microscopy for globally accessible science & healthcare
URF\R1\180153
Royal Society
https://doi.org/10.13039/501100000288
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.
Faculty of Science
Physics
Research Centres & Institutes
Centre for Photonics and Photonic Materials
