NaturalHistoryMuseum/gouda

Name: gouda

Owner: Natural History Museum

Description: Reading barcodes in complex images

Created: 2015-03-20 10:05:36.0

Updated: 2018-03-27 07:15:08.0

Pushed: 2016-12-21 09:04:16.0

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Size: 8959

Language: Python

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README

gouda

A python package for decoding barcodes, possibly more than one, in complex images such as scans of museum specimens.

Gouda supports Python 2.7, 3.4 and 3.5. A universal wheel build is available on the releases page.

A command-line program decode_barcodes is available for Windows 64-bit and Mac OS X. It reads barcode values in individual images and in batches of images files in a directory. It can print values to CSV and can rename files with the value(s) or barcode(s). Download from the releases page. For help run

decode_barcodes --help

See also the examples below.

gouda/engines

An engine is an interface to a barcode reading library. Gouda has engines for a number of open-source and commercial libraries.

Open source
Commercial

Not all libraries are available on all OSes. Gouda engines are currently hard-coded to detect either Data Matrix or Code 128 + Code 39 barcodes - those used by the Natural History Musem.

gouda/strategies

No engines are capable of reliably locating and decoding (possibly multiple) barcodes. Gouda provides two strategies to help the decoding engines. If strategy A finds no barcodes, strategy B is attempted.

Installation

Python

TODO These instructions need updating for Python 3. The easiest way is to install the current Python 2.7 release of Anaconda:

conda update --all
pip install --upgrade pip
pip install -r requirements.pip
conda install pywin32=220
FOR /F %a IN ('python -c "import sys; print(sys.exec_prefix)"') DO %a\python %a\Scripts\pywin32_postinstall.py -install
Install OpenCV
Linux
conda install -c https://conda.binstar.org/menpo opencv
OS X
conda install -c https://conda.binstar.org/jjhelmus opencv
Windows

Download OpenCV 2.4.13 and extract to c:\opencv\ If you installed 32-bit Anaconda:

FOR /F %a IN ('python -c "import sys; print(sys.exec_prefix)"') DO copy C:\opencv\build\python\2.7\x86\cv2.pyd %a\DLLs

If you installed 64-bit Anaconda:

FOR /F %a IN ('python -c "import sys; print(sys.exec_prefix)"') DO copy C:\opencv\build\python\2.7\x64\cv2.pyd %a\DLLs

Test by start Anaconda prompt and running

python -c "import cv2; print cv2"
Install decoders
Accusoft

Windows only. Download and install their SDK.

DataSymbol

Windows only. Download and install their SDK.

DTK

Windows 32-bit only. You must run 32-bit Python. Download and install their SDK.

Inlite

Windows only. Download and install their SDK.

libdmtx

The pylibdmtx Python package is a dependency of gouda and is listed in requirements.pip.

The libdmtx DLLs are included with the Windows Python wheel builds of pylibdmtx. On other operating systems, you will need to install the libdmtx shared library.

Linux

Install the libdmtx shared lib.

sudo apt-get install libdmtx0a
OS X

Install the libdmtx shared lib.

brew install libdmtx
Softek

Linux, OS X and Windows. Download and install their SDK.

If on OS X or Linux, set SOFTEK_BARDECODE in gouda/config.py to the path to the bardecode app provided with the SDK.

Enter your licence key in SOFTEK_LICENSE_KEY in gouda/config.py.

Windows

You may need to install the Visual C++ Redistributable Packages for Visual Studio 2013 before registering the COM controls.

You may need to use 'Run As Administrator' when registering the controls.

Stecos

Tested on OS X only. Download and install their SDK.

On OS X:

sudo cp ScMac64SDK/bin/*dylib /usr/lib/

Alter the readDM and readbar programs to print decoded data in the form 'TYPE:DATA\n' and recompile them. If on OS X or Linux, set STECOS_DMREAD and STECOS_READBAR in gouda/config.py to the paths to the readDM and readbar apps respectively, provided with the SDK.

zbar

The pyzbar Python package is a dependency of gouda and is listed in requirements.pip.

The zbar DLLs are included with the Windows Python wheel builds of pyzbar. On other operating systems, you will need to install the zbar shared library.

Linux 
sudo apt-get install libzbar-dev
Mac

Install the zbar library

brew install zbar
Test 
python -c "import zbar; print(zbar)"
zxing

Install a JDK.

cd gouda/java/decode_data_matrix/
./build.sh
Unit tests
nosetests
decode_barcodes script

These examples illustrate running the script from source. If you downloaded decode_barcodes you should replace python -m gouda.scripts.decode_barcodes with decode_barcodes in the following examples.

Print values of all 1d (Code 128) barcodes using the zbar library:
python -m gouda.scripts.decode_barcodes zbar gouda/tests/test_data/code128.png
gouda/tests/test_data/code128.png
Found [1] barcodes:
[0] [CODE128] [b'Stegosaurus']
A terse (file per line) report of two files:
python -m gouda.scripts.decode_barcodes zbar --action terse gouda/tests/test_data/code128.png gouda/tests/test_data/BM001128287.jpg
gouda/tests/test_data/BM001128287.jpg [b'BM001128287'] [b'BM001128286'] [b'BM001128288']
gouda/tests/test_data/code128.png [b'Stegosaurus']
A rich csv report (file per line):
python -m gouda.scripts.decode_barcodes zbar --action csv gouda/tests/test_data/code128.png gouda/tests/test_data/BM001128287.jpg
OS,Engine,Directory,File,Image.conversion,Elapsed,N.found,Types,Values,Strategy
darwin,zbar,test_data,BM001128287.jpg,Unchanged,0.7893128395080566,3,CODE128|CODE128|CODE128,BM001128287|BM001128286|BM001128288,resize: scaling factor [1.0] sharpening [0]
darwin,zbar,test_data,code128.png,Unchanged,0.7991600036621094,1,CODE128,Stegosaurus,resize: scaling factor [1.0] sharpening [0]
Reading images as greyscale

Greyscale can improve or degrade chances of finding barcodes, dependent upon the image and engine.

python -m gouda.scripts.decode_barcodes zbar --action csv --greyscale gouda/tests/test_data/code128.png gouda/tests/test_data/BM001128287.jpg
OS,Engine,Directory,File,Image.conversion,Elapsed,N.found,Types,Values,Strategy
darwin,zbar,test_data,BM001128287.jpg,Greyscale,0.9049880504608154,3,CODE128|CODE128|CODE128,BM001128287|BM001128286|BM001128288,resize: scaling factor [1.0] sharpening [0]
darwin,zbar,test_data,code128.png,Greyscale,0.9112460613250732,1,CODE128,Stegosaurus,resize: scaling factor [1.0] sharpening [0]
Building a release

Mac OS X

./build.sh

On Windows

build.bat
This work is supported by the National Institutes of Health's National Center for Advancing Translational Sciences, Grant Number U24TR002306. This work is solely the responsibility of the creators and does not necessarily represent the official views of the National Institutes of Health.