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.
An engine is an interface to a barcode reading library. Gouda has engines for a number of open-source and commercial libraries.
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.
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.
- Strategy A - shrink image until a barcode is found
- this algorithm exits as soon as one or more barcodes are reported by the
engine:
- Present the image to the decoding library at 100%, 95%, 90%, 85%...5% of its original size
- Sharpen the image and repeat 1
- Sharpen the image even more and repeat 1
- Strategy B
- Use OpenCV to identify areas of the image that might contain barcodes
- Present each candidate area to the engines
- this algorithm exits as soon as one or more barcodes are reported by the
engine:
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
conda install -c https://conda.binstar.org/menpo opencv
conda install -c https://conda.binstar.org/jjhelmus opencv
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"
Windows only. Download and install their SDK.
Windows only. Download and install their SDK.
Windows 32-bit only. You must run 32-bit Python. Download and install their SDK.
Windows only. Download and install their SDK.
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.
Install the libdmtx shared lib.
sudo apt-get install libdmtx0a
Install the libdmtx shared lib.
brew install libdmtx
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.
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.
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.
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.
sudo apt-get install libzbar-dev
Install the zbar library
brew install zbar
python -c "import zbar; print(zbar)"
Install a JDK.
cd gouda/java/decode_data_matrix/
./build.sh
nosetests
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.
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']
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']
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]
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]
Mac OS X
./build.sh
On Windows
build.bat