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https://github.com/danilosalvati/imagestolarmodel.jl
https://github.com/danilosalvati/imagestolarmodel.jl
Last synced: 4 days ago
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- Host: GitHub
- URL: https://github.com/danilosalvati/imagestolarmodel.jl
- Owner: danilosalvati
- License: mit
- Created: 2015-10-17T23:30:09.000Z (over 9 years ago)
- Default Branch: master
- Last Pushed: 2016-01-25T15:51:52.000Z (almost 9 years ago)
- Last Synced: 2024-11-15T20:12:42.159Z (2 months ago)
- Language: TeX
- Size: 12.6 MB
- Stars: 0
- Watchers: 2
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# ImagesToLARModel.jl
Installation
------
Pkg.clone("git://github.com/sadan91/ImagesToLARModel.jl.git")
This module require an installation of python with scipy and numpy for the denoising filter
Use
------
#### Data preparation
using(ImagesToLARModel)
prepareData()
or:
using(ImagesToLARModel)
prepareData(, [, , , ])
This is an example of a valid JSON configuration file:
{
"inputDirectory": "Path of the input directory",
"outputDirectory": "Path of the output directory",
"crop": List with values for images resizing (they can be extended or cropped),
"noise_shape": A number which indicates the intensity of the denoising
filter (0 if you want to disable denoising),
"threshold": A number indicating the chosen threshold for data
"threshold3d": A number indicating the chosen threshold for the
three-dimensional filter (0 if you want to disable this filter)
"zDim": A number indicating the number of images computed at once from the
three-dimensional filter (0 if you want to take the entire stack)
}
For example we can write:
{
"inputDirectory": "/home/juser/IMAGES/",
"outputDirectory": "/home/juser/OUTPUT/",
"crop": [[1,800],[1,600],[1,50]],
"noise_shape": 0,
"threshold": 8,
"threshold3d": 100,
"zDim":0
}
These are the accepted parameters:
- inputDirectory: Directory containing the stack of images
- outputDirectory: Directory containing the output
- crop: Parameter for images resizing (they can be extended or cropped)
- noise_shape: Intensity of the denoising filter for images (0 if you want to disable it)
- threshold: Set a threshold for raw data. Pixels under that threshold will be
set to black, otherwise they will be set to white. If threshold
is not specified, segmentation will be done using a clustering algorithm
- threshold3d: set a threshold for the three-dimensional filter
- zDim: set the number of images computed at once from the three-dimensional filter
#### Data conversion
using(ImagesToLARModel)
convertImagesToLARModel()
or:
using(ImagesToLARModel)
convertImagesToLARModel(, , , , [, , ])
This is an example of a valid JSON configuration file:
{
"inputDirectory": "Path of the input directory",
"outputDirectory": "Path of the output directory",
"nx": border x,
"ny": border y,
"nz": border z,
"DEBUG_LEVEL": julia Logging level
"parallelMerge": "true" or "false",
}
For example we can write:
{
"inputDirectory": "/home/juser/IMAGES/",
"outputDirectory": "/home/juser/OUTPUT/",
"nx": 2,
"ny": 2,
"nz": 2,
"DEBUG_LEVEL": 2
}
These are the accepted parameters:
- inputDirectory: Directory containing the stack of images
- outputDirectory: Directory containing the output
- nx, ny, nz: Border dimensions
- DEBUG_LEVEL: Debug level for [Julia logger](https://github.com/kmsquire/Logging.jl). It can be one of the following:
- DEBUG (1 for JSON configuration file)
- INFO (2 for JSON configuration file)
- WARNING (3 for JSON configuration file)
- ERROR (4 for JSON configuration file)
- CRITICAL (5 for JSON configuration file)
- parallelMerge: Choose if you want to merge model files using a distribuite algorithm or not (experimental)