Command line scripts¶
Automatic orientation of intensity image¶
Automatic orientation of object in images.
usage: orientation [-h] [--extra_channels EXTRA_CHANNELS [EXTRA_CHANNELS ...]]
[--regexp_channels REGEXP_CHANNELS]
[--out_suffix OUT_SUFFIX] [--format FORMAT]
[--output_path OUTPUT_PATH]
[--log_level {ERROR,WARNING,NOTSET,CRITICAL,DEBUG,INFO}]
images [images ...]
Positional Arguments¶
- images
list of images filename to orient.
Extra channels options¶
- --extra_channels
list of extra channels to orient, limit to one image as first argument!.
- --regexp_channels
the position of the variable character in file names to define extra-channel.
output arguments¶
- --out_suffix
suffix to add to the file prior to saving.
Default: “-auto_rotated”
- --format
if specified, may change the output image format.
- --output_path
if specified, change the output path.
logging arguments¶
- --log_level
Possible choices: ERROR, WARNING, NOTSET, CRITICAL, DEBUG, INFO
logging level to use, ‘INFO’ by default.
Default: “INFO”
Orient the object along its main axes.
Image resampling¶
Resampling an image allow to change its voxelsize and shape using interpolation methods while preserving the image physical extent.
usage: resampling [-h] [--label | --linear] [-p OUTPUT_PATH] [-f FORMAT]
[-r REPLACE REPLACE]
[--log_level {ERROR,WARNING,NOTSET,CRITICAL,DEBUG,INFO}]
images [images ...] voxelsize [voxelsize ...]
Positional Arguments¶
- images
image or list of images to resample.
- voxelsize
voxelsize or list voxelsize for each axis.
Named Arguments¶
- --label
use it to resample labelled images, change the interpolation method to ‘nearest’.
Default: False
- --linear
use it with intensity images, change the interpolation method to ‘linear’ instead of ‘cubic-spline’.
Default: False
output arguments¶
- -p, --output_path
if specified, change the output path. Make sure it is empty as it could overwrite the files!
- -f, --format
if specified, change the output image format.
- -r, --replace
if specified, replace the string in output image format.Should be made of two parts, the chain to replace and the replacement.
logging arguments¶
- --log_level
Possible choices: ERROR, WARNING, NOTSET, CRITICAL, DEBUG, INFO
logging level to use, ‘INFO’ by default.
Default: “INFO”
Pay attention to the type of image you are interpolating, intensity or labelled, as it modify the information contained in the image depending on the selected method!
Multi-angle images manual landmarks definition¶
Manually place landmarks for multi-angles fusion initialisation.
usage: multiangle_initialisation [-h] [-d DATASET] [-t TIME_INDEX]
[--channel CHANNEL] [-o OUT_DATASET]
[--log_level {ERROR,WARNING,NOTSET,CRITICAL,DEBUG,INFO}]
json
Positional Arguments¶
- json
a JSON file containing the metadata and locations of the required dataset.
Named Arguments¶
- -d, --dataset
the dataset to use as intensity image input for fusion algorithm, ‘raw’ by default.
Default: “raw”
- -t, --time_index
the time-index of the multi-angles image used in fusion procedure, all of them by default.
Default: []
multichannel image arguments¶
- --channel
channel to use with a multichannel image.
output arguments¶
- -o, --out_dataset
the dataset name to use to save landmarks files, ‘multiangle_landmarks’ by default.
Default: “multiangle_landmarks”
logging arguments¶
- --log_level
Possible choices: ERROR, WARNING, NOTSET, CRITICAL, DEBUG, INFO
logging level to use, ‘INFO’ by default
Default: “INFO”
Multi-angle images fusion¶
Performs multi-angle images registration and fusion
usage: multiangle_fusion [-h] [-d DATASET] [-t TIME_INDEX] [--manual_init]
[--n_iter N_ITER [N_ITER ...]]
[--average_method {mean,robust-mean,median,minimum,maximum,quantile,sum,var,stddev}]
[--super_resolution] [--global_averaging]
[--last_non_linear] [--py_ll PY_LL [PY_LL ...]]
[--channel CHANNEL] [--ext EXT]
[--out_dataset OUT_DATASET]
[--log_level {ERROR,WARNING,NOTSET,CRITICAL,DEBUG,INFO}]
json
Positional Arguments¶
- json
a JSON file containing the metadata and locations of the required dataset.
Named Arguments¶
- -d, --dataset
the dataset to use as intensity image input for multi-angles image fusion procedure, ‘raw’ by default.
Default: “raw”
- -t, --time_index
the time-index of the multi-angles image used in fusion procedure, all of them by default.
Default: []
fusion arguments¶
- --manual_init
add this option to use prior manual definition of landmarks with multiangle_initialisation.py.
Default: False
- --n_iter
number of iterations to performs when fusing multi-angle images, default is 2.
Default: 2
- --average_method
Possible choices: mean, robust-mean, median, minimum, maximum, quantile, sum, var, stddev
averaging method to use when fusing multi-angle images, default is mean.
Default: [‘mean’, ‘robust-mean’, ‘median’, ‘minimum’, ‘maximum’, ‘quantile’, ‘sum’, ‘var’, ‘stddev’]
- --super_resolution
creates a super-resolution image when fusing multi-angle images at last step.
Default: False
- --global_averaging
perform global averaging of each voxel by the total number of images, else use mask for local averaging.
Default: False
- --last_non_linear
perform non-linear registration at last iteration step, else only rigid and affine registrations are used.
Default: False
- --py_ll
use this to control the pyramid lowest level for block-matching, 2 by default.
Default: 2
multichannel image arguments¶
- --channel
channel to use with a multichannel image.
output arguments¶
- --ext
extension used to save fused images, ‘tif’ by default.
Default: “tif”
- --out_dataset
export fused images in a ‘fusion’ dataset.
Default: “fusion”
logging arguments¶
- --log_level
Possible choices: ERROR, WARNING, NOTSET, CRITICAL, DEBUG, INFO
logging level to use, ‘INFO’ by default.
Default: “INFO”
Sequence registration¶
Sequence registration of a time-series.
Sequence registration is a (temporal) forward registration of all images of a time series onto the last one.
Use image I[t] (image at time t) as float and image I[N] as reference, with N
the index of the last image of the temporal sequence.
It allows to obtain a sequence fully registered on the same template, i.e. same image frame (shape, extent, …).
This tool will produce the following data:
a series of sequence transformations allowing registration of I[t] onto I[N] frame (saved under the trsf_dataset location).
a series of sequence registered images, that is I[t] registered onto I[N] frame (saved under the out_dataset location).
This tool will produce the following figure:
a set of “original” projections for the time-series
a set of “registered” projections for the time-series
Note that the “rigid” part of the transformations is always saved. Except for the figures, the produced data is automatically referenced in the JSON file.
usage: sequence_registration [-h] [-int INTENSITY_DATASET]
[-seg SEGMENTATION_DATASET] [-trsf TRSF_DATASET]
[--channel CHANNEL] [--orientation {1,-1}]
[--registration_type {similitude,rigid,affine,vectorfield}]
[--proj_method {contour,background,maximum,average,minimum,max,mean,min}]
[--ext EXT] [--out_dataset OUT_DATASET] [--force]
[--log_level {ERROR,WARNING,NOTSET,CRITICAL,DEBUG,INFO}]
json
Positional Arguments¶
- json
a JSON file containing the metadata and locations of the required dataset.
Named Arguments¶
- -int, --intensity_dataset
name of the dataset containing the intensity images, ‘raw’ by default.
Default: “raw”
- -seg, --segmentation_dataset
the dataset containing the segmented image on which to project the dataset, ‘watershed_segmentation’ by default.
Default: “watershed_segmentation”
- -trsf, --trsf_dataset
name of the dataset containing the transformations, ‘trsf’ by default.
Default: “trsf”
images arguments¶
- --channel
channel to register, mandatory for multichannel images.
- --orientation
Possible choices: 1, -1
image orientation, use -1 with an inverted microscope, 1 by default.
Default: 1
registration arguments¶
- --registration_type
Possible choices: similitude, rigid, affine, vectorfield
type of registration to performs, ‘rigid’ by default.
Default: “rigid”
- --force
force computation of transformations.
Default: False
figure arguments¶
- --proj_method
Possible choices: contour, background, maximum, average, minimum, max, mean, min
projection method to use. ‘contour’ (default) works well with cell walls/membranes. ‘maximum’ works well with nuclei.
Default: “contour”
output arguments¶
- --ext
file extension of registered images, ‘tif’ by default.
Default: “tif”
- --out_dataset
export images in ‘temporal_registration’ dataset
Default: “temporal_registration”
logging arguments¶
- --log_level
Possible choices: ERROR, WARNING, NOTSET, CRITICAL, DEBUG, INFO
logging level to use, ‘INFO’ by default.
Default: “INFO”