Configuration Options

Most of the example applications provided can be configured from command line arguments, as described in the Tutorial section. Some applications, like source finding, however, require a large set of configuration options, specified inside a configuration file, passed to the application as a command line argument --config=[FILE].

In this section we report a list of the main configuration options defined in CAESAR to customize tasks. The full list of options defined is kept in ConfigParser.cc class. To print the full list of defined options use the ConfigParser::PrintOptions() method. For example from ROOT prompt type:

Caesar::ConfigParser::Instance().PrintOptions()

or from the python CLI:

from ROOT import gSystem
gSystem.Load('libCaesar')
from ROOT import Caesar

Caesar.ConfigParser.Instance().PrintOptions()

Input Options

These options enable control of input data to be given to CAESAR applications.

Option

Description

Default

Values

inputFile

Input image filename (.root/.fits)

“”

inputImage

Image name to be read in input ROOT file

“”

readTileImage

Read sub-image
If false read the entire image

false

true
false

tileMinX

Min image x pixel coordinate to be read
Used only when readTileImage is true

0

tileMaxX

Max image x pixel coordinate to be read
Used only when readTileImage is true

0

tileMinY

Min image y pixel coordinate to be read
Used only when readTileImage is true

0

tileMinY

Max image y pixel coordinate to be read
Used only when readTileImage is true

0

Output Options

These options enable control of information & data reported in output by CAESAR applications.

Option

Description

Default

Values

saveToFile

Save results & maps to output
ROOT file

true

true
false

saveConfig

Save config options to output
ROOT file

true

true
false

saveSources

Save sources to output ROOT
file

true

true
false

saveInputMap

Save input map to output
ROOT file

false

true
false

saveBkgMap

Save computed background map
to output ROOT file

true

true
false

saveNoiseMap

Save computed rms map
to output ROOT file

true

true
false

saveResidualMap

Save computed residual map
to output ROOT file

true

true
false

saveSignificanceMap

Save computed significance map
to output ROOT file

true

true
false

saveSaliencyMap

Save computed saliency map
to output ROOT file

true

true
false

saveSegmentedMap

Save computed segmented map
to output ROOT file

true

true
false

outputFile

Name of ROOT file where to
store output data (images,
run config, sources, etc)

output.root

saveToCatalogFile

Save island and fitted
components to ascii files

true

true
false

outputCatalogFile

Name of ascii file where to
store source catalog

catalog.dat

outputComponentCatalogFile

Name of ascii file where to
store fitted source component
catalog

catalog_fitcomp.dat

saveDS9Region

Save sources & fit components
to DS9 region files

true

true
false

ds9RegionFile

Name of DS9 region file where
to store source catalog

ds9.reg

ds9FitRegionFile

Name of ascii file where to
store source fitted components

ds9_fitcomp.reg

convertDS9RegionsToWCS

Store DS9 regions in WCS
coordinates

false

true
false

ds9WCSType

DS9 region WCS type to be used
if convertDS9RegionsToWCS=true

0

0=J2000
1=B1950
2=GAL

ds9RegionFormat

Shape to be used to store
source islands in DS9 region

2

1=ellipse
2=polygon

saveToFITSFile

Save output data images to
FITS files

false

true
false

inputMapFITSFile

Name of FITS file where
to store input map read

input.fits

bkgMapFITSFile

Name of FITS file where
to store computed bkg map

bkg.fits

noiseMapFITSFile

Name of FITS file where
to store computed rms map

rms.fits

significanceMapFITSFile

Name of FITS file where to
store computed significance map

significance.fits

residualMapFITSFile

Name of FITS file where
to store computed residual map

residual.fits

saliencyMapFITSFile

Name of FITS file where
to store computed saliency map

saliency.fits

Run & Distributed Processing Options

These options enable control of application run (e.g. logging levels) and distributed processing (e.g. number of threads).

Option

Description

Default

Values

logLevel

Log level threshold

INFO

DEBUG
INFO
WARN
ERROR
FATAL

nThreads

Number of threads used if
OPENMP is enabled. If set to
-1 a number of threads equal
to the available cores is used

-1

splitInTiles

Split input image in tiles
for parallel processing

false

true
false

tileSizeX

Size of tile in pixels along X
coordinate used for partition

1000

tileSizeY

Size of tile in pixels along Y
coordinate used for partition

1000

useTileOverlap

Enable tile overlap in image
partition for parallel
processing

false

true
false

tileStepSizeX

Tile overlap fraction along
X coordinate to partition the
input image for parallel
processing (1=no overlap,
0.5=half overlap)

1

tileStepSizeY

Tile overlap fraction along
Y coordinate to partition the
input image for parallel
processing (1=no overlap,
0.5=half overlap)

1

mergeSourcesAtEdge

Merge overlapping sources
found at tile edge by each
worker when aggregating the
final catalog

true

true
false

mergeSources

Merge overlapping sources
found in each tile. If true
compact and extended sources
found by different algorithms
in a tile are merged if
overlapping. If you want to
keep sources distinct set
option to false

false

true
false

Stats & Background Compute Options

These options enable control of image background calculation. Background can be either computed globally or locally. Local background maps (bkg, rms) are obtained by interpolating background estimator values computed on a grid of sampling image rectangular boxes.

Option

Description

Default

Values

bkgEstimator

Stat estimator used to compute
image background & noise
image background & noise
image background & noise

2

1=Mean/RMS
2=Median/MAD
3=BiWeight
4=Clipped Median/RMS

useParallelMedianAlgo

Use C++ parallel algorithm
to compute median estimator

true

true
false

useLocalBkg

Compute local background
and noise maps and use them
instead of global bkg info

true

true
false

use2ndPassInLocalBkg

Use 2nd pass to refine local
noise map

true

true
false

skipOutliersInLocalBkg

Exclude pixels belonging to
detected bright blobs when
computing local background
estimators. Blob find seed thr
parameters are reported in
source finding option table
below

false

true
false

boxSizeX

Size of sampling box along x
coordinate for local bkg
calculation in pixels. Size is
instead assumed as multiple of
beam size if
useBeamInfoInBkg is true

20

boxSizeY

Size of sampling box along y
coordinate for local bkg
calculation in pixels. Size is
instead assumed as multiple of
beam size if
useBeamInfoInBkg is true

20

gridSizeX

Size of grid along x
coordinate used for local bkg
interpolation expressed as
fraction of sampling box x
size

0.2

gridSizeY

Size of grid along y
coordinate used for local bkg
interpolation expressed as
fraction of sampling box y
size

0.2

sourceBkgBoxBorderSize

Border pad size in pixels of
box around source bounding box
used to estimate bkg for
fitting

20

useBeamInfoInBkg

Use beam information in bkg
sampling box size definition.
Beam info are taken from image
when available, otherwise from
user beam parameter below.

true

true
false

pixSize

User-supplied map pixel area
in arcsec. Used when CDELT
info is not available in
image metadata

1

beamFWHM

User-supplied circular beam
FWHM in arcsec (BMAJ=BMIN).
Used when beam info is not
available in image metadata

6.5

beamBmaj

User-supplied beam ellipse
major axis in arcsec.
Used when beam info is not
available in image metadata

10

beamBmin

User-supplied beam ellipse
minor axis in arcsec.
Used when beam info is not
available in image metadata

5

beamTheta

User-supplied beam position
angle in degrees and measured
CCW from North (pa=0 North).
Used when beam info is not
available in image metadata

0

Source Finding Options

These options enable control of source detection. This is performed using a flood-fill algorithm aggregating pixels around significant seeds if above a given merge threshold. Detected blobs form a collection of candidate sources.

Option

Description

Default

Values

searchCompactSources

Enable/disable search of
compact sources

true

true
false

minNPix

Minimum number of pixels
to consider a blob as source
candidate

5

seedThr

Seed threshold in blob finding
given as number of sigmas
above background

5

mergeThr

Merge/aggregation threshold
in blob finding given as
number of sigmas above
background. Pixels above this
threshold are added to the blob

2.6

mergeBelowSeed

Add to blob only pixels above
merge threshold but below seed
threshold

false

true
false

searchNegativeExcess

Search for holes (i.e. blobs
with negative significance)
along with “positive” blobs

false

true
false

compactSourceSearchNIters

Number of iterations to be
performed in compact source
search. At each iteration the
seed threshold is decreased by
seedThrStep

1

seedThrStep

Seed threshold decrease step
size between iterations.
Effective only when
compactSourceSearchNIters>1

0.5

Nested Source Finding Options

These options enable control of nested source detection. Nested sources are blobs inside another mother blobs. Detection of nested blob uses a blob detection algorithm, based on the thresholding of a filter blob map (LoG or Gaus2D smoothed), which increases the computation time, particularly if blob search is done at multiple spatial scales. In presence of extended/diffuse object you can consider turning off this calculation. If however you have extended and bright object and you turn off nested source search you may see that compact/point-source located inside the extended one will be included in the mother and not fitted.

Option

Description

Default

Values

searchNestedSources

Enable/disable search of
compact nested sources

true

true
false

blobMaskMethod

Filter map used in nested
blob finder to search blobs

2

1=gaus smoothed Lapl
2=multi-scale LoG

nestedBlobKernFactor

Filter kernel size factor par
so that kern size=
factor x sigma (sigma is the
filter scale par in pixels)

6

sourceToBeamAreaThrToSearchNested

Mother source area/beam thr to
add nested sources. If
npix<=thr*beamArea no nested
sources are added to the
mother source even if detected.
If thr=0 nested sources are
always added if
searchNestedSources is
enabled

10

nestedBlobThrFactor

Threshold factor param used in
blob filter map to create mask
(thr=thrFactor*<img>).

0

minNestedMotherDist

Minimum distance in pixels
(in x or y) between nested and
parent blob centroids below
which nested source is skipped
as most probably equal to the
parent (avoid duplicates)

2

maxMatchingPixFraction

Maximum fraction of matching
pixels between nested and
parent blob above which nested
is skipped as most probably
equal to the parent (avoid
duplicates)

0.5

nestedBlobPeakZThr

Nested blob significance
seed thr in sigmas (in filter
blob map) below which nested
blob is skipped

5

nestedBlobPeakZMergeThr

Nested blob peak significance
merge thr in sigmas (in filter
blob map) below which nested
blob is skipped

2.5

nestedBlobMinScale

Nested blob min search scale
factor parameter so that blob
filter scale in pixels is
= scaleFactor x beam width

1

nestedBlobMaxScale

Nested blob max search scale
factor parameter so that blob
filter scale in pixels is
= scaleFactor x beam width

3

nestedBlobScaleStep

Nested blob scale factor step
so that scaleFactor=
minScaleFactor + step

1

Source Selection Options

These options enable control of quality selection cuts applied to detected blobs to select good source candidates and tag point-source candidates (used later in source residual map and fitting stage). Options are also provided to select sources to be stored in the final catalog.

Option

Description

Default

Values

applySourceSelection

Enable/disable source
selection

true

true
false

useMinBoundingBoxCut

Apply minimum bounding box cut
to detected blobs

false

true
false

sourceMinBoundingBox

Minimum bounding box cut value
in pixel. Blobs with minimum
bounding box size below the
threshold are tagged as bad

2

useCircRatioCut

Apply cut on blob circular
ratio param to detected blobs

false

true
false

psCircRatioThr

Circular ratio cut value.
in pixel. Blobs with circ
ratio above this threshold
passed the point-like cut
(1=circle, 0=line)

0.4

0 1

useElongCut

Apply cut on blob elongation
param to detected blobs

false

true
false

psElongThr

Elongation cut value.
Blobs with elongation param
below this threshold
passed the point-like cut

0.7

0 1

useMaxNPixCut

Apply cut on blob maximum
number of pixels.

false

true
false

psMaxNPix

Max number of pixels cut value.
Blobs with a number of pixels
below this threshold
passed the point-like cut

1000

useEllipseAreaRatioCut

Apply cut on ratio between
blob area and blob ellipse
bounding box area.

false

true
false
psEllipseAreaRatioMinThr
psEllipseAreaRatioMaxThr
Area/EllipseArea ratio min and
max cut values.
Blobs in cut range passes the
point-like cut

0.6 1.4

useNBeamsCut

Apply cut on number of beams
found in detected blob
(NBeams=blob npix/beam npix)

false

true
false

psNBeamsThr

Max number of beams cut value.
Blobs with a number of beams
below this threshold
passed the point-like cut

10

Source Fitting Options

These options enable control of source fitting stage: minimization algorithm and relative parameters, starting parameters and limits, etc.

Option

Description

Default

Values

fitSources

Enable/disable source
fitting stage

false

true
false

fitUseThreads

Split source fitting among
multiple threads. Multithread
is not supported by Minuit
minimizer

false

true
false

fitScaleDataToMax

Scale source flux data to max
peak flux if true, otherwise
scale to mJy units

false

true
false

fitMinimizer

Minimizer used in source
fitting

Minuit2

Minuit
Minuit2

fitMinimizerAlgo

Minimization algorithm used in
source fitting

minimize

migrad
simplex
scan
minimize
fumili

fitPrintLevel

Minimizer printout level

1

fitStrategy

Minimizer strategy parameter
(larger means more accurate
minimization but more fcn
calls)

2

fitFcnTolerance

Fit function minimization
tolerance (smaller means more
accurate minimization but more
fcn calls)

1.e-2

fitMaxIters

Maximum number of iterations
that can be done by minimizer
before giving up and returning
not converged fit

100000

fitImproveConvergence

Try to improve convergence by
iterating fit if not converged
or converged with pars at
limits

true

true
false

fitNRetries

Number of times fit is
repeated (with enlarged
limits) if improve convergence
flag is enabled

1000

fitParBoundIncreaseStepSize

Par bound rel increase step
size set when trying to improve
convergence:
parmax= parmax_old+(1+nretry)*
fitParBoundIncreaseStepSize
*0.5*|max-min|

0.1

fitDoFinalMinimizerStep

If enabled run HESSE minimizer
at convergence to improve
minimum and par error estimate
limits

true

true
false

fitRetryWithLessComponents

If fit fails to converge,
repeat it iteratively with one
component less at each cycle
until convergence or until no
more components are available

true

true
false

nBeamsMaxToFit

Maximum number of beams
for a compact source to be
fitted (if above this threshold
the fit is not performed)

20

fitUseNestedAsComponents

If true use nested sources
(if any) as starting fit
components, otherwise estimate
blended components in blob
using a peak finding +
segmentation algorithm

false

true
false

fitMaxNComponents

Maximum number of components
fitted in a blob

5

peakMinKernelSize

Minimum dilation kernel size
in pixels used to detect start
fit components

3

peakMaxKernelSize

Maximum dilation kernel size
in pixels used to detect start
fit components

7

peakKernelMultiplicityThr

Requested peak multiplicity
across different dilation
kernels. A multiplicity=-1
imposes that a peak must be
found in all given dilation
kernels (within a tolerance)
to be considered a component

1

peakShiftTolerance

Peak max position offset in
pixels above which two peaks
are considered distincs.
Used to compare peaks found
in different dilation kernels

2

peakZThrMin

Minimum peak flux significance
(in nsigmas wrt source avg
bkg and rms) below which peak
is skipped and not considered
as a fit component

1

fitWithCentroidLimits

Apply limits to source
centroid pars in fit

true

true
false

fixCentroidInPreFit

Fix source centroid pars
in pre-fit

false

true
false

fitCentroidLimit

Source centroid par limits
given as max offset in pixel
with respect to starting fit
centroid pars

3

fitWithFixedBkg

Fix bkg level par in fit

true

true
false

fitWithBkgLimits

Apply limits to bkg level par
in fit

true

true
false

fitUseEstimatedBkgLevel

Use estimated (avg bkg) as
starting bkg level par in fit

true

true
false

fitUseBkgBoxEstimate

Use bkg estimated in a box
around source (if available)
as bkg level par in fit

true

true
false
false

fitBkgLevel

Starting bkg level par in fit
(used when option
fitParBoundIncreaseStepSize is
false

0

fitWithAmplLimits

Apply limits to amplitude par
in fit

true

true
false

fixAmplInPreFit

Fix amplitude par in pre-fit

true

true
false

fitAmplLimit

Amplitude par limit given as
max relative offset with
respect to starting source
component peak
Speak*(1+-fitAmplLimit))

0.3

fitWithSigmaLimits

Apply limits to sigma pars
in fit

true

true
false

fixSigmaInPreFit

Fix sigma pars in pre-fit

false

true
false

fitSigmaLimit

Sigma par limit given as max
relative offset with respect
to starting component sigma
pars

0.3

fitWithFixedSigma

Fix sigma pars in fit

false

true
false

fitWithThetaLimits

Apply limits to theta par
in fit

true

true
false

fixThetaInPreFit

Fix theta par in pre-fit

false

true
false

fitWithFixedTheta

Fix theta par in fit

false

true
false

fitThetaLimit

Theta par limit given as max
offset in degrees with respect
to starting component theta
par

5

useFluxZCutInFit

If enabled only blob pixels
above a significance threshold
are included in chi2. Pixels
below threshold are included
in a regularization chi2 term

false

true
false

fitZCutMin

Blob significance
threshold below which pixels
are included in the
regularization chi2 term but
not in the chi2

2.5

fitChi2RegPar

Fit chi2 regularization par
so that total chi2 is given by
chi2(Z>thr)+regPar*chi2(Z<thr)

0

Source Fit Selection Cuts

These options enable control of source fit selection cuts. These cuts are used to assign flag to source fitted components.

Option

Description

Default

Values

fitApplyRedChi2Cut

Apply fit Chi2/NDF cut.
Used to set fit quality flag.
If Chi2/NDF>cut the good fit
cut is not passed

true

true
false

fitRedChi2Cut

Chi2/NDF cut value

5

fitApplyFitEllipseCuts

Apply fit ellipse selection
cuts. Used to set component
flags. If not passed, fit
component is tagged as fake

false

true
false

fitEllipseEccentricityRatioMinCut

Ellipse eccentricity ratio
(fit/beam) min cut value

0.5

fitEllipseEccentricityRatioMaxCut

Ellipse eccentricity ratio
(fit/beam) max cut value

1.5

fitEllipseAreaRatioMinCut

Ellipse area ratio
(fit/beam) min cut value

0.01

fitEllipseAreaRatioMaxCut

Ellipse area ratio
(fit/beam) max cut value

10

fitEllipseRotAngleCut

Ellipse rot angle diff
(|fit-beam|) cut value
in degrees

45

Source Residual Options

These options enable control of source residual map. Residual map is made by removing and/or subtracting detected sources from the input map. Source removal is done by replacing source pixel flux values (along with surrounding pixel around them, controlled by a dilation filter) with a residual model value, chosen among: average estimated background, median of source pixels. Residual model value can be randomized if desired. Source removal is controlled by two significance thresholds. Sources with fluxes above the higher threshold are removed regardless of any other conditions (e.g. on source type, etc). Sources with fluxes above the lower threshold (but below the higher threshold) are removed conditionally on chosen source type assigned in the finding process (e.g. point-like, compact, extended). Sources tagged as point-like can be removed with two different algorithms. The first one is described above and consists of replacing source pixel values by model values. The second method uses source fit model (if available) and subtract flux model from the input image. Removal of sources with nested components is controlled by the removeNestedSources flag. If enabled, the removal/subtraction process is done on nested sources and not on parent source pixels. On the contrary, sources are removed as described above and nested sources are removed, being part of the parent.

Option

Description

Default

Values

computeResidualMap

Compute compact source
residual map (after compact
source search)

false

true
false

residualZHighThr

High source significance
threshold (in nsigmas wrt bkg)
used to remove sources

10

residualZThr

Source significance
threshold (in nsigmas wrt bkg)
used to remove sources

5

removeNestedSources

Remove nested sources instead
of parent source
is not supported by Minuit
minimizer

true

true
false

dilateKernelSize

Dilation filter kernel size in
pixels used to remove sources.
NB: Must be an odd number >1
This option controls the halo
size around source to be
removed

9

removedSourceType

Type of sources to be removed
threshold (in nsigmas wrt bkg)
used to remove sources

2

-1=all types
1=compact
2=point-like
3=extended

residualModel

Residual model used to replace
source pixel values

1

1=bkg
2=source median

residualModelRandomize

Randomize residual model pixel
values

false

true
false

psSubtractionMethod

Method used to subtract point
sources

1

1=model removal
2=fit model subtract

Extended Source Finding Options

These options enable control of extended source search. Specific options for the available algorithms are reported in the Tables below. Superpixel Hierarchical Clustering algorithm is not currently available (not ported yet from CAESAR old repository).

Option

Description

Default

Values

searchExtendedSources

Enable/disable search of
extended sources after compact
source finding

false

true
false

extendedSearchMethod

Extended source search method



4

1=Wavelet Transform
2=SP Hier Clustering
3=Active Contour
4=Saliency Filter

useResidualInExtendedSearch

Use residual map as input for
extended source search
source finding

true

true
false

usePreSmoothing

Apply smoothing to residual
map before performing extended
source finding

true

true
false

smoothFilter

Filter used to smooth residual
map

2

1=gaus
2=guided

gausFilterKernSize

Gaussian filter kernel size
in pixels. NB: Must be an odd
value

5

gausFilterSigma

Gaussian filter sigma par
in pixels

1

guidedFilterRadius

Guided filter radius par
in pixels

12

guidedFilterColorEps

Guided filter epsilon par
(regularization parameter)

0.04

Wavelet Transform Algorithm Options

These options enable control of extended source search with the Wavelet Transform method.

Option

Description

Default

Values

wtScaleSearchMin

Minimum Wavelet scale to be
used for extended source
search

3

wtScaleSearchMax

Maximum Wavelet scale to be
used for extended source
search

6

Active Contour Algorithm Options

These options enable control of extended source search with the Active Contour method. Two algorithms are provided: Chan-Vese, Linear Region-based Active Contour (LRAC).

Option

Description

Default

Values

acMethod

Active contour method

1

1=Chan-Vese
2=LRAC

acNIters

Maximum number of iterations

1000

acInitLevelSetMethod

Level set initialization
method

1

1=circle
2=checkerboard
3=saliency

acInitLevelSetSizePar

Level set size fraction wrt
to minimum image size (e.g.
circle radius=fraction x image
size)

0.1

acTolerance

Tolerance parameter to stop
main iteration loop

0.1

0
1

cvNItersInner

Number of iteration done in
inner cycle in Chan-Vese algo

5

cvNItersReInit

Number of iteration done in
re-initialization step in
Chan-Vese algo

5

cvTimeStepPar

Chan-Vese time step par

0.007

cvWindowSizePar

Chan-Vese window size par

1

cvLambda1Par

Chan-Vese lambda1 par

1

cvLambda2Par

Chan-Vese lambda2 par

2

cvMuPar

Chan-Vese mu par

0.5

cvNuPar

Chan-Vese nu par

0

cvPPar

Chan-Vese p par

1

lracLambdaPar

LRAC regularization par

0.1

lracRadiusPar

LRAC radius of locatization
ball par

10

lracEpsPar

LRAC convergence par

0.01

Saliency Filtering Algorithm Options

These options enable control of extended source search with the Saliency Filtering method.

Option

Description

Default

Values

spBeta

Superpixel regularization
parameter

1

spMinArea

Superpixel min area
parameter in pixels

10

saliencyResoMin

Superpixel min scale par in
pixels used in multi-scale
saliency calculation

20

saliencyResoMax

Superpixel max scale par in
pixels used in multi-scale
saliency calculation

60

saliencyResoStep

Superpixel scale step par in
pixels used in multi-scale
saliency calculation

10

saliencyNNFactor

Fraction of most similar
superpixel neighbors used
in saliency map computation

0.2

0
1

saliencyUseRobustPars

Use robust stats pars in
saliency map computation

false

true
false

saliencyDissExpFalloffPar

Superpixel dissimilarity
exponential decay parameter
used in saliency map
computation

100

saliencySpatialDistRegPar

Regularization parameter
controlling superpixel
spatial-intensity balance in
in distance measure used for
saliency map computation
(1 means equal weights)

1

saliencyMultiResoCombThrFactor

Fraction of resolution
scales required
above threshold to
consider a pixel salient.
If set to 1 a pixel is
considered salient if its
saliency value at all
scales is above threshold

0.7

0
1

saliencyUseBkgMap

Add background map to
total saliency map

false

true
false

saliencyUseNoiseMap

Add noise map to
total saliency map

false

true
false

saliencyThrFactor

Saliency threshold factor
parameter. Threshold is
computed as:
thr=<saliency>*factor
(<saliency> is the median)
if saliencyUseOptimalThr
disabled

2.8

saliencyUseOptimalThr

Use optimal threshold in
multiscale saliency
thresholding. If true the
threshold is computed as
max(min(otsuThr,valleyThr),
medianThr)

true

true
false

saliencyImgThrFactor

Threshold factor on input
map to consider a pixel as
salient. Threshold is set as
thr=<img>*factor (<img> is
the median). Pixel below
threshold are not set as
salient even if saliency is
above saliency threshold

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