From 9b264e6b8126ec0ef0ca3141f21bd19ae159bf73 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Fabian=20K=C3=BCppers?= Date: Thu, 29 Apr 2021 15:09:43 +0200 Subject: [PATCH] Update copyright note --- README.rst | 6 +++--- docs/build/html/.buildinfo | 2 +- .../_autosummary_binning/netcal.binning.BBQ.html | 2 +- .../_autosummary_binning/netcal.binning.ENIR.html | 2 +- .../netcal.binning.HistogramBinning.html | 4 ++-- .../netcal.binning.IsotonicRegression.html | 2 +- .../_autosummary_metric/netcal.metrics.ACE.html | 4 ++-- .../_autosummary_metric/netcal.metrics.ECE.html | 4 ++-- .../_autosummary_metric/netcal.metrics.MCE.html | 4 ++-- .../netcal.presentation.ReliabilityDiagram.html | 4 ++-- .../netcal.regularization.confidence_penalty.html | 2 +- .../netcal.scaling.BetaCalibration.html | 4 ++-- .../netcal.scaling.BetaCalibrationDependent.html | 4 ++-- .../netcal.scaling.LogisticCalibration.html | 4 ++-- .../netcal.scaling.LogisticCalibrationDependent.html | 4 ++-- .../netcal.scaling.TemperatureScaling.html | 4 ++-- docs/build/html/_autosummary/netcal.binning.html | 2 +- docs/build/html/_autosummary/netcal.metrics.html | 2 +- docs/build/html/_autosummary/netcal.presentation.html | 2 +- docs/build/html/_autosummary/netcal.regularization.html | 2 +- docs/build/html/_autosummary/netcal.scaling.html | 2 +- .../netcal.AbstractCalibration.html | 2 +- docs/build/html/genindex.html | 2 +- docs/build/html/index.html | 8 ++++---- docs/build/html/py-modindex.html | 2 +- docs/build/html/search.html | 2 +- docs/build/html/searchindex.js | 2 +- docs/source/conf.py | 6 +++--- examples/__init__.py | 4 ++-- examples/classification/CIFAR.py | 4 ++-- examples/classification/Evaluation.py | 4 ++-- examples/classification/__init__.py | 4 ++-- examples/classification/utils.py | 4 ++-- examples/detection/artificial/Calibration.py | 4 ++-- examples/detection/artificial/CreateDataset.py | 4 ++-- examples/detection/artificial/Evaluation.py | 4 ++-- examples/detection/artificial/__init__.py | 4 ++-- examples/detection/artificial/toolchain.py | 4 ++-- examples/detection/mscoco/Evaluation.py | 4 ++-- netcal/AbstractCalibration.py | 4 ++-- netcal/Decorator.py | 4 ++-- netcal/Logging.py | 4 ++-- netcal/__init__.py | 4 ++-- netcal/binning/BBQ.py | 4 ++-- netcal/binning/ENIR.py | 4 ++-- netcal/binning/HistogramBinning.py | 6 +++--- netcal/binning/IsotonicRegression.py | 4 ++-- netcal/binning/NearIsotonicRegression.py | 4 ++-- netcal/binning/__init__.py | 4 ++-- netcal/metrics/ACE.py | 6 +++--- netcal/metrics/ECE.py | 6 +++--- netcal/metrics/MCE.py | 6 +++--- netcal/metrics/Miscalibration.py | 6 +++--- netcal/metrics/__init__.py | 4 ++-- netcal/presentation/ReliabilityDiagram.py | 6 +++--- netcal/presentation/__init__.py | 4 ++-- netcal/regularization/ConfidencePenalty.py | 4 ++-- netcal/regularization/__init__.py | 4 ++-- netcal/scaling/BetaCalibration.py | 6 +++--- netcal/scaling/BetaCalibrationDependent.py | 6 +++--- netcal/scaling/LogisticCalibration.py | 6 +++--- netcal/scaling/LogisticCalibrationDependent.py | 6 +++--- netcal/scaling/TemperatureScaling.py | 6 +++--- netcal/scaling/__init__.py | 4 ++-- setup.py | 4 ++-- 65 files changed, 130 insertions(+), 130 deletions(-) diff --git a/README.rst b/README.rst index 10de734..a44546a 100644 --- a/README.rst +++ b/README.rst @@ -3,8 +3,8 @@ Calibration Framework Calibration framework in Python 3 for Neural Networks. For full API reference documentation, visit https://fabiankueppers.github.io/calibration-framework. -Copyright (C) 2019-2020 Ruhr West University of Applied Sciences, Bottrop, Germany -AND Visteon Electronics Germany GmbH, Kerpen, Germany +Copyright (C) 2019-2021 Ruhr West University of Applied Sciences, Bottrop, Germany +AND Elektronische Fahrwerksysteme GmbH, Gaimersheim, Germany This Source Code Form is subject to the terms of the Mozilla Public License, v. 2.0. If a copy of the MPL was not distributed with this @@ -233,4 +233,4 @@ References .. [9] Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M. and Duchesnay, E.: "Scikit-learn: Machine Learning in Python." In Journal of Machine Learning Research, volume 12 pp 2825-2830, 2011. .. [10] Platt, John: "Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods." Advances in large margin classifiers, 10(3): 61–74, 1999. .. [11] Neumann, Lukas, Andrew Zisserman, and Andrea Vedaldi: "Relaxed Softmax: Efficient Confidence Auto-Calibration for Safe Pedestrian Detection." Conference on Neural Information Processing Systems (NIPS) Workshop MLITS, 2018. -.. [12] Fabian Küppers, Jan Kronenberger, Amirhossein Shantia and Anselm Haselhoff: "Multivariate Confidence Calibration for Object Detection"." The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, in press, 2020 +.. [12] Fabian Küppers, Jan Kronenberger, Amirhossein Shantia and Anselm Haselhoff: "Multivariate Confidence Calibration for Object Detection"." The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2020 diff --git a/docs/build/html/.buildinfo b/docs/build/html/.buildinfo index 5a190de..515f083 100644 --- a/docs/build/html/.buildinfo +++ b/docs/build/html/.buildinfo @@ -1,4 +1,4 @@ # Sphinx build info version 1 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done. -config: 5be3a53f752ff4e87c219f0d2ef49b4a +config: 78e6332c97a52e1ea66f816824406211 tags: 645f666f9bcd5a90fca523b33c5a78b7 diff --git a/docs/build/html/_autosummary/_autosummary_binning/netcal.binning.BBQ.html b/docs/build/html/_autosummary/_autosummary_binning/netcal.binning.BBQ.html index c15a7fd..16e9055 100644 --- a/docs/build/html/_autosummary/_autosummary_binning/netcal.binning.BBQ.html +++ b/docs/build/html/_autosummary/_autosummary_binning/netcal.binning.BBQ.html @@ -354,7 +354,7 @@

Navigation

diff --git a/docs/build/html/_autosummary/_autosummary_binning/netcal.binning.ENIR.html b/docs/build/html/_autosummary/_autosummary_binning/netcal.binning.ENIR.html index 2f9b3fd..b859cb4 100644 --- a/docs/build/html/_autosummary/_autosummary_binning/netcal.binning.ENIR.html +++ b/docs/build/html/_autosummary/_autosummary_binning/netcal.binning.ENIR.html @@ -355,7 +355,7 @@

Navigation

diff --git a/docs/build/html/_autosummary/_autosummary_binning/netcal.binning.HistogramBinning.html b/docs/build/html/_autosummary/_autosummary_binning/netcal.binning.HistogramBinning.html index 51ef053..a204644 100644 --- a/docs/build/html/_autosummary/_autosummary_binning/netcal.binning.HistogramBinning.html +++ b/docs/build/html/_autosummary/_autosummary_binning/netcal.binning.HistogramBinning.html @@ -93,7 +93,7 @@

netcal.binning.HistogramBinning3

Fabian Küppers, Jan Kronenberger, Amirhossein Shantia and Anselm Haselhoff: “Multivariate Confidence Calibration for Object Detection.” -The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2020, in press.

+The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops.

Methods

@@ -367,7 +367,7 @@

Navigation

diff --git a/docs/build/html/_autosummary/_autosummary_binning/netcal.binning.IsotonicRegression.html b/docs/build/html/_autosummary/_autosummary_binning/netcal.binning.IsotonicRegression.html index b7c39ff..0d32efe 100644 --- a/docs/build/html/_autosummary/_autosummary_binning/netcal.binning.IsotonicRegression.html +++ b/docs/build/html/_autosummary/_autosummary_binning/netcal.binning.IsotonicRegression.html @@ -329,7 +329,7 @@

Navigation

diff --git a/docs/build/html/_autosummary/_autosummary_metric/netcal.metrics.ACE.html b/docs/build/html/_autosummary/_autosummary_metric/netcal.metrics.ACE.html index 132ee42..ce137e1 100644 --- a/docs/build/html/_autosummary/_autosummary_metric/netcal.metrics.ACE.html +++ b/docs/build/html/_autosummary/_autosummary_metric/netcal.metrics.ACE.html @@ -83,7 +83,7 @@

netcal.metrics.ACE2

Fabian Küppers, Jan Kronenberger, Amirhossein Shantia and Anselm Haselhoff: “Multivariate Confidence Calibration for Object Detection.” -The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2020, in press.

+The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops.

Methods

@@ -212,7 +212,7 @@

Navigation

diff --git a/docs/build/html/_autosummary/_autosummary_metric/netcal.metrics.ECE.html b/docs/build/html/_autosummary/_autosummary_metric/netcal.metrics.ECE.html index 2946453..32740af 100644 --- a/docs/build/html/_autosummary/_autosummary_metric/netcal.metrics.ECE.html +++ b/docs/build/html/_autosummary/_autosummary_metric/netcal.metrics.ECE.html @@ -84,7 +84,7 @@

netcal.metrics.ECE2

Fabian Küppers, Jan Kronenberger, Amirhossein Shantia and Anselm Haselhoff: “Multivariate Confidence Calibration for Object Detection.” -The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2020, in press.

+The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops.

Methods

@@ -213,7 +213,7 @@

Navigation

diff --git a/docs/build/html/_autosummary/_autosummary_metric/netcal.metrics.MCE.html b/docs/build/html/_autosummary/_autosummary_metric/netcal.metrics.MCE.html index af6df98..f0f44c3 100644 --- a/docs/build/html/_autosummary/_autosummary_metric/netcal.metrics.MCE.html +++ b/docs/build/html/_autosummary/_autosummary_metric/netcal.metrics.MCE.html @@ -82,7 +82,7 @@

netcal.metrics.MCE2

Fabian Küppers, Jan Kronenberger, Amirhossein Shantia and Anselm Haselhoff: “Multivariate Confidence Calibration for Object Detection.” -The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2020, in press.

+The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops.

Methods

@@ -214,7 +214,7 @@

Navigation

diff --git a/docs/build/html/_autosummary/_autosummary_presentation/netcal.presentation.ReliabilityDiagram.html b/docs/build/html/_autosummary/_autosummary_presentation/netcal.presentation.ReliabilityDiagram.html index a8d5f62..e472b67 100644 --- a/docs/build/html/_autosummary/_autosummary_presentation/netcal.presentation.ReliabilityDiagram.html +++ b/docs/build/html/_autosummary/_autosummary_presentation/netcal.presentation.ReliabilityDiagram.html @@ -89,7 +89,7 @@

netcal.presentation.ReliabilityDiagram3

Fabian Küppers, Jan Kronenberger, Amirhossein Shantia and Anselm Haselhoff: “Multivariate Confidence Calibration for Object Detection.” -The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2020, in press.

+The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops.

Methods

@@ -209,7 +209,7 @@

Navigation

diff --git a/docs/build/html/_autosummary/_autosummary_regularization_func/netcal.regularization.confidence_penalty.html b/docs/build/html/_autosummary/_autosummary_regularization_func/netcal.regularization.confidence_penalty.html index e4e12ff..0fb8a0b 100644 --- a/docs/build/html/_autosummary/_autosummary_regularization_func/netcal.regularization.confidence_penalty.html +++ b/docs/build/html/_autosummary/_autosummary_regularization_func/netcal.regularization.confidence_penalty.html @@ -134,7 +134,7 @@

Navigation

diff --git a/docs/build/html/_autosummary/_autosummary_scaling/netcal.scaling.BetaCalibration.html b/docs/build/html/_autosummary/_autosummary_scaling/netcal.scaling.BetaCalibration.html index f425aee..2febf42 100644 --- a/docs/build/html/_autosummary/_autosummary_scaling/netcal.scaling.BetaCalibration.html +++ b/docs/build/html/_autosummary/_autosummary_scaling/netcal.scaling.BetaCalibration.html @@ -119,7 +119,7 @@

netcal.scaling.BetaCalibration2

Fabian Küppers, Jan Kronenberger, Amirhossein Shantia and Anselm Haselhoff: “Multivariate Confidence Calibration for Object Detection.” -The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2020, in press.

+The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops.

Methods

@@ -376,7 +376,7 @@

Navigation

diff --git a/docs/build/html/_autosummary/_autosummary_scaling/netcal.scaling.BetaCalibrationDependent.html b/docs/build/html/_autosummary/_autosummary_scaling/netcal.scaling.BetaCalibrationDependent.html index 92a9c0c..ecb290f 100644 --- a/docs/build/html/_autosummary/_autosummary_scaling/netcal.scaling.BetaCalibrationDependent.html +++ b/docs/build/html/_autosummary/_autosummary_scaling/netcal.scaling.BetaCalibrationDependent.html @@ -117,7 +117,7 @@

netcal.scaling.BetaCalibrationDependent1(1,2)

Fabian Küppers, Jan Kronenberger, Amirhossein Shantia and Anselm Haselhoff: “Multivariate Confidence Calibration for Object Detection.” -The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2020, in press.

+The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops.

2

Libby, David L., and Melvin R. Novick: @@ -379,7 +379,7 @@

Navigation

diff --git a/docs/build/html/_autosummary/_autosummary_scaling/netcal.scaling.LogisticCalibration.html b/docs/build/html/_autosummary/_autosummary_scaling/netcal.scaling.LogisticCalibration.html index 6919703..12d11e1 100644 --- a/docs/build/html/_autosummary/_autosummary_scaling/netcal.scaling.LogisticCalibration.html +++ b/docs/build/html/_autosummary/_autosummary_scaling/netcal.scaling.LogisticCalibration.html @@ -120,7 +120,7 @@

netcal.scaling.LogisticCalibration3

Fabian Küppers, Jan Kronenberger, Amirhossein Shantia and Anselm Haselhoff: “Multivariate Confidence Calibration for Object Detection.” -The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2020, in press.

+The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops.

Methods

@@ -377,7 +377,7 @@

Navigation

diff --git a/docs/build/html/_autosummary/_autosummary_scaling/netcal.scaling.LogisticCalibrationDependent.html b/docs/build/html/_autosummary/_autosummary_scaling/netcal.scaling.LogisticCalibrationDependent.html index ed0bd2d..184db6b 100644 --- a/docs/build/html/_autosummary/_autosummary_scaling/netcal.scaling.LogisticCalibrationDependent.html +++ b/docs/build/html/_autosummary/_autosummary_scaling/netcal.scaling.LogisticCalibrationDependent.html @@ -102,7 +102,7 @@

netcal.scaling.LogisticCalibrationDependent1(1,2)

Fabian Küppers, Jan Kronenberger, Amirhossein Shantia and Anselm Haselhoff: “Multivariate Confidence Calibration for Object Detection.” -The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2020, in press.

+The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops.

Methods

@@ -359,7 +359,7 @@

Navigation

diff --git a/docs/build/html/_autosummary/_autosummary_scaling/netcal.scaling.TemperatureScaling.html b/docs/build/html/_autosummary/_autosummary_scaling/netcal.scaling.TemperatureScaling.html index fc09997..ad8a050 100644 --- a/docs/build/html/_autosummary/_autosummary_scaling/netcal.scaling.TemperatureScaling.html +++ b/docs/build/html/_autosummary/_autosummary_scaling/netcal.scaling.TemperatureScaling.html @@ -83,7 +83,7 @@

netcal.scaling.TemperatureScaling2

Fabian Küppers, Jan Kronenberger, Amirhossein Shantia and Anselm Haselhoff: “Multivariate Confidence Calibration for Object Detection.” -The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2020, in press.

+The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops.

Methods

@@ -346,7 +346,7 @@

Navigation

diff --git a/docs/build/html/_autosummary/netcal.binning.html b/docs/build/html/_autosummary/netcal.binning.html index 58d60fd..6eab21b 100644 --- a/docs/build/html/_autosummary/netcal.binning.html +++ b/docs/build/html/_autosummary/netcal.binning.html @@ -134,7 +134,7 @@

Navigation

diff --git a/docs/build/html/_autosummary/netcal.metrics.html b/docs/build/html/_autosummary/netcal.metrics.html index ecf4c09..b3405b1 100644 --- a/docs/build/html/_autosummary/netcal.metrics.html +++ b/docs/build/html/_autosummary/netcal.metrics.html @@ -133,7 +133,7 @@

Navigation

diff --git a/docs/build/html/_autosummary/netcal.presentation.html b/docs/build/html/_autosummary/netcal.presentation.html index b8faac6..20480d0 100644 --- a/docs/build/html/_autosummary/netcal.presentation.html +++ b/docs/build/html/_autosummary/netcal.presentation.html @@ -125,7 +125,7 @@

Navigation

diff --git a/docs/build/html/_autosummary/netcal.regularization.html b/docs/build/html/_autosummary/netcal.regularization.html index 0b77d8d..42d0e84 100644 --- a/docs/build/html/_autosummary/netcal.regularization.html +++ b/docs/build/html/_autosummary/netcal.regularization.html @@ -126,7 +126,7 @@

Navigation

diff --git a/docs/build/html/_autosummary/netcal.scaling.html b/docs/build/html/_autosummary/netcal.scaling.html index 48869c8..095da4e 100644 --- a/docs/build/html/_autosummary/netcal.scaling.html +++ b/docs/build/html/_autosummary/netcal.scaling.html @@ -137,7 +137,7 @@

Navigation

diff --git a/docs/build/html/_autosummary_abstract_calibration/netcal.AbstractCalibration.html b/docs/build/html/_autosummary_abstract_calibration/netcal.AbstractCalibration.html index 66d999e..71827f1 100644 --- a/docs/build/html/_autosummary_abstract_calibration/netcal.AbstractCalibration.html +++ b/docs/build/html/_autosummary_abstract_calibration/netcal.AbstractCalibration.html @@ -351,7 +351,7 @@

Navigation

diff --git a/docs/build/html/genindex.html b/docs/build/html/genindex.html index e1defd7..c0b11b2 100644 --- a/docs/build/html/genindex.html +++ b/docs/build/html/genindex.html @@ -462,7 +462,7 @@

Navigation

diff --git a/docs/build/html/index.html b/docs/build/html/index.html index fe3e231..a2edcba 100644 --- a/docs/build/html/index.html +++ b/docs/build/html/index.html @@ -88,8 +88,8 @@

API ReferenceCalibration Framework

Calibration framework in Python 3 for Neural Networks. For full API reference documentation, visit https://fabiankueppers.github.io/calibration-framework.

-

Copyright (C) 2019-2020 Ruhr West University of Applied Sciences, Bottrop, Germany -AND Visteon Electronics Germany GmbH, Kerpen, Germany

+

Copyright (C) 2019-2021 Ruhr West University of Applied Sciences, Bottrop, Germany +AND Elektronische Fahrwerksysteme GmbH, Gaimersheim, Germany

This Source Code Form is subject to the terms of the Mozilla Public License, v. 2.0. If a copy of the MPL was not distributed with this file, You can obtain one at http://mozilla.org/MPL/2.0/.

@@ -352,7 +352,7 @@

References

Neumann, Lukas, Andrew Zisserman, and Andrea Vedaldi: “Relaxed Softmax: Efficient Confidence Auto-Calibration for Safe Pedestrian Detection.” Conference on Neural Information Processing Systems (NIPS) Workshop MLITS, 2018.

12(1,2,3,4,5,6,7,8,9,10,11,12,13,14)
-

Fabian Küppers, Jan Kronenberger, Amirhossein Shantia and Anselm Haselhoff: “Multivariate Confidence Calibration for Object Detection”.” The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, in press, 2020

+

Fabian Küppers, Jan Kronenberger, Amirhossein Shantia and Anselm Haselhoff: “Multivariate Confidence Calibration for Object Detection”.” The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2020

@@ -430,7 +430,7 @@

Navigation

diff --git a/docs/build/html/py-modindex.html b/docs/build/html/py-modindex.html index 0e8380c..06c0578 100644 --- a/docs/build/html/py-modindex.html +++ b/docs/build/html/py-modindex.html @@ -116,7 +116,7 @@

Navigation

diff --git a/docs/build/html/search.html b/docs/build/html/search.html index 395ae44..fd5a4b4 100644 --- a/docs/build/html/search.html +++ b/docs/build/html/search.html @@ -87,7 +87,7 @@

Navigation

diff --git a/docs/build/html/searchindex.js b/docs/build/html/searchindex.js index da71c38..3f8080b 100644 --- a/docs/build/html/searchindex.js +++ b/docs/build/html/searchindex.js @@ -1 +1 @@ -Search.setIndex({docnames:["_autosummary/_autosummary_binning/netcal.binning.BBQ","_autosummary/_autosummary_binning/netcal.binning.ENIR","_autosummary/_autosummary_binning/netcal.binning.HistogramBinning","_autosummary/_autosummary_binning/netcal.binning.IsotonicRegression","_autosummary/_autosummary_metric/netcal.metrics.ACE","_autosummary/_autosummary_metric/netcal.metrics.ECE","_autosummary/_autosummary_metric/netcal.metrics.MCE","_autosummary/_autosummary_presentation/netcal.presentation.ReliabilityDiagram","_autosummary/_autosummary_regularization_func/netcal.regularization.confidence_penalty","_autosummary/_autosummary_scaling/netcal.scaling.BetaCalibration","_autosummary/_autosummary_scaling/netcal.scaling.BetaCalibrationDependent","_autosummary/_autosummary_scaling/netcal.scaling.LogisticCalibration","_autosummary/_autosummary_scaling/netcal.scaling.LogisticCalibrationDependent","_autosummary/_autosummary_scaling/netcal.scaling.TemperatureScaling","_autosummary/netcal.binning","_autosummary/netcal.metrics","_autosummary/netcal.presentation","_autosummary/netcal.regularization","_autosummary/netcal.scaling","_autosummary_abstract_calibration/netcal.AbstractCalibration","index"],envversion:{"sphinx.domains.c":1,"sphinx.domains.changeset":1,"sphinx.domains.citation":1,"sphinx.domains.cpp":1,"sphinx.domains.index":1,"sphinx.domains.javascript":1,"sphinx.domains.math":2,"sphinx.domains.python":1,"sphinx.domains.rst":1,"sphinx.domains.std":1,sphinx:56},filenames:["_autosummary/_autosummary_binning/netcal.binning.BBQ.rst","_autosummary/_autosummary_binning/netcal.binning.ENIR.rst","_autosummary/_autosummary_binning/netcal.binning.HistogramBinning.rst","_autosummary/_autosummary_binning/netcal.binning.IsotonicRegression.rst","_autosummary/_autosummary_metric/netcal.metrics.ACE.rst","_autosummary/_autosummary_metric/netcal.metrics.ECE.rst","_autosummary/_autosummary_metric/netcal.metrics.MCE.rst","_autosummary/_autosummary_presentation/netcal.presentation.ReliabilityDiagram.rst","_autosummary/_autosummary_regularization_func/netcal.regularization.confidence_penalty.rst","_autosummary/_autosummary_scaling/netcal.scaling.BetaCalibration.rst","_autosummary/_autosummary_scaling/netcal.scaling.BetaCalibrationDependent.rst","_autosummary/_autosummary_scaling/netcal.scaling.LogisticCalibration.rst","_autosummary/_autosummary_scaling/netcal.scaling.LogisticCalibrationDependent.rst","_autosummary/_autosummary_scaling/netcal.scaling.TemperatureScaling.rst","_autosummary/netcal.binning.rst","_autosummary/netcal.metrics.rst","_autosummary/netcal.presentation.rst","_autosummary/netcal.regularization.rst","_autosummary/netcal.scaling.rst","_autosummary_abstract_calibration/netcal.AbstractCalibration.rst","index.rst"],objects:{"":{netcal:[20,0,0,"-"]},"netcal.AbstractCalibration":{clear:[19,2,1,""],epsilon:[19,3,1,""],fit:[19,2,1,""],fit_transform:[19,2,1,""],get_params:[19,2,1,""],load_model:[19,2,1,""],logger:[19,3,1,""],save_model:[19,2,1,""],set_params:[19,2,1,""],squeeze_generic:[19,2,1,""],transform:[19,2,1,""]},"netcal.binning":{BBQ:[0,1,1,""],ENIR:[1,1,1,""],HistogramBinning:[2,1,1,""],IsotonicRegression:[3,1,1,""]},"netcal.binning.BBQ":{clear:[0,2,1,""],fit:[0,2,1,""],fit_transform:[0,2,1,""],get_params:[0,2,1,""],load_model:[0,2,1,""],save_model:[0,2,1,""],set_params:[0,2,1,""],squeeze_generic:[0,2,1,""],transform:[0,2,1,""]},"netcal.binning.ENIR":{clear:[1,2,1,""],fit:[1,2,1,""],fit_transform:[1,2,1,""],get_params:[1,2,1,""],load_model:[1,2,1,""],save_model:[1,2,1,""],set_params:[1,2,1,""],squeeze_generic:[1,2,1,""],transform:[1,2,1,""]},"netcal.binning.HistogramBinning":{clear:[2,2,1,""],fit:[2,2,1,""],fit_transform:[2,2,1,""],get_degrees_of_freedom:[2,2,1,""],get_params:[2,2,1,""],load_model:[2,2,1,""],save_model:[2,2,1,""],set_params:[2,2,1,""],squeeze_generic:[2,2,1,""],transform:[2,2,1,""]},"netcal.binning.IsotonicRegression":{clear:[3,2,1,""],fit:[3,2,1,""],fit_transform:[3,2,1,""],get_params:[3,2,1,""],load_model:[3,2,1,""],save_model:[3,2,1,""],set_params:[3,2,1,""],squeeze_generic:[3,2,1,""],transform:[3,2,1,""]},"netcal.metrics":{ACE:[4,1,1,""],ECE:[5,1,1,""],MCE:[6,1,1,""]},"netcal.metrics.ACE":{measure:[4,2,1,""],squeeze_generic:[4,2,1,""]},"netcal.metrics.ECE":{measure:[5,2,1,""],squeeze_generic:[5,2,1,""]},"netcal.metrics.MCE":{measure:[6,2,1,""],squeeze_generic:[6,2,1,""]},"netcal.presentation":{ReliabilityDiagram:[7,1,1,""]},"netcal.presentation.ReliabilityDiagram":{plot:[7,2,1,""]},"netcal.regularization":{confidence_penalty:[8,4,1,""]},"netcal.scaling":{BetaCalibration:[9,1,1,""],BetaCalibrationDependent:[10,1,1,""],LogisticCalibration:[11,1,1,""],LogisticCalibrationDependent:[12,1,1,""],TemperatureScaling:[13,1,1,""]},"netcal.scaling.BetaCalibration":{clear:[9,2,1,""],fit:[9,2,1,""],fit_transform:[9,2,1,""],get_params:[9,2,1,""],load_model:[9,2,1,""],save_model:[9,2,1,""],set_params:[9,2,1,""],squeeze_generic:[9,2,1,""],transform:[9,2,1,""]},"netcal.scaling.BetaCalibrationDependent":{clear:[10,2,1,""],fit:[10,2,1,""],fit_transform:[10,2,1,""],get_params:[10,2,1,""],load_model:[10,2,1,""],save_model:[10,2,1,""],set_params:[10,2,1,""],squeeze_generic:[10,2,1,""],transform:[10,2,1,""]},"netcal.scaling.LogisticCalibration":{clear:[11,2,1,""],fit:[11,2,1,""],fit_transform:[11,2,1,""],get_params:[11,2,1,""],load_model:[11,2,1,""],save_model:[11,2,1,""],set_params:[11,2,1,""],squeeze_generic:[11,2,1,""],transform:[11,2,1,""]},"netcal.scaling.LogisticCalibrationDependent":{clear:[12,2,1,""],fit:[12,2,1,""],fit_transform:[12,2,1,""],get_params:[12,2,1,""],load_model:[12,2,1,""],save_model:[12,2,1,""],set_params:[12,2,1,""],squeeze_generic:[12,2,1,""],transform:[12,2,1,""]},"netcal.scaling.TemperatureScaling":{clear:[13,2,1,""],fit:[13,2,1,""],fit_transform:[13,2,1,""],get_params:[13,2,1,""],load_model:[13,2,1,""],save_model:[13,2,1,""],set_params:[13,2,1,""],squeeze_generic:[13,2,1,""],temperature:[13,2,1,""],transform:[13,2,1,""]},netcal:{AbstractCalibration:[19,1,1,""],binning:[14,0,0,"-"],metrics:[15,0,0,"-"],presentation:[16,0,0,"-"],regularization:[17,0,0,"-"],scaling:[18,0,0,"-"]}},objnames:{"0":["py","module","Python module"],"1":["py","class","Python class"],"2":["py","method","Python method"],"3":["py","attribute","Python attribute"],"4":["py","function","Python function"]},objtypes:{"0":"py:module","1":"py:class","2":"py:method","3":"py:attribute","4":"py:function"},terms:{"16th":[1,20],"22nd":7,"2nd":19,"34th":[7,11,13,20],"abstract":19,"boolean":[0,1,2,3,9,10,11,12,13,19],"case":[9,11],"class":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,19,20],"default":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,19,20],"float":[4,5,6,7,8,19],"function":[0,1,2,3,7,8,9,10,11,12,13,19],"import":[10,12,20],"int":[0,1,2,3,4,5,6,7,9,10,11,12,13,19],"k\u00fcpper":[2,4,5,6,7,9,10,11,12,13,20],"new":20,"public":20,"return":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,15,19],"true":[0,1,2,3,4,5,6,7,9,10,11,12,13,19,20],ACE:[7,15,16,20],AND:20,Axes:[0,1,2,3,4,5,6,9,10,11,12,13,19],ECE:[4,7,15,16,20],For:[2,9,10,11,12,17,20],Near:[1,20],The:[0,1,2,3,4,5,6,7,9,10,11,12,13,15,19,20],These:[0,1,17,20],Use:17,Using:[0,1,9,11],_miscalibr:[4,5,6],a_k:9,aaai:[0,5,6,20],abl:20,abov:8,abstractcalibr:[0,1,2,3,9,10,11,12,13,20],acc:[4,5,6],accord:[4,5,9,10,11,12,20],accur:[2,3,20],accuraci:[4,5,6,7,14,15,16,18,20],achiev:[17,20],adam:10,added:20,addit:[0,1,2,3,4,5,6,7,9,10,11,12,13,19,20],adjac:1,advanc:[11,20],after:[0,1,2,3,9,10,11,12,13,19],afterward:7,aic:[0,1],aikaik:[0,1],aka:11,akaik:[0,1],algorithm:1,alia:[13,20],all:[0,1,2,4,5,6,7,9,10,11,12,19,20],allow:1,along:20,alpha:[9,10],alpha_0:10,alpha_k:[9,10],also:[4,5,6,9,10,11,12,13,20],altern:13,alwai:[4,5,6],amirhossein:[2,4,5,6,7,9,10,11,12,13,20],amount:[0,2,4,5,6,7,20],andrea:[4,20],andrew:[4,20],ani:[0,1,2,3,8,9,10,11,12,13,19],anoth:20,anselm:[2,4,5,6,7,9,10,11,12,13,20],appli:[2,8,9,10,11,12,13,17,20],applic:[10,20],approx:[0,1,9,10,11,12],approxim:[14,18],arg:7,argument:7,arrai:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,19,20],artifici:[0,5,6,9,20],assess:10,assign:[2,8],assum:[4,5,9,11],ast:10,ast_j:10,attributeerror:[7,19],author:20,auto:[4,9,20],auto_select:9,avail:20,averag:[4,5,6,7,15,20],axes:[0,1,2,3,4,5,6,9,10,11,12,13,19],axes_to_keep:[0,1,2,3,4,5,6,9,10,11,12,13,19],axi:20,b_i:5,b_k:9,background:[9,10,11,12],base:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,19,20],baseestim:19,basic:20,batch:[7,10],bayesian:[0,1,2,5,6,20],bbq:20,bdeu:0,been:20,befor:19,behaviour:20,below:20,best:9,beta:[9,10,20],beta_0:10,beta_k:[9,10],betacalibr:20,betacalibrationdepend:20,between:[4,5,6,7,9,11,15,16,20],bia:11,bianca:[2,3,20],bias:20,bic:[0,1,2],big:10,bigg:[9,10],bin:[4,5,6,7,15,16],binari:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,19,20],blondel:20,booktitl:20,bool:[0,1,2,3,4,5,6,7,9,10,11,12,13,19],both:12,bottrop:20,bound:20,boundari:[2,3],box:[0,1,2,3,4,5,6,7,9,10,11,12,13,19,20],branch:[2,20],brucher:20,build:[0,1,2,3,9,10,11,12,13,19],built:19,calcul:[0,1,4,5,6,7,20],calibr:[0,1,2,3,4,5,6,7,9,10,11,12,13,14,15,17,18,19],calibrated_scor:20,call:[2,19,20],callback:17,can:[0,1,7,8,9,10,11,12,13,19,20],captur:20,caruana:7,center:20,certain:[1,20],charl:[2,3,20],check:19,child:[0,1,2,3,9,10,11,12,13,19],chorowski:[8,20],chosen:2,chuan:[7,11,13,20],cite:20,classic:7,classif:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,19],classifi:[1,2,3,9,10,11,12,20],classmethod:[0,1,2,3,4,5,6,9,10,11,12,13,19],clear:[0,1,2,3,9,10,11,12,13,19],code:20,color:7,combin:[9,10,11,12],command:20,common:[15,20],commonli:20,comparison:[11,20],compat:[10,12],compon:[0,1,2,3,9,10,11,12,13,19],comput:[0,2,4,5,6,7,9,10,11,12,13,19,20],conf:[4,5,6],confer:[0,1,2,4,5,6,7,9,10,11,12,13,20],confid:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20],confidence_penalti:20,conform:11,consecut:1,consist:[9,10,11,12,14,16,18],constant:3,constructor:20,contain:[0,1,2,3,9,10,11,12,13,19,20],contrast:1,convert:19,cooper:[0,1,5,6,20],coordin:7,copi:20,copyright:20,corr:[8,20],correl:20,could:7,counterpart:20,cournapeau:20,covari:12,criterion:[0,1],critic:20,cross:7,crucial:20,current:0,cvf:20,cvpr:[2,4,5,6,7,9,10,11,12,13,20],data:[0,1,2,3,9,10,11,12,13,19,20],david:10,debug:19,decis:[2,20],decompos:12,deep:[0,1,2,3,9,10,11,12,13,19],defin:[0,1,2,3,4,5,6,9,10,11,12,13,19,20],degre:2,deliv:[9,10,11,12],denot:[0,1,4,5,6,9,10,11,12,20],densiti:[9,10,11,12],depend:[10,12,20],describ:10,descript:20,design:20,detail:20,detect:[0,1,2,3,4,5,6,7,9,10,11,12,13,19],determin:[9,11,20],deviat:[15,20],devic:10,diagram:[7,16,20],dict:[0,1,2,3,9,10,11,12,13,19],differ:[0,2,4,5,6,7,20],digit:[19,20],dim:[0,1,2,3,4,5,6,7,9,10,11,12,13,19],dimens:[0,1,2,3,4,5,6,7,9,10,11,12,13,19],directli:[1,12,20],displai:16,distribut:[8,9,10,11,12,20],divid:20,divis:19,document:20,doe:[7,19],done:20,dubourg:20,duchesnai:20,dure:[17,20],dynam:3,each:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,15,16,19,20],easi:20,easili:[9,20],easy:10,ece:20,educ:10,effici:[4,20],either:[0,1,2,3,4,5,6,7,9,10,11,12,13,19,20],elbow:[0,1],electron:20,elkan:[2,3,20],ell:[9,10,11,12],encod:[0,1,2,3,4,5,6,7,9,10,11,12,13,19],enir:20,ensembl:[1,20],entropi:8,epsilon:19,equal:[1,2,4,15,16,20],equal_interv:2,error:[4,5,6,15,19,20],especi:20,estim:[0,1,2,3,9,10,11,12,13,14,17,18,19,20],etc:7,evalu:7,even:[0,1,2,3,4,5,6,9,10,11,12,13,19],everi:20,examin:7,exampl:17,exp:[0,1,9,10,11,12],expect:[5,15,20],express:[9,11],extend:[9,11,20],extens:20,fabian:[2,4,5,6,7,9,10,11,12,13,20],fabiankuepp:20,factor:11,fals:[0,1,2,3,4,5,6,7,9,10,11,12,13,19],featur:[0,1,2,3,4,5,6,7,9,10,11,12,13,19],feature_nam:7,figur:7,file:20,filenam:[0,1,2,3,7,9,10,11,12,13,19],filho:[9,20],first:[9,10,11,12],fit:[0,1,2,3,7,9,10,11,12,13,19,20],fit_param:[0,1,2,3,9,10,11,12,13,19],fit_transform:[0,1,2,3,9,10,11,12,13,19],flach:[9,20],flag:20,fmax:7,fmin:7,follow:20,foral:10,form:[0,1,2,3,9,10,11,12,13,19,20],formul:11,found:[9,20],frac:[4,5,9,10,11,12],framework:[10,12],freedom:2,from:[0,1,2,3,9,10,11,12,13,19,20],full:20,furthermor:20,gap:[7,15,16,20],gener:[9,10,11,12],geoff:[7,11,13,20],germani:20,get:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,19,20],get_degrees_of_freedom:2,get_param:[0,1,2,3,9,10,11,12,13,19],github:20,give:15,given:[0,1,3,4,5,7,9,10,11,12,15,20],gmbh:20,good:7,gramfort:20,gregori:[0,1,5,6,20],grisel:20,ground:[0,1,2,3,4,5,6,7,9,10,11,12,13,19,20],ground_truth:20,group:[1,4,5,6,20],guarante:[12,19],guo:[7,11,13,20],has:[9,10,11,12,19,20],haselhoff:[2,4,5,6,7,9,10,11,12,13,20],hat:[0,1,9,10,11,12,13],hauskrecht:[0,5,6,20],have:[0,1,2,3,4,5,6,7,9,10,11,12,13,19],heatmap:20,height:[7,9,10,11,12],highest:[15,20],hinton:[8,20],histogram:[2,4,5,6,7,20],histogrambin:[0,3,20],hoefl:20,holger:20,hot:[0,1,2,3,4,5,6,7,9,10,11,12,13,19],how:20,howev:[11,20],http:20,icdm:[1,20],icml:[2,20],ieee:[1,2,4,5,6,7,9,10,11,12,13,20],implement:[9,20],improv:[9,19,20],includ:[2,7,20],independ:[0,1,2,3,9,11,13,19],independent_prob:[0,1,2,3,9,11,13,19],indic:[9,10,11,12,20],inequ:19,info:19,inform:[0,1,2,4,7,20],inherit:[19,20],initi:1,inproceed:20,input:[0,1,2,3,4,5,6,7,9,10,11,12,13,19,20],input_calibr:20,insert:[10,12],instanc:[0,1,2,3,7,9,10,11,12,13,17,19],instead:[9,10,11,12],integ:2,intellig:[0,5,6,9,20],intern:[1,7,11,13,20],interpret:[7,9,10,11,12],interv:2,invok:20,iou:20,isoton:[1,3,20],isotonicregress:[1,20],iter:[0,1,2,3,4,5,6,7,9,10,11,12,13,19],its:2,jan:[2,4,5,6,7,9,10,11,12,13,20],jmlr:[7,11,13],john:[11,20],journal:[10,20],june:20,kaiser:[8,20],kdd:[2,3,20],keep:[0,1,2,3,4,5,6,9,10,11,12,13,19],kept:[0,1,2,3,4,5,6,9,10,11,12,13,19],kerpen:20,kilian:[7,11,13,20],kronenberg:[2,4,5,6,7,9,10,11,12,13,20],kueppers_2020_cvpr_workshop:20,kull:[9,20],label:[0,1,2,3,4,5,6,7,9,10,11,12,13,19,20],lambda_j:10,lambda_k:10,larg:[11,20],last:[0,1,2,3,4,5,6,7,9,10,11,12,13,19],latter:[0,1,2,3,9,10,11,12,13,19],learn:[7,10,11,13,20],least:[0,1,2,3,4,5,6,7,9,10,11,12,13,19],led:13,length:[0,1,2,7],less:20,let:[0,1],libbi:10,licens:20,like:[7,19,20],likelihood:[0,1,9,10,11,12,20],list:[0,1,2,3,4,5,6,7,9,10,11,12,13,19],load:[0,1,2,3,9,10,11,12,13,19],load_model:[0,1,2,3,9,10,11,12,13,19],locat:20,log:[0,1,9,10,11,12,19],logarithm:[8,9,10,11,12],logger:19,logist:[9,10,11,12,13,20],logisticcalibr:[13,20],logisticcalibrationdepend:20,logit:[9,10,11,12,13,20],loss:[8,20],low:[0,1],lowest:19,lr_depend:20,luka:[4,20],lukasz:8,machin:[7,11,13,20],mahdi:[0,1,5,6,20],main:4,mandatori:20,manner:2,map:[0,1,2,3,4,5,6,9,10,11,12,13,19,20],margin:[11,20],match:[7,9,10,11,12,19,20],mathbb:[11,12],mathcal:[0,1],mathemat:[9,10,11,12],matplotlib:[7,20],matric:12,matrix:12,max_:6,max_it:10,maximum:[6,7,10,15,20],mce:[7,15,20],mean:[9,10,11,12,15,20],measur:[4,5,6,7,14,15,20],meeli:[9,20],melvin:10,messag:19,method:[0,1,2,3,4,5,6,7,9,10,11,12,13,14,15,16,17,18,19],metric:7,michel:20,might:[0,1,7],milo:[0,5,6,20],mine:[1,20],minimum:7,miscalibr:[4,5,6,7,9,10,11,12,15,16,20],miscellan:20,mizil:7,mlit:[4,20],mode:[2,4,5,6,7,9,11,20],model:[0,1,2,3,9,10,11,12,13,17,19,20],modern:[7,11,13,20],modifi:1,momentum:10,monotoni:1,month:20,more:[7,19,20],most:20,mozilla:20,mpava:1,mpl:20,multi:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,19,20],multiclass:[2,3,9,11,20],multidimension:[2,20],multinomi:9,multipl:[0,1,7,9,11],multivari:[2,4,5,6,7,9,10,11,12,13,20],must:[0,1,2,3,4,5,6,7,9,10,11,12,13,19,20],n_bin:20,n_box_featur:[0,1,2,3,4,5,6,7,9,10,11,12,13,19],n_class:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,19,20],n_featur:[0,1,2,3,9,10,11,12,13,19],n_features_new:[0,1,2,3,9,10,11,12,13,19],n_sampl:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,19,20],naeini:[0,1,5,6,20],naiv:[2,20],name:[0,1,2,3,9,10,11,12,13,19],natur:20,ndarrai:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,19],nearli:20,necessari:[9,10,11,12,20],need:[2,19,20],neither:20,nest:[0,1,2,3,9,10,11,12,13,19],netcal:20,network:[7,8,11,13,20],neumann:[4,20],neural:[4,7,8,11,13,20],niculescu:7,ninth:[0,5,6,20],nip:[4,20],nir:1,none:[0,1,2,3,7,8,9,10,11,12,13,19],nor:20,norm:8,normal:[0,1,2,11,12],notat:10,novick:10,num_sampl:[4,5,6],number:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,15,19],numpi:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,19,20],nx1:[2,4,5,6,7],nx2:[2,4,5,6,7],object:[0,1,2,3,4,5,6,7,9,10,11,12,13,19,20],observ:[7,15,16,18,20],obtain:[0,1,2,5,6,9,10,11,12,17,20],odd:[9,10,11,12],onc:7,one:[0,1,2,3,4,5,6,7,9,10,11,12,13,19,20],onli:[4,5,6,7,9,10,11,12,20],onlin:[0,1,2,3,4,5,6,7,8,9,11,13],oper:[13,19],optim:[9,10,11,12],option:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,19],org:[7,11,13,20],origin:[0,1,2,3,9,10,11,12,13],other:[0,1,2,3,9,11,13,19],out:[0,1],output:[0,1,2,3,8,9,10,11,12,13,19,20],over:[0,1,4,5,6,7,17,20],overconfid:20,own:20,packag:[14,16,18,20],pakdaman:[0,1,5,6,20],paper:0,param:[0,1,2,3,9,10,11,12,13,19],paramet:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,17,19,20],part:[11,20],pass:7,passo:20,pattern:[2,4,5,6,7,9,10,11,12,13,20],pedestrian:[4,20],pedregosa:20,penal:[8,17,20],penalti:[8,17,20],pereyra:[8,20],perform:[13,19,20],perrot:20,peter:[9,20],pickl:[0,1,2,3,9,10,11,12,13,19],piecewis:3,pip3:20,pip:20,pipelin:[0,1,2,3,9,10,11,12,13,19],platt:[11,20],pleas:20,pleiss:[7,11,13,20],plot:[7,20],pmlr:[9,20],pool:1,posit:[9,10,11,12,20],possibl:[0,1,2,3,9,10,11,12,13,19],posterior:[0,1,8,9,10,11,12],prebuild:17,predict:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,17,19,20],prefer:20,preffer:20,present:[0,1,2,3,4,5,6,9,10,11,12,13,19,20],press:[2,4,5,6,7,9,10,11,12,13,20],prettenhof:20,print:19,probabilist:[11,20],probabl:[0,1,2,3,5,6,7,9,10,11,13,19,20],problem:[9,10,11,12],proceed:[7,11,13,20],process:[4,20],prod:10,prohibit:17,properti:[7,13],propos:[0,1,2,3,9,10,11,12,13],propto:[0,1],provid:[7,9,10,11,12,20],purpos:20,pyplot:7,python3:20,python:20,quantil:[0,20],quantiti:20,quick:1,quick_init:1,quit:20,rais:[7,19],rate:10,ratio:[9,10,11,12],readm:20,reason:[10,12],recent:20,recognit:[2,4,5,6,7,9,10,11,12,13,20],refer:[0,1,2,3,4,5,6,7,8,9,10,11,12,13],regress:[1,2,3,7,9,10,11,12,13,20],regular:11,rel:[0,1,20],relative_x_posit:20,relax:[4,20],reliabilitydiagram:20,reliabl:[7,16,20],remain:[4,5,6],remind:20,reparametr:9,requir:12,research:20,respect:[9,10,12],restrict:[1,12],result:7,return_map:[4,5,6],return_num_sampl:[4,5,6],right:20,robert:20,rootlogg:19,ruhr:20,runtimeerror:19,ryan:20,s_k:[9,10],safe:[4,20],safeti:20,same:[2,4,5,6,7,11],sampl:[2,4,5,6,7,9,10,11,12,15,16,20],sample_threshold:[4,5,6,7],save:[0,1,2,3,7,9,10,11,12,13,19],save_arg:7,save_model:[0,1,2,3,9,10,11,12,13,19],savefig:7,scale:7,scheme:[9,10,11,12],scienc:20,scikit:20,scipi:[10,20],scope:20,score:[0,1,2,3,9,10,11,12,20],score_funct:[0,1],second:7,see:20,select:9,self:[0,1,2,3,9,10,11,12,13,19],semidefinit:12,separ:[4,5,6,7,20],set:[0,1,2,3,7,9,10,11,12,13,19],set_param:[0,1,2,3,9,10,11,12,13,19],setup:20,setuptool:20,sever:[0,1,2,3,4,5,6,7,9,10,11,12,13,14,18,19,20],shantia:[2,4,5,6,7,9,10,11,12,13,20],shape:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,19,20],should:[0,1,2,3,4,5,6,7,9,10,11,12,13,17,19,20],shown:20,sigma:12,sigma_:[12,13],sigmoid:[0,1,2,3,9,11,13,19],silva:[9,20],similar:[3,15,16,20],simpl:[0,1,2,3,9,10,11,12,13,19],simpli:[2,11,20],size:[0,1,2,3,4,5,6,9,10,11,12,13,16,19],sklearn:19,snippet:20,softmax:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,19,20],some:20,sort:[0,1,2,3],sourc:[0,1,2,3,4,5,6,7,8,9,11,13,20],space:[7,20],specifii:20,split:2,squeez:[0,1,2,3,4,5,6,9,10,11,12,13,19],squeeze_gener:[0,1,2,3,4,5,6,9,10,11,12,13,19],stack:20,standard:[1,9,10,11],statist:[9,10,20],str:[0,1,2,3,7,9,10,11,12,13,19],string:[0,1,2,3,7,9,10,11,12,13,19],structur:20,subject:20,subobject:[0,1,2,3,9,10,11,12,13,19],suffix:7,suit:20,sum:[0,9,10,20],sum_:[0,1,4,5],sum_k:9,summar:9,sun:[7,11,13,20],supervis:7,support:[0,11,20],symmetr:12,system:[4,20],target:[0,1,2,3,9,10,11,12,13,19],task:[4,5,9,10,11,12,13,20],technometr:20,telmo:[9,20],temperatur:[11,13,20],temperature_onli:11,temperaturesc:20,term:[8,20],text:[4,5,6,9,10,11,12,13],than:[7,19],thei:[0,1,2,3,4,5,6,9,10,11,12,13,19],them:1,therefor:[9,10,11,12],theta:[0,1],thi:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,16,18,19,20],thirion:20,those:[9,10,11,12,20],threshold:8,thu:11,tibshirani:20,time:12,titl:[7,20],title_suffix:7,tool:20,top:[9,10,11,12],torch:20,tqdm:20,train:[0,1,2,3,9,10,11,12,13,17,19,20],transform:[0,1,2,3,9,10,11,12,13,19,20],transformermixin:19,treat:[0,1,2,3,4,5,6,7,9,10,11,12,13,19],tree:[2,20],tri:[10,12],truth:[0,1,2,3,4,5,6,7,9,10,11,12,13,19,20],tucker:[8,20],tupl:[0,1,2,3,4,5,6,7,9,10,11,12,13,19],twenti:[0,5,6,20],two:20,type:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,19],typic:8,uncalibr:[0,1,2,3,9,10,11,12,13,19,20],uncalibrated_scor:20,union:[0,1,2,3,4,5,6,7,9,10,11,12,13,19],univari:[9,11],univers:20,updat:[0,1,2,3,9,10,11,12,13,19],use:[2,4,5,6,7,9,10,11,12,14,18,20],used:[0,1,2,3,4,5,6,7,9,10,11,12,13,19,20],uses:[9,10,11,12,20],using:[0,1,5,6,7,9,11,20],util:[0,9,10,11,20],valid:7,valu:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,19],vanderpla:20,variabl:[9,10,11,12],varianc:11,variant:10,varoquaux:20,vector:[0,1,2,3,4,5,6,7,9,10,11,12,13,19,20],vedaldi:[4,20],version:[0,1,2,3,9,10,11,12,13,19],violat:1,vision:[2,4,5,6,7,9,10,11,12,13,20],visit:20,visteon:20,visual:[7,16],volum:[7,11,13,20],wai:7,want:20,warn:19,weight:[0,1,4,8,15,20],weinberg:[7,11,13,20],weiss:20,well:[0,1,2,3,5,6,9,10,11,12,13,19,20],west:20,where:[4,5,6,9,10,20],wherea:[9,10,11,12],which:[0,9,10,11,12,14,17,18,20],width:[2,7,9,10,11,12],wise:7,work:[0,1,2,3,9,10,11,12,13,19,20],workshop:[2,4,5,6,7,9,10,11,12,13,20],write:20,x_0:[0,1],x_1:[0,1],x_new:[0,1,2,3,9,10,11,12,13,19],y_0:[0,1],y_1:[0,1],year:20,you:20,your:20,zadrozni:[2,3,20],zisserman:[4,20]},titles:["netcal.binning.BBQ","netcal.binning.ENIR","netcal.binning.HistogramBinning","netcal.binning.IsotonicRegression","netcal.metrics.ACE","netcal.metrics.ECE","netcal.metrics.MCE","netcal.presentation.ReliabilityDiagram","netcal.regularization.confidence_penalty","netcal.scaling.BetaCalibration","netcal.scaling.BetaCalibrationDependent","netcal.scaling.LogisticCalibration","netcal.scaling.LogisticCalibrationDependent","netcal.scaling.TemperatureScaling","netcal.binning","netcal.metrics","netcal.presentation","netcal.regularization","netcal.scaling","netcal.AbstractCalibration","API Reference"],titleterms:{"class":[14,15,16,18],"function":17,ACE:4,ECE:5,abstractcalibr:19,api:20,avail:[14,15,16,17,18],bbq:0,betacalibr:9,betacalibrationdepend:10,bin:[0,1,2,3,14,20],calibr:20,classif:20,confidence_penalti:8,content:20,detect:20,enir:1,exampl:20,framework:20,histogrambin:2,instal:20,isotonicregress:3,logisticcalibr:11,logisticcalibrationdepend:12,mce:6,method:20,metric:[4,5,6,15,20],netcal:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19],overview:20,present:[7,16],refer:20,regular:[8,17,20],reliabilitydiagram:7,requir:20,scale:[9,10,11,12,13,18,20],tabl:20,temperaturesc:13,visual:20}}) \ No newline at end of file +Search.setIndex({docnames:["_autosummary/_autosummary_binning/netcal.binning.BBQ","_autosummary/_autosummary_binning/netcal.binning.ENIR","_autosummary/_autosummary_binning/netcal.binning.HistogramBinning","_autosummary/_autosummary_binning/netcal.binning.IsotonicRegression","_autosummary/_autosummary_metric/netcal.metrics.ACE","_autosummary/_autosummary_metric/netcal.metrics.ECE","_autosummary/_autosummary_metric/netcal.metrics.MCE","_autosummary/_autosummary_presentation/netcal.presentation.ReliabilityDiagram","_autosummary/_autosummary_regularization_func/netcal.regularization.confidence_penalty","_autosummary/_autosummary_scaling/netcal.scaling.BetaCalibration","_autosummary/_autosummary_scaling/netcal.scaling.BetaCalibrationDependent","_autosummary/_autosummary_scaling/netcal.scaling.LogisticCalibration","_autosummary/_autosummary_scaling/netcal.scaling.LogisticCalibrationDependent","_autosummary/_autosummary_scaling/netcal.scaling.TemperatureScaling","_autosummary/netcal.binning","_autosummary/netcal.metrics","_autosummary/netcal.presentation","_autosummary/netcal.regularization","_autosummary/netcal.scaling","_autosummary_abstract_calibration/netcal.AbstractCalibration","index"],envversion:{"sphinx.domains.c":1,"sphinx.domains.changeset":1,"sphinx.domains.citation":1,"sphinx.domains.cpp":1,"sphinx.domains.index":1,"sphinx.domains.javascript":1,"sphinx.domains.math":2,"sphinx.domains.python":1,"sphinx.domains.rst":1,"sphinx.domains.std":1,sphinx:56},filenames:["_autosummary/_autosummary_binning/netcal.binning.BBQ.rst","_autosummary/_autosummary_binning/netcal.binning.ENIR.rst","_autosummary/_autosummary_binning/netcal.binning.HistogramBinning.rst","_autosummary/_autosummary_binning/netcal.binning.IsotonicRegression.rst","_autosummary/_autosummary_metric/netcal.metrics.ACE.rst","_autosummary/_autosummary_metric/netcal.metrics.ECE.rst","_autosummary/_autosummary_metric/netcal.metrics.MCE.rst","_autosummary/_autosummary_presentation/netcal.presentation.ReliabilityDiagram.rst","_autosummary/_autosummary_regularization_func/netcal.regularization.confidence_penalty.rst","_autosummary/_autosummary_scaling/netcal.scaling.BetaCalibration.rst","_autosummary/_autosummary_scaling/netcal.scaling.BetaCalibrationDependent.rst","_autosummary/_autosummary_scaling/netcal.scaling.LogisticCalibration.rst","_autosummary/_autosummary_scaling/netcal.scaling.LogisticCalibrationDependent.rst","_autosummary/_autosummary_scaling/netcal.scaling.TemperatureScaling.rst","_autosummary/netcal.binning.rst","_autosummary/netcal.metrics.rst","_autosummary/netcal.presentation.rst","_autosummary/netcal.regularization.rst","_autosummary/netcal.scaling.rst","_autosummary_abstract_calibration/netcal.AbstractCalibration.rst","index.rst"],objects:{"":{netcal:[20,0,0,"-"]},"netcal.AbstractCalibration":{clear:[19,2,1,""],epsilon:[19,3,1,""],fit:[19,2,1,""],fit_transform:[19,2,1,""],get_params:[19,2,1,""],load_model:[19,2,1,""],logger:[19,3,1,""],save_model:[19,2,1,""],set_params:[19,2,1,""],squeeze_generic:[19,2,1,""],transform:[19,2,1,""]},"netcal.binning":{BBQ:[0,1,1,""],ENIR:[1,1,1,""],HistogramBinning:[2,1,1,""],IsotonicRegression:[3,1,1,""]},"netcal.binning.BBQ":{clear:[0,2,1,""],fit:[0,2,1,""],fit_transform:[0,2,1,""],get_params:[0,2,1,""],load_model:[0,2,1,""],save_model:[0,2,1,""],set_params:[0,2,1,""],squeeze_generic:[0,2,1,""],transform:[0,2,1,""]},"netcal.binning.ENIR":{clear:[1,2,1,""],fit:[1,2,1,""],fit_transform:[1,2,1,""],get_params:[1,2,1,""],load_model:[1,2,1,""],save_model:[1,2,1,""],set_params:[1,2,1,""],squeeze_generic:[1,2,1,""],transform:[1,2,1,""]},"netcal.binning.HistogramBinning":{clear:[2,2,1,""],fit:[2,2,1,""],fit_transform:[2,2,1,""],get_degrees_of_freedom:[2,2,1,""],get_params:[2,2,1,""],load_model:[2,2,1,""],save_model:[2,2,1,""],set_params:[2,2,1,""],squeeze_generic:[2,2,1,""],transform:[2,2,1,""]},"netcal.binning.IsotonicRegression":{clear:[3,2,1,""],fit:[3,2,1,""],fit_transform:[3,2,1,""],get_params:[3,2,1,""],load_model:[3,2,1,""],save_model:[3,2,1,""],set_params:[3,2,1,""],squeeze_generic:[3,2,1,""],transform:[3,2,1,""]},"netcal.metrics":{ACE:[4,1,1,""],ECE:[5,1,1,""],MCE:[6,1,1,""]},"netcal.metrics.ACE":{measure:[4,2,1,""],squeeze_generic:[4,2,1,""]},"netcal.metrics.ECE":{measure:[5,2,1,""],squeeze_generic:[5,2,1,""]},"netcal.metrics.MCE":{measure:[6,2,1,""],squeeze_generic:[6,2,1,""]},"netcal.presentation":{ReliabilityDiagram:[7,1,1,""]},"netcal.presentation.ReliabilityDiagram":{plot:[7,2,1,""]},"netcal.regularization":{confidence_penalty:[8,4,1,""]},"netcal.scaling":{BetaCalibration:[9,1,1,""],BetaCalibrationDependent:[10,1,1,""],LogisticCalibration:[11,1,1,""],LogisticCalibrationDependent:[12,1,1,""],TemperatureScaling:[13,1,1,""]},"netcal.scaling.BetaCalibration":{clear:[9,2,1,""],fit:[9,2,1,""],fit_transform:[9,2,1,""],get_params:[9,2,1,""],load_model:[9,2,1,""],save_model:[9,2,1,""],set_params:[9,2,1,""],squeeze_generic:[9,2,1,""],transform:[9,2,1,""]},"netcal.scaling.BetaCalibrationDependent":{clear:[10,2,1,""],fit:[10,2,1,""],fit_transform:[10,2,1,""],get_params:[10,2,1,""],load_model:[10,2,1,""],save_model:[10,2,1,""],set_params:[10,2,1,""],squeeze_generic:[10,2,1,""],transform:[10,2,1,""]},"netcal.scaling.LogisticCalibration":{clear:[11,2,1,""],fit:[11,2,1,""],fit_transform:[11,2,1,""],get_params:[11,2,1,""],load_model:[11,2,1,""],save_model:[11,2,1,""],set_params:[11,2,1,""],squeeze_generic:[11,2,1,""],transform:[11,2,1,""]},"netcal.scaling.LogisticCalibrationDependent":{clear:[12,2,1,""],fit:[12,2,1,""],fit_transform:[12,2,1,""],get_params:[12,2,1,""],load_model:[12,2,1,""],save_model:[12,2,1,""],set_params:[12,2,1,""],squeeze_generic:[12,2,1,""],transform:[12,2,1,""]},"netcal.scaling.TemperatureScaling":{clear:[13,2,1,""],fit:[13,2,1,""],fit_transform:[13,2,1,""],get_params:[13,2,1,""],load_model:[13,2,1,""],save_model:[13,2,1,""],set_params:[13,2,1,""],squeeze_generic:[13,2,1,""],temperature:[13,2,1,""],transform:[13,2,1,""]},netcal:{AbstractCalibration:[19,1,1,""],binning:[14,0,0,"-"],metrics:[15,0,0,"-"],presentation:[16,0,0,"-"],regularization:[17,0,0,"-"],scaling:[18,0,0,"-"]}},objnames:{"0":["py","module","Python module"],"1":["py","class","Python class"],"2":["py","method","Python method"],"3":["py","attribute","Python attribute"],"4":["py","function","Python function"]},objtypes:{"0":"py:module","1":"py:class","2":"py:method","3":"py:attribute","4":"py:function"},terms:{"16th":[1,20],"22nd":7,"2nd":19,"34th":[7,11,13,20],"abstract":19,"boolean":[0,1,2,3,9,10,11,12,13,19],"case":[9,11],"class":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,19,20],"default":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,19,20],"float":[4,5,6,7,8,19],"function":[0,1,2,3,7,8,9,10,11,12,13,19],"import":[10,12,20],"int":[0,1,2,3,4,5,6,7,9,10,11,12,13,19],"k\u00fcpper":[2,4,5,6,7,9,10,11,12,13,20],"new":20,"public":20,"return":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,15,19],"true":[0,1,2,3,4,5,6,7,9,10,11,12,13,19,20],ACE:[7,15,16,20],AND:20,Axes:[0,1,2,3,4,5,6,9,10,11,12,13,19],ECE:[4,7,15,16,20],For:[2,9,10,11,12,17,20],Near:[1,20],The:[0,1,2,3,4,5,6,7,9,10,11,12,13,15,19,20],These:[0,1,17,20],Use:17,Using:[0,1,9,11],_miscalibr:[4,5,6],a_k:9,aaai:[0,5,6,20],abl:20,abov:8,abstractcalibr:[0,1,2,3,9,10,11,12,13,20],acc:[4,5,6],accord:[4,5,9,10,11,12,20],accur:[2,3,20],accuraci:[4,5,6,7,14,15,16,18,20],achiev:[17,20],adam:10,added:20,addit:[0,1,2,3,4,5,6,7,9,10,11,12,13,19,20],adjac:1,advanc:[11,20],after:[0,1,2,3,9,10,11,12,13,19],afterward:7,aic:[0,1],aikaik:[0,1],aka:11,akaik:[0,1],algorithm:1,alia:[13,20],all:[0,1,2,4,5,6,7,9,10,11,12,19,20],allow:1,along:20,alpha:[9,10],alpha_0:10,alpha_k:[9,10],also:[4,5,6,9,10,11,12,13,20],altern:13,alwai:[4,5,6],amirhossein:[2,4,5,6,7,9,10,11,12,13,20],amount:[0,2,4,5,6,7,20],andrea:[4,20],andrew:[4,20],ani:[0,1,2,3,8,9,10,11,12,13,19],anoth:20,anselm:[2,4,5,6,7,9,10,11,12,13,20],appli:[2,8,9,10,11,12,13,17,20],applic:[10,20],approx:[0,1,9,10,11,12],approxim:[14,18],arg:7,argument:7,arrai:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,19,20],artifici:[0,5,6,9,20],assess:10,assign:[2,8],assum:[4,5,9,11],ast:10,ast_j:10,attributeerror:[7,19],author:20,auto:[4,9,20],auto_select:9,avail:20,averag:[4,5,6,7,15,20],axes:[0,1,2,3,4,5,6,9,10,11,12,13,19],axes_to_keep:[0,1,2,3,4,5,6,9,10,11,12,13,19],axi:20,b_i:5,b_k:9,background:[9,10,11,12],base:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,19,20],baseestim:19,basic:20,batch:[7,10],bayesian:[0,1,2,5,6,20],bbq:20,bdeu:0,been:20,befor:19,behaviour:20,below:20,best:9,beta:[9,10,20],beta_0:10,beta_k:[9,10],betacalibr:20,betacalibrationdepend:20,between:[4,5,6,7,9,11,15,16,20],bia:11,bianca:[2,3,20],bias:20,bic:[0,1,2],big:10,bigg:[9,10],bin:[4,5,6,7,15,16],binari:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,19,20],blondel:20,booktitl:20,bool:[0,1,2,3,4,5,6,7,9,10,11,12,13,19],both:12,bottrop:20,bound:20,boundari:[2,3],box:[0,1,2,3,4,5,6,7,9,10,11,12,13,19,20],branch:[2,20],brucher:20,build:[0,1,2,3,9,10,11,12,13,19],built:19,calcul:[0,1,4,5,6,7,20],calibr:[0,1,2,3,4,5,6,7,9,10,11,12,13,14,15,17,18,19],calibrated_scor:20,call:[2,19,20],callback:17,can:[0,1,7,8,9,10,11,12,13,19,20],captur:20,caruana:7,center:20,certain:[1,20],charl:[2,3,20],check:19,child:[0,1,2,3,9,10,11,12,13,19],chorowski:[8,20],chosen:2,chuan:[7,11,13,20],cite:20,classic:7,classif:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,19],classifi:[1,2,3,9,10,11,12,20],classmethod:[0,1,2,3,4,5,6,9,10,11,12,13,19],clear:[0,1,2,3,9,10,11,12,13,19],code:20,color:7,combin:[9,10,11,12],command:20,common:[15,20],commonli:20,comparison:[11,20],compat:[10,12],compon:[0,1,2,3,9,10,11,12,13,19],comput:[0,2,4,5,6,7,9,10,11,12,13,19,20],conf:[4,5,6],confer:[0,1,2,4,5,6,7,9,10,11,12,13,20],confid:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20],confidence_penalti:20,conform:11,consecut:1,consist:[9,10,11,12,14,16,18],constant:3,constructor:20,contain:[0,1,2,3,9,10,11,12,13,19,20],contrast:1,convert:19,cooper:[0,1,5,6,20],coordin:7,copi:20,copyright:20,corr:[8,20],correl:20,could:7,counterpart:20,cournapeau:20,covari:12,criterion:[0,1],critic:20,cross:7,crucial:20,current:0,cvf:[2,4,5,6,7,9,10,11,12,13,20],cvpr:[2,4,5,6,7,9,10,11,12,13,20],data:[0,1,2,3,9,10,11,12,13,19,20],david:10,debug:19,decis:[2,20],decompos:12,deep:[0,1,2,3,9,10,11,12,13,19],defin:[0,1,2,3,4,5,6,9,10,11,12,13,19,20],degre:2,deliv:[9,10,11,12],denot:[0,1,4,5,6,9,10,11,12,20],densiti:[9,10,11,12],depend:[10,12,20],describ:10,descript:20,design:20,detail:20,detect:[0,1,2,3,4,5,6,7,9,10,11,12,13,19],determin:[9,11,20],deviat:[15,20],devic:10,diagram:[7,16,20],dict:[0,1,2,3,9,10,11,12,13,19],differ:[0,2,4,5,6,7,20],digit:[19,20],dim:[0,1,2,3,4,5,6,7,9,10,11,12,13,19],dimens:[0,1,2,3,4,5,6,7,9,10,11,12,13,19],directli:[1,12,20],displai:16,distribut:[8,9,10,11,12,20],divid:20,divis:19,document:20,doe:[7,19],done:20,dubourg:20,duchesnai:20,dure:[17,20],dynam:3,each:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,15,16,19,20],easi:20,easili:[9,20],easy:10,ece:20,educ:10,effici:[4,20],either:[0,1,2,3,4,5,6,7,9,10,11,12,13,19,20],elbow:[0,1],electron:[],elektronisch:20,elkan:[2,3,20],ell:[9,10,11,12],encod:[0,1,2,3,4,5,6,7,9,10,11,12,13,19],enir:20,ensembl:[1,20],entropi:8,epsilon:19,equal:[1,2,4,15,16,20],equal_interv:2,error:[4,5,6,15,19,20],especi:20,estim:[0,1,2,3,9,10,11,12,13,14,17,18,19,20],etc:7,evalu:7,even:[0,1,2,3,4,5,6,9,10,11,12,13,19],everi:20,examin:7,exampl:17,exp:[0,1,9,10,11,12],expect:[5,15,20],express:[9,11],extend:[9,11,20],extens:20,fabian:[2,4,5,6,7,9,10,11,12,13,20],fabiankuepp:20,factor:11,fahrwerksystem:20,fals:[0,1,2,3,4,5,6,7,9,10,11,12,13,19],featur:[0,1,2,3,4,5,6,7,9,10,11,12,13,19],feature_nam:7,figur:7,file:20,filenam:[0,1,2,3,7,9,10,11,12,13,19],filho:[9,20],first:[9,10,11,12],fit:[0,1,2,3,7,9,10,11,12,13,19,20],fit_param:[0,1,2,3,9,10,11,12,13,19],fit_transform:[0,1,2,3,9,10,11,12,13,19],flach:[9,20],flag:20,fmax:7,fmin:7,follow:20,foral:10,form:[0,1,2,3,9,10,11,12,13,19,20],formul:11,found:[9,20],frac:[4,5,9,10,11,12],framework:[10,12],freedom:2,from:[0,1,2,3,9,10,11,12,13,19,20],full:20,furthermor:20,gaimersheim:20,gap:[7,15,16,20],gener:[9,10,11,12],geoff:[7,11,13,20],germani:20,get:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,19,20],get_degrees_of_freedom:2,get_param:[0,1,2,3,9,10,11,12,13,19],github:20,give:15,given:[0,1,3,4,5,7,9,10,11,12,15,20],gmbh:20,good:7,gramfort:20,gregori:[0,1,5,6,20],grisel:20,ground:[0,1,2,3,4,5,6,7,9,10,11,12,13,19,20],ground_truth:20,group:[1,4,5,6,20],guarante:[12,19],guo:[7,11,13,20],has:[9,10,11,12,19,20],haselhoff:[2,4,5,6,7,9,10,11,12,13,20],hat:[0,1,9,10,11,12,13],hauskrecht:[0,5,6,20],have:[0,1,2,3,4,5,6,7,9,10,11,12,13,19],heatmap:20,height:[7,9,10,11,12],highest:[15,20],hinton:[8,20],histogram:[2,4,5,6,7,20],histogrambin:[0,3,20],hoefl:20,holger:20,hot:[0,1,2,3,4,5,6,7,9,10,11,12,13,19],how:20,howev:[11,20],http:20,icdm:[1,20],icml:[2,20],ieee:[1,2,4,5,6,7,9,10,11,12,13,20],implement:[9,20],improv:[9,19,20],includ:[2,7,20],independ:[0,1,2,3,9,11,13,19],independent_prob:[0,1,2,3,9,11,13,19],indic:[9,10,11,12,20],inequ:19,info:19,inform:[0,1,2,4,7,20],inherit:[19,20],initi:1,inproceed:20,input:[0,1,2,3,4,5,6,7,9,10,11,12,13,19,20],input_calibr:20,insert:[10,12],instanc:[0,1,2,3,7,9,10,11,12,13,17,19],instead:[9,10,11,12],integ:2,intellig:[0,5,6,9,20],intern:[1,7,11,13,20],interpret:[7,9,10,11,12],interv:2,invok:20,iou:20,isoton:[1,3,20],isotonicregress:[1,20],iter:[0,1,2,3,4,5,6,7,9,10,11,12,13,19],its:2,jan:[2,4,5,6,7,9,10,11,12,13,20],jmlr:[7,11,13],john:[11,20],journal:[10,20],june:20,kaiser:[8,20],kdd:[2,3,20],keep:[0,1,2,3,4,5,6,9,10,11,12,13,19],kept:[0,1,2,3,4,5,6,9,10,11,12,13,19],kerpen:[],kilian:[7,11,13,20],kronenberg:[2,4,5,6,7,9,10,11,12,13,20],kueppers_2020_cvpr_workshop:20,kull:[9,20],label:[0,1,2,3,4,5,6,7,9,10,11,12,13,19,20],lambda_j:10,lambda_k:10,larg:[11,20],last:[0,1,2,3,4,5,6,7,9,10,11,12,13,19],latter:[0,1,2,3,9,10,11,12,13,19],learn:[7,10,11,13,20],least:[0,1,2,3,4,5,6,7,9,10,11,12,13,19],led:13,length:[0,1,2,7],less:20,let:[0,1],libbi:10,licens:20,like:[7,19,20],likelihood:[0,1,9,10,11,12,20],list:[0,1,2,3,4,5,6,7,9,10,11,12,13,19],load:[0,1,2,3,9,10,11,12,13,19],load_model:[0,1,2,3,9,10,11,12,13,19],locat:20,log:[0,1,9,10,11,12,19],logarithm:[8,9,10,11,12],logger:19,logist:[9,10,11,12,13,20],logisticcalibr:[13,20],logisticcalibrationdepend:20,logit:[9,10,11,12,13,20],loss:[8,20],low:[0,1],lowest:19,lr_depend:20,luka:[4,20],lukasz:8,machin:[7,11,13,20],mahdi:[0,1,5,6,20],main:4,mandatori:20,manner:2,map:[0,1,2,3,4,5,6,9,10,11,12,13,19,20],margin:[11,20],match:[7,9,10,11,12,19,20],mathbb:[11,12],mathcal:[0,1],mathemat:[9,10,11,12],matplotlib:[7,20],matric:12,matrix:12,max_:6,max_it:10,maximum:[6,7,10,15,20],mce:[7,15,20],mean:[9,10,11,12,15,20],measur:[4,5,6,7,14,15,20],meeli:[9,20],melvin:10,messag:19,method:[0,1,2,3,4,5,6,7,9,10,11,12,13,14,15,16,17,18,19],metric:7,michel:20,might:[0,1,7],milo:[0,5,6,20],mine:[1,20],minimum:7,miscalibr:[4,5,6,7,9,10,11,12,15,16,20],miscellan:20,mizil:7,mlit:[4,20],mode:[2,4,5,6,7,9,11,20],model:[0,1,2,3,9,10,11,12,13,17,19,20],modern:[7,11,13,20],modifi:1,momentum:10,monotoni:1,month:20,more:[7,19,20],most:20,mozilla:20,mpava:1,mpl:20,multi:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,19,20],multiclass:[2,3,9,11,20],multidimension:[2,20],multinomi:9,multipl:[0,1,7,9,11],multivari:[2,4,5,6,7,9,10,11,12,13,20],must:[0,1,2,3,4,5,6,7,9,10,11,12,13,19,20],n_bin:20,n_box_featur:[0,1,2,3,4,5,6,7,9,10,11,12,13,19],n_class:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,19,20],n_featur:[0,1,2,3,9,10,11,12,13,19],n_features_new:[0,1,2,3,9,10,11,12,13,19],n_sampl:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,19,20],naeini:[0,1,5,6,20],naiv:[2,20],name:[0,1,2,3,9,10,11,12,13,19],natur:20,ndarrai:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,19],nearli:20,necessari:[9,10,11,12,20],need:[2,19,20],neither:20,nest:[0,1,2,3,9,10,11,12,13,19],netcal:20,network:[7,8,11,13,20],neumann:[4,20],neural:[4,7,8,11,13,20],niculescu:7,ninth:[0,5,6,20],nip:[4,20],nir:1,none:[0,1,2,3,7,8,9,10,11,12,13,19],nor:20,norm:8,normal:[0,1,2,11,12],notat:10,novick:10,num_sampl:[4,5,6],number:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,15,19],numpi:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,19,20],nx1:[2,4,5,6,7],nx2:[2,4,5,6,7],object:[0,1,2,3,4,5,6,7,9,10,11,12,13,19,20],observ:[7,15,16,18,20],obtain:[0,1,2,5,6,9,10,11,12,17,20],odd:[9,10,11,12],onc:7,one:[0,1,2,3,4,5,6,7,9,10,11,12,13,19,20],onli:[4,5,6,7,9,10,11,12,20],onlin:[0,1,2,3,4,5,6,7,8,9,11,13],oper:[13,19],optim:[9,10,11,12],option:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,19],org:[7,11,13,20],origin:[0,1,2,3,9,10,11,12,13],other:[0,1,2,3,9,11,13,19],out:[0,1],output:[0,1,2,3,8,9,10,11,12,13,19,20],over:[0,1,4,5,6,7,17,20],overconfid:20,own:20,packag:[14,16,18,20],pakdaman:[0,1,5,6,20],paper:0,param:[0,1,2,3,9,10,11,12,13,19],paramet:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,17,19,20],part:[11,20],pass:7,passo:20,pattern:[2,4,5,6,7,9,10,11,12,13,20],pedestrian:[4,20],pedregosa:20,penal:[8,17,20],penalti:[8,17,20],pereyra:[8,20],perform:[13,19,20],perrot:20,peter:[9,20],pickl:[0,1,2,3,9,10,11,12,13,19],piecewis:3,pip3:20,pip:20,pipelin:[0,1,2,3,9,10,11,12,13,19],platt:[11,20],pleas:20,pleiss:[7,11,13,20],plot:[7,20],pmlr:[9,20],pool:1,posit:[9,10,11,12,20],possibl:[0,1,2,3,9,10,11,12,13,19],posterior:[0,1,8,9,10,11,12],prebuild:17,predict:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,17,19,20],prefer:20,preffer:20,present:[0,1,2,3,4,5,6,9,10,11,12,13,19,20],press:[],prettenhof:20,print:19,probabilist:[11,20],probabl:[0,1,2,3,5,6,7,9,10,11,13,19,20],problem:[9,10,11,12],proceed:[7,11,13,20],process:[4,20],prod:10,prohibit:17,properti:[7,13],propos:[0,1,2,3,9,10,11,12,13],propto:[0,1],provid:[7,9,10,11,12,20],purpos:20,pyplot:7,python3:20,python:20,quantil:[0,20],quantiti:20,quick:1,quick_init:1,quit:20,rais:[7,19],rate:10,ratio:[9,10,11,12],readm:20,reason:[10,12],recent:20,recognit:[2,4,5,6,7,9,10,11,12,13,20],refer:[0,1,2,3,4,5,6,7,8,9,10,11,12,13],regress:[1,2,3,7,9,10,11,12,13,20],regular:11,rel:[0,1,20],relative_x_posit:20,relax:[4,20],reliabilitydiagram:20,reliabl:[7,16,20],remain:[4,5,6],remind:20,reparametr:9,requir:12,research:20,respect:[9,10,12],restrict:[1,12],result:7,return_map:[4,5,6],return_num_sampl:[4,5,6],right:20,robert:20,rootlogg:19,ruhr:20,runtimeerror:19,ryan:20,s_k:[9,10],safe:[4,20],safeti:20,same:[2,4,5,6,7,11],sampl:[2,4,5,6,7,9,10,11,12,15,16,20],sample_threshold:[4,5,6,7],save:[0,1,2,3,7,9,10,11,12,13,19],save_arg:7,save_model:[0,1,2,3,9,10,11,12,13,19],savefig:7,scale:7,scheme:[9,10,11,12],scienc:20,scikit:20,scipi:[10,20],scope:20,score:[0,1,2,3,9,10,11,12,20],score_funct:[0,1],second:7,see:20,select:9,self:[0,1,2,3,9,10,11,12,13,19],semidefinit:12,separ:[4,5,6,7,20],set:[0,1,2,3,7,9,10,11,12,13,19],set_param:[0,1,2,3,9,10,11,12,13,19],setup:20,setuptool:20,sever:[0,1,2,3,4,5,6,7,9,10,11,12,13,14,18,19,20],shantia:[2,4,5,6,7,9,10,11,12,13,20],shape:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,19,20],should:[0,1,2,3,4,5,6,7,9,10,11,12,13,17,19,20],shown:20,sigma:12,sigma_:[12,13],sigmoid:[0,1,2,3,9,11,13,19],silva:[9,20],similar:[3,15,16,20],simpl:[0,1,2,3,9,10,11,12,13,19],simpli:[2,11,20],size:[0,1,2,3,4,5,6,9,10,11,12,13,16,19],sklearn:19,snippet:20,softmax:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,19,20],some:20,sort:[0,1,2,3],sourc:[0,1,2,3,4,5,6,7,8,9,11,13,20],space:[7,20],specifii:20,split:2,squeez:[0,1,2,3,4,5,6,9,10,11,12,13,19],squeeze_gener:[0,1,2,3,4,5,6,9,10,11,12,13,19],stack:20,standard:[1,9,10,11],statist:[9,10,20],str:[0,1,2,3,7,9,10,11,12,13,19],string:[0,1,2,3,7,9,10,11,12,13,19],structur:20,subject:20,subobject:[0,1,2,3,9,10,11,12,13,19],suffix:7,suit:20,sum:[0,9,10,20],sum_:[0,1,4,5],sum_k:9,summar:9,sun:[7,11,13,20],supervis:7,support:[0,11,20],symmetr:12,system:[4,20],target:[0,1,2,3,9,10,11,12,13,19],task:[4,5,9,10,11,12,13,20],technometr:20,telmo:[9,20],temperatur:[11,13,20],temperature_onli:11,temperaturesc:20,term:[8,20],text:[4,5,6,9,10,11,12,13],than:[7,19],thei:[0,1,2,3,4,5,6,9,10,11,12,13,19],them:1,therefor:[9,10,11,12],theta:[0,1],thi:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,16,18,19,20],thirion:20,those:[9,10,11,12,20],threshold:8,thu:11,tibshirani:20,time:12,titl:[7,20],title_suffix:7,tool:20,top:[9,10,11,12],torch:20,tqdm:20,train:[0,1,2,3,9,10,11,12,13,17,19,20],transform:[0,1,2,3,9,10,11,12,13,19,20],transformermixin:19,treat:[0,1,2,3,4,5,6,7,9,10,11,12,13,19],tree:[2,20],tri:[10,12],truth:[0,1,2,3,4,5,6,7,9,10,11,12,13,19,20],tucker:[8,20],tupl:[0,1,2,3,4,5,6,7,9,10,11,12,13,19],twenti:[0,5,6,20],two:20,type:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,19],typic:8,uncalibr:[0,1,2,3,9,10,11,12,13,19,20],uncalibrated_scor:20,union:[0,1,2,3,4,5,6,7,9,10,11,12,13,19],univari:[9,11],univers:20,updat:[0,1,2,3,9,10,11,12,13,19],use:[2,4,5,6,7,9,10,11,12,14,18,20],used:[0,1,2,3,4,5,6,7,9,10,11,12,13,19,20],uses:[9,10,11,12,20],using:[0,1,5,6,7,9,11,20],util:[0,9,10,11,20],valid:7,valu:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,19],vanderpla:20,variabl:[9,10,11,12],varianc:11,variant:10,varoquaux:20,vector:[0,1,2,3,4,5,6,7,9,10,11,12,13,19,20],vedaldi:[4,20],version:[0,1,2,3,9,10,11,12,13,19],violat:1,vision:[2,4,5,6,7,9,10,11,12,13,20],visit:20,visteon:[],visual:[7,16],volum:[7,11,13,20],wai:7,want:20,warn:19,weight:[0,1,4,8,15,20],weinberg:[7,11,13,20],weiss:20,well:[0,1,2,3,5,6,9,10,11,12,13,19,20],west:20,where:[4,5,6,9,10,20],wherea:[9,10,11,12],which:[0,9,10,11,12,14,17,18,20],width:[2,7,9,10,11,12],wise:7,work:[0,1,2,3,9,10,11,12,13,19,20],workshop:[2,4,5,6,7,9,10,11,12,13,20],write:20,x_0:[0,1],x_1:[0,1],x_new:[0,1,2,3,9,10,11,12,13,19],y_0:[0,1],y_1:[0,1],year:20,you:20,your:20,zadrozni:[2,3,20],zisserman:[4,20]},titles:["netcal.binning.BBQ","netcal.binning.ENIR","netcal.binning.HistogramBinning","netcal.binning.IsotonicRegression","netcal.metrics.ACE","netcal.metrics.ECE","netcal.metrics.MCE","netcal.presentation.ReliabilityDiagram","netcal.regularization.confidence_penalty","netcal.scaling.BetaCalibration","netcal.scaling.BetaCalibrationDependent","netcal.scaling.LogisticCalibration","netcal.scaling.LogisticCalibrationDependent","netcal.scaling.TemperatureScaling","netcal.binning","netcal.metrics","netcal.presentation","netcal.regularization","netcal.scaling","netcal.AbstractCalibration","API Reference"],titleterms:{"class":[14,15,16,18],"function":17,ACE:4,ECE:5,abstractcalibr:19,api:20,avail:[14,15,16,17,18],bbq:0,betacalibr:9,betacalibrationdepend:10,bin:[0,1,2,3,14,20],calibr:20,classif:20,confidence_penalti:8,content:20,detect:20,enir:1,exampl:20,framework:20,histogrambin:2,instal:20,isotonicregress:3,logisticcalibr:11,logisticcalibrationdepend:12,mce:6,method:20,metric:[4,5,6,15,20],netcal:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19],overview:20,present:[7,16],refer:20,regular:[8,17,20],reliabilitydiagram:7,requir:20,scale:[9,10,11,12,13,18,20],tabl:20,temperaturesc:13,visual:20}}) \ No newline at end of file diff --git a/docs/source/conf.py b/docs/source/conf.py index c93cf31..ac8f059 100644 --- a/docs/source/conf.py +++ b/docs/source/conf.py @@ -1,5 +1,5 @@ -# Copyright (C) 2019-2020 Ruhr West University of Applied Sciences, Bottrop, Germany -# AND Visteon Electronics Germany GmbH, Kerpen, Germany +# Copyright (C) 2019-2021 Ruhr West University of Applied Sciences, Bottrop, Germany +# AND Elektronische Fahrwerksysteme GmbH, Gaimersheim Germany # # This Source Code Form is subject to the terms of the Mozilla Public # License, v. 2.0. If a copy of the MPL was not distributed with this @@ -23,7 +23,7 @@ # -- Project information ----------------------------------------------------- project = 'calibration-framework' -copyright = '2019-2020, Ruhr West University of Applied Sciences, Bottrop, Germany AND Visteon Electronics Germany GmbH, Kerpen, Germany' +copyright = '2019-2021, Ruhr West University of Applied Sciences, Bottrop, Germany AND Elektronische Fahrwerksysteme GmbH, Gaimersheim Germany' author = 'Fabian Kueppers' # The full version, including alpha/beta/rc tags diff --git a/examples/__init__.py b/examples/__init__.py index f050261..1ce3eb8 100644 --- a/examples/__init__.py +++ b/examples/__init__.py @@ -1,6 +1,6 @@ """ -Copyright (C) 2019-2020 Ruhr West University of Applied Sciences, Bottrop, Germany -AND Visteon Electronics Germany GmbH, Kerpen, Germany +Copyright (C) 2019-2021 Ruhr West University of Applied Sciences, Bottrop, Germany +AND Elektronische Fahrwerksysteme GmbH, Gaimersheim Germany This Source Code Form is subject to the terms of the Mozilla Public License, v. 2.0. If a copy of the MPL was not distributed with this diff --git a/examples/classification/CIFAR.py b/examples/classification/CIFAR.py index 8daa998..03425e7 100644 --- a/examples/classification/CIFAR.py +++ b/examples/classification/CIFAR.py @@ -1,5 +1,5 @@ -# Copyright (C) 2019-2020 Ruhr West University of Applied Sciences, Bottrop, Germany -# AND Visteon Electronics Germany GmbH, Kerpen, Germany +# Copyright (C) 2019-2021 Ruhr West University of Applied Sciences, Bottrop, Germany +# AND Elektronische Fahrwerksysteme GmbH, Gaimersheim Germany # # This Source Code Form is subject to the terms of the Mozilla Public # License, v. 2.0. If a copy of the MPL was not distributed with this diff --git a/examples/classification/Evaluation.py b/examples/classification/Evaluation.py index e2336de..e41c84b 100644 --- a/examples/classification/Evaluation.py +++ b/examples/classification/Evaluation.py @@ -1,5 +1,5 @@ -# Copyright (C) 2019-2020 Ruhr West University of Applied Sciences, Bottrop, Germany -# AND Visteon Electronics Germany GmbH, Kerpen, Germany +# Copyright (C) 2019-2021 Ruhr West University of Applied Sciences, Bottrop, Germany +# AND Elektronische Fahrwerksysteme GmbH, Gaimersheim Germany # # This Source Code Form is subject to the terms of the Mozilla Public # License, v. 2.0. If a copy of the MPL was not distributed with this diff --git a/examples/classification/__init__.py b/examples/classification/__init__.py index 3b019e7..0857f83 100644 --- a/examples/classification/__init__.py +++ b/examples/classification/__init__.py @@ -1,5 +1,5 @@ -# Copyright (C) 2019-2020 Ruhr West University of Applied Sciences, Bottrop, Germany -# AND Visteon Electronics Germany GmbH, Kerpen, Germany +# Copyright (C) 2019-2021 Ruhr West University of Applied Sciences, Bottrop, Germany +# AND Elektronische Fahrwerksysteme GmbH, Gaimersheim Germany # # This Source Code Form is subject to the terms of the Mozilla Public # License, v. 2.0. If a copy of the MPL was not distributed with this diff --git a/examples/classification/utils.py b/examples/classification/utils.py index d34bf24..fd39a0d 100644 --- a/examples/classification/utils.py +++ b/examples/classification/utils.py @@ -1,5 +1,5 @@ -# Copyright (C) 2019-2020 Ruhr West University of Applied Sciences, Bottrop, Germany -# AND Visteon Electronics Germany GmbH, Kerpen, Germany +# Copyright (C) 2019-2021 Ruhr West University of Applied Sciences, Bottrop, Germany +# AND Elektronische Fahrwerksysteme GmbH, Gaimersheim Germany # # This Source Code Form is subject to the terms of the Mozilla Public # License, v. 2.0. If a copy of the MPL was not distributed with this diff --git a/examples/detection/artificial/Calibration.py b/examples/detection/artificial/Calibration.py index a96f158..1e62bca 100644 --- a/examples/detection/artificial/Calibration.py +++ b/examples/detection/artificial/Calibration.py @@ -1,5 +1,5 @@ -# Copyright (C) 2019-2020 Ruhr West University of Applied Sciences, Bottrop, Germany -# AND Visteon Electronics Germany GmbH, Kerpen, Germany +# Copyright (C) 2019-2021 Ruhr West University of Applied Sciences, Bottrop, Germany +# AND Elektronische Fahrwerksysteme GmbH, Gaimersheim Germany # # This Source Code Form is subject to the terms of the Mozilla Public # License, v. 2.0. If a copy of the MPL was not distributed with this diff --git a/examples/detection/artificial/CreateDataset.py b/examples/detection/artificial/CreateDataset.py index 9ca90aa..9d2b333 100644 --- a/examples/detection/artificial/CreateDataset.py +++ b/examples/detection/artificial/CreateDataset.py @@ -1,5 +1,5 @@ -# Copyright (C) 2019-2020 Ruhr West University of Applied Sciences, Bottrop, Germany -# AND Visteon Electronics Germany GmbH, Kerpen, Germany +# Copyright (C) 2019-2021 Ruhr West University of Applied Sciences, Bottrop, Germany +# AND Elektronische Fahrwerksysteme GmbH, Gaimersheim Germany # # This Source Code Form is subject to the terms of the Mozilla Public # License, v. 2.0. If a copy of the MPL was not distributed with this diff --git a/examples/detection/artificial/Evaluation.py b/examples/detection/artificial/Evaluation.py index 1e6c03b..ab7f8aa 100644 --- a/examples/detection/artificial/Evaluation.py +++ b/examples/detection/artificial/Evaluation.py @@ -1,5 +1,5 @@ -# Copyright (C) 2019-2020 Ruhr West University of Applied Sciences, Bottrop, Germany -# AND Visteon Electronics Germany GmbH, Kerpen, Germany +# Copyright (C) 2019-2021 Ruhr West University of Applied Sciences, Bottrop, Germany +# AND Elektronische Fahrwerksysteme GmbH, Gaimersheim Germany # # This Source Code Form is subject to the terms of the Mozilla Public # License, v. 2.0. If a copy of the MPL was not distributed with this diff --git a/examples/detection/artificial/__init__.py b/examples/detection/artificial/__init__.py index 79bc6c2..3a3b1ed 100644 --- a/examples/detection/artificial/__init__.py +++ b/examples/detection/artificial/__init__.py @@ -1,5 +1,5 @@ -# Copyright (C) 2019-2020 Ruhr West University of Applied Sciences, Bottrop, Germany -# AND Visteon Electronics Germany GmbH, Kerpen, Germany +# Copyright (C) 2019-2021 Ruhr West University of Applied Sciences, Bottrop, Germany +# AND Elektronische Fahrwerksysteme GmbH, Gaimersheim Germany # # This Source Code Form is subject to the terms of the Mozilla Public # License, v. 2.0. If a copy of the MPL was not distributed with this diff --git a/examples/detection/artificial/toolchain.py b/examples/detection/artificial/toolchain.py index 599fd85..510d592 100644 --- a/examples/detection/artificial/toolchain.py +++ b/examples/detection/artificial/toolchain.py @@ -1,5 +1,5 @@ -# Copyright (C) 2019-2020 Ruhr West University of Applied Sciences, Bottrop, Germany -# AND Visteon Electronics Germany GmbH, Kerpen, Germany +# Copyright (C) 2019-2021 Ruhr West University of Applied Sciences, Bottrop, Germany +# AND Elektronische Fahrwerksysteme GmbH, Gaimersheim Germany # # This Source Code Form is subject to the terms of the Mozilla Public # License, v. 2.0. If a copy of the MPL was not distributed with this diff --git a/examples/detection/mscoco/Evaluation.py b/examples/detection/mscoco/Evaluation.py index 2b1fa93..da8a132 100644 --- a/examples/detection/mscoco/Evaluation.py +++ b/examples/detection/mscoco/Evaluation.py @@ -1,5 +1,5 @@ -# Copyright (C) 2019-2020 Ruhr West University of Applied Sciences, Bottrop, Germany -# AND Visteon Electronics Germany GmbH, Kerpen, Germany +# Copyright (C) 2019-2021 Ruhr West University of Applied Sciences, Bottrop, Germany +# AND Elektronische Fahrwerksysteme GmbH, Gaimersheim Germany # # This Source Code Form is subject to the terms of the Mozilla Public # License, v. 2.0. If a copy of the MPL was not distributed with this diff --git a/netcal/AbstractCalibration.py b/netcal/AbstractCalibration.py index 1088ef2..e051e47 100644 --- a/netcal/AbstractCalibration.py +++ b/netcal/AbstractCalibration.py @@ -1,5 +1,5 @@ -# Copyright (C) 2019-2020 Ruhr West University of Applied Sciences, Bottrop, Germany -# AND Visteon Electronics Germany GmbH, Kerpen, Germany +# Copyright (C) 2019-2021 Ruhr West University of Applied Sciences, Bottrop, Germany +# AND Elektronische Fahrwerksysteme GmbH, Gaimersheim Germany # # This Source Code Form is subject to the terms of the Mozilla Public # License, v. 2.0. If a copy of the MPL was not distributed with this diff --git a/netcal/Decorator.py b/netcal/Decorator.py index d38032a..0281e83 100644 --- a/netcal/Decorator.py +++ b/netcal/Decorator.py @@ -1,6 +1,6 @@ """ -Copyright (C) 2019-2020 Ruhr West University of Applied Sciences, Bottrop, Germany -AND Visteon Electronics Germany GmbH, Kerpen, Germany +Copyright (C) 2019-2021 Ruhr West University of Applied Sciences, Bottrop, Germany +AND Elektronische Fahrwerksysteme GmbH, Gaimersheim Germany This Source Code Form is subject to the terms of the Mozilla Public License, v. 2.0. If a copy of the MPL was not distributed with this diff --git a/netcal/Logging.py b/netcal/Logging.py index 4235515..6b12065 100644 --- a/netcal/Logging.py +++ b/netcal/Logging.py @@ -1,5 +1,5 @@ -# Copyright (C) 2019-2020 Ruhr West University of Applied Sciences, Bottrop, Germany -# AND Visteon Electronics Germany GmbH, Kerpen, Germany +# Copyright (C) 2019-2021 Ruhr West University of Applied Sciences, Bottrop, Germany +# AND Elektronische Fahrwerksysteme GmbH, Gaimersheim Germany # # This Source Code Form is subject to the terms of the Mozilla Public # License, v. 2.0. If a copy of the MPL was not distributed with this diff --git a/netcal/__init__.py b/netcal/__init__.py index ead55c6..ef525a9 100644 --- a/netcal/__init__.py +++ b/netcal/__init__.py @@ -1,5 +1,5 @@ -# Copyright (C) 2019-2020 Ruhr West University of Applied Sciences, Bottrop, Germany -# AND Visteon Electronics Germany GmbH, Kerpen, Germany +# Copyright (C) 2019-2021 Ruhr West University of Applied Sciences, Bottrop, Germany +# AND Elektronische Fahrwerksysteme GmbH, Gaimersheim Germany # # This Source Code Form is subject to the terms of the Mozilla Public # License, v. 2.0. If a copy of the MPL was not distributed with this diff --git a/netcal/binning/BBQ.py b/netcal/binning/BBQ.py index 293cbaf..964ef19 100644 --- a/netcal/binning/BBQ.py +++ b/netcal/binning/BBQ.py @@ -1,5 +1,5 @@ -# Copyright (C) 2019-2020 Ruhr West University of Applied Sciences, Bottrop, Germany -# AND Visteon Electronics Germany GmbH, Kerpen, Germany +# Copyright (C) 2019-2021 Ruhr West University of Applied Sciences, Bottrop, Germany +# AND Elektronische Fahrwerksysteme GmbH, Gaimersheim Germany # # This Source Code Form is subject to the terms of the Mozilla Public # License, v. 2.0. If a copy of the MPL was not distributed with this diff --git a/netcal/binning/ENIR.py b/netcal/binning/ENIR.py index fe10fc7..af838a0 100644 --- a/netcal/binning/ENIR.py +++ b/netcal/binning/ENIR.py @@ -1,5 +1,5 @@ -# Copyright (C) 2019-2020 Ruhr West University of Applied Sciences, Bottrop, Germany -# AND Visteon Electronics Germany GmbH, Kerpen, Germany +# Copyright (C) 2019-2021 Ruhr West University of Applied Sciences, Bottrop, Germany +# AND Elektronische Fahrwerksysteme GmbH, Gaimersheim Germany # # This Source Code Form is subject to the terms of the Mozilla Public # License, v. 2.0. If a copy of the MPL was not distributed with this diff --git a/netcal/binning/HistogramBinning.py b/netcal/binning/HistogramBinning.py index 5ddc0b1..5b18c13 100644 --- a/netcal/binning/HistogramBinning.py +++ b/netcal/binning/HistogramBinning.py @@ -1,5 +1,5 @@ -# Copyright (C) 2019-2020 Ruhr West University of Applied Sciences, Bottrop, Germany -# AND Visteon Electronics Germany GmbH, Kerpen, Germany +# Copyright (C) 2019-2021 Ruhr West University of Applied Sciences, Bottrop, Germany +# AND Elektronische Fahrwerksysteme GmbH, Gaimersheim Germany # # This Source Code Form is subject to the terms of the Mozilla Public # License, v. 2.0. If a copy of the MPL was not distributed with this @@ -56,7 +56,7 @@ class are treated as independent of each other (sigmoid). .. [3] Fabian Küppers, Jan Kronenberger, Amirhossein Shantia and Anselm Haselhoff: "Multivariate Confidence Calibration for Object Detection." - The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2020, in press. + The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops. """ @accepts((int, tuple, list), bool, bool, bool) diff --git a/netcal/binning/IsotonicRegression.py b/netcal/binning/IsotonicRegression.py index 61b90bc..f6292bf 100644 --- a/netcal/binning/IsotonicRegression.py +++ b/netcal/binning/IsotonicRegression.py @@ -1,5 +1,5 @@ -# Copyright (C) 2019-2020 Ruhr West University of Applied Sciences, Bottrop, Germany -# AND Visteon Electronics Germany GmbH, Kerpen, Germany +# Copyright (C) 2019-2021 Ruhr West University of Applied Sciences, Bottrop, Germany +# AND Elektronische Fahrwerksysteme GmbH, Gaimersheim Germany # # This Source Code Form is subject to the terms of the Mozilla Public # License, v. 2.0. If a copy of the MPL was not distributed with this diff --git a/netcal/binning/NearIsotonicRegression.py b/netcal/binning/NearIsotonicRegression.py index ba6c137..757b645 100644 --- a/netcal/binning/NearIsotonicRegression.py +++ b/netcal/binning/NearIsotonicRegression.py @@ -1,5 +1,5 @@ -# Copyright (C) 2019-2020 Ruhr West University of Applied Sciences, Bottrop, Germany -# AND Visteon Electronics Germany GmbH, Kerpen, Germany +# Copyright (C) 2019-2021 Ruhr West University of Applied Sciences, Bottrop, Germany +# AND Elektronische Fahrwerksysteme GmbH, Gaimersheim Germany # # This Source Code Form is subject to the terms of the Mozilla Public # License, v. 2.0. If a copy of the MPL was not distributed with this diff --git a/netcal/binning/__init__.py b/netcal/binning/__init__.py index 2c6c25b..cb1ea84 100644 --- a/netcal/binning/__init__.py +++ b/netcal/binning/__init__.py @@ -1,5 +1,5 @@ -# Copyright (C) 2019-2020 Ruhr West University of Applied Sciences, Bottrop, Germany -# AND Visteon Electronics Germany GmbH, Kerpen, Germany +# Copyright (C) 2019-2021 Ruhr West University of Applied Sciences, Bottrop, Germany +# AND Elektronische Fahrwerksysteme GmbH, Gaimersheim Germany # # This Source Code Form is subject to the terms of the Mozilla Public # License, v. 2.0. If a copy of the MPL was not distributed with this diff --git a/netcal/metrics/ACE.py b/netcal/metrics/ACE.py index 57df620..d2a447a 100644 --- a/netcal/metrics/ACE.py +++ b/netcal/metrics/ACE.py @@ -1,5 +1,5 @@ -# Copyright (C) 2019-2020 Ruhr West University of Applied Sciences, Bottrop, Germany -# AND Visteon Electronics Germany GmbH, Kerpen, Germany +# Copyright (C) 2019-2021 Ruhr West University of Applied Sciences, Bottrop, Germany +# AND Elektronische Fahrwerksysteme GmbH, Gaimersheim Germany # # This Source Code Form is subject to the terms of the Mozilla Public # License, v. 2.0. If a copy of the MPL was not distributed with this @@ -45,7 +45,7 @@ class ACE(_Miscalibration): `Get source online `_ .. [2] Fabian Küppers, Jan Kronenberger, Amirhossein Shantia and Anselm Haselhoff: "Multivariate Confidence Calibration for Object Detection." - The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2020, in press. + The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops. """ @dimensions((1, 2), (1, 2), None, None) diff --git a/netcal/metrics/ECE.py b/netcal/metrics/ECE.py index 3ac57ca..431e9c4 100644 --- a/netcal/metrics/ECE.py +++ b/netcal/metrics/ECE.py @@ -1,5 +1,5 @@ -# Copyright (C) 2019-2020 Ruhr West University of Applied Sciences, Bottrop, Germany -# AND Visteon Electronics Germany GmbH, Kerpen, Germany +# Copyright (C) 2019-2021 Ruhr West University of Applied Sciences, Bottrop, Germany +# AND Elektronische Fahrwerksysteme GmbH, Gaimersheim Germany # # This Source Code Form is subject to the terms of the Mozilla Public # License, v. 2.0. If a copy of the MPL was not distributed with this @@ -46,7 +46,7 @@ class ECE(_Miscalibration): `Get source online `_ .. [2] Fabian Küppers, Jan Kronenberger, Amirhossein Shantia and Anselm Haselhoff: "Multivariate Confidence Calibration for Object Detection." - The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2020, in press. + The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops. """ @dimensions((1, 2), (1, 2), None, None) diff --git a/netcal/metrics/MCE.py b/netcal/metrics/MCE.py index 4656ed7..8ee8d82 100644 --- a/netcal/metrics/MCE.py +++ b/netcal/metrics/MCE.py @@ -1,5 +1,5 @@ -# Copyright (C) 2019-2020 Ruhr West University of Applied Sciences, Bottrop, Germany -# AND Visteon Electronics Germany GmbH, Kerpen, Germany +# Copyright (C) 2019-2021 Ruhr West University of Applied Sciences, Bottrop, Germany +# AND Elektronische Fahrwerksysteme GmbH, Gaimersheim Germany # # This Source Code Form is subject to the terms of the Mozilla Public # License, v. 2.0. If a copy of the MPL was not distributed with this @@ -44,7 +44,7 @@ class MCE(_Miscalibration): `Get source online `_ .. [2] Fabian Küppers, Jan Kronenberger, Amirhossein Shantia and Anselm Haselhoff: "Multivariate Confidence Calibration for Object Detection." - The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2020, in press. + The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops. """ @dimensions((1, 2), (1, 2), None, None) diff --git a/netcal/metrics/Miscalibration.py b/netcal/metrics/Miscalibration.py index 0e37312..a934cba 100644 --- a/netcal/metrics/Miscalibration.py +++ b/netcal/metrics/Miscalibration.py @@ -1,5 +1,5 @@ -# Copyright (C) 2019-2020 Ruhr West University of Applied Sciences, Bottrop, Germany -# AND Visteon Electronics Germany GmbH, Kerpen, Germany +# Copyright (C) 2019-2021 Ruhr West University of Applied Sciences, Bottrop, Germany +# AND Elektronische Fahrwerksysteme GmbH, Gaimersheim Germany # # This Source Code Form is subject to the terms of the Mozilla Public # License, v. 2.0. If a copy of the MPL was not distributed with this @@ -43,7 +43,7 @@ class _Miscalibration(object): `Get source online `_ .. [3] Fabian Küppers, Jan Kronenberger, Amirhossein Shantia and Anselm Haselhoff: "Multivariate Confidence Calibration for Object Detection." - The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2020, in press. + The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops. """ epsilon = np.finfo(np.float).eps diff --git a/netcal/metrics/__init__.py b/netcal/metrics/__init__.py index 7f925a3..49d34c9 100644 --- a/netcal/metrics/__init__.py +++ b/netcal/metrics/__init__.py @@ -1,5 +1,5 @@ -# Copyright (C) 2019-2020 Ruhr West University of Applied Sciences, Bottrop, Germany -# AND Visteon Electronics Germany GmbH, Kerpen, Germany +# Copyright (C) 2019-2021 Ruhr West University of Applied Sciences, Bottrop, Germany +# AND Elektronische Fahrwerksysteme GmbH, Gaimersheim Germany # # This Source Code Form is subject to the terms of the Mozilla Public # License, v. 2.0. If a copy of the MPL was not distributed with this diff --git a/netcal/presentation/ReliabilityDiagram.py b/netcal/presentation/ReliabilityDiagram.py index dce4cd1..99f987b 100644 --- a/netcal/presentation/ReliabilityDiagram.py +++ b/netcal/presentation/ReliabilityDiagram.py @@ -1,5 +1,5 @@ -# Copyright (C) 2019-2020 Ruhr West University of Applied Sciences, Bottrop, Germany -# AND Visteon Electronics Germany GmbH, Kerpen, Germany +# Copyright (C) 2019-2021 Ruhr West University of Applied Sciences, Bottrop, Germany +# AND Elektronische Fahrwerksysteme GmbH, Gaimersheim Germany # # This Source Code Form is subject to the terms of the Mozilla Public # License, v. 2.0. If a copy of the MPL was not distributed with this @@ -56,7 +56,7 @@ class ReliabilityDiagram(object): `Get source online `_ .. [3] Fabian Küppers, Jan Kronenberger, Amirhossein Shantia and Anselm Haselhoff: "Multivariate Confidence Calibration for Object Detection." - The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2020, in press. + The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops. """ @accepts((int, tuple, list), bool, (float, None), int, (list, None), (float, None), (str, None), (str, None)) diff --git a/netcal/presentation/__init__.py b/netcal/presentation/__init__.py index 182b3ea..8c5cf70 100644 --- a/netcal/presentation/__init__.py +++ b/netcal/presentation/__init__.py @@ -1,5 +1,5 @@ -# Copyright (C) 2019-2020 Ruhr West University of Applied Sciences, Bottrop, Germany -# AND Visteon Electronics Germany GmbH, Kerpen, Germany +# Copyright (C) 2019-2021 Ruhr West University of Applied Sciences, Bottrop, Germany +# AND Elektronische Fahrwerksysteme GmbH, Gaimersheim Germany # # This Source Code Form is subject to the terms of the Mozilla Public # License, v. 2.0. If a copy of the MPL was not distributed with this diff --git a/netcal/regularization/ConfidencePenalty.py b/netcal/regularization/ConfidencePenalty.py index 1c8395e..24313cf 100644 --- a/netcal/regularization/ConfidencePenalty.py +++ b/netcal/regularization/ConfidencePenalty.py @@ -1,5 +1,5 @@ -# Copyright (C) 2019-2020 Ruhr West University of Applied Sciences, Bottrop, Germany -# AND Visteon Electronics Germany GmbH, Kerpen, Germany +# Copyright (C) 2019-2021 Ruhr West University of Applied Sciences, Bottrop, Germany +# AND Elektronische Fahrwerksysteme GmbH, Gaimersheim Germany # # This Source Code Form is subject to the terms of the Mozilla Public # License, v. 2.0. If a copy of the MPL was not distributed with this diff --git a/netcal/regularization/__init__.py b/netcal/regularization/__init__.py index 66581c7..feafa9c 100644 --- a/netcal/regularization/__init__.py +++ b/netcal/regularization/__init__.py @@ -1,5 +1,5 @@ -# Copyright (C) 2019-2020 Ruhr West University of Applied Sciences, Bottrop, Germany -# AND Visteon Electronics Germany GmbH, Kerpen, Germany +# Copyright (C) 2019-2021 Ruhr West University of Applied Sciences, Bottrop, Germany +# AND Elektronische Fahrwerksysteme GmbH, Gaimersheim Germany # # This Source Code Form is subject to the terms of the Mozilla Public # License, v. 2.0. If a copy of the MPL was not distributed with this diff --git a/netcal/scaling/BetaCalibration.py b/netcal/scaling/BetaCalibration.py index 3b16619..2efadfc 100644 --- a/netcal/scaling/BetaCalibration.py +++ b/netcal/scaling/BetaCalibration.py @@ -1,5 +1,5 @@ -# Copyright (C) 2019-2020 Ruhr West University of Applied Sciences, Bottrop, Germany -# AND Visteon Electronics Germany GmbH, Kerpen, Germany +# Copyright (C) 2019-2021 Ruhr West University of Applied Sciences, Bottrop, Germany +# AND Elektronische Fahrwerksysteme GmbH, Gaimersheim Germany # # This Source Code Form is subject to the terms of the Mozilla Public # License, v. 2.0. If a copy of the MPL was not distributed with this @@ -91,7 +91,7 @@ class are treated as independent of each other (sigmoid). `Get source online `_ .. [2] Fabian Küppers, Jan Kronenberger, Amirhossein Shantia and Anselm Haselhoff: "Multivariate Confidence Calibration for Object Detection." - The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2020, in press. + The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops. """ @accepts(bool, bool, bool) diff --git a/netcal/scaling/BetaCalibrationDependent.py b/netcal/scaling/BetaCalibrationDependent.py index c64419b..3fc241e 100644 --- a/netcal/scaling/BetaCalibrationDependent.py +++ b/netcal/scaling/BetaCalibrationDependent.py @@ -1,5 +1,5 @@ -# Copyright (C) 2019-2020 Ruhr West University of Applied Sciences, Bottrop, Germany -# AND Visteon Electronics Germany GmbH, Kerpen, Germany +# Copyright (C) 2019-2021 Ruhr West University of Applied Sciences, Bottrop, Germany +# AND Elektronische Fahrwerksysteme GmbH, Gaimersheim Germany # # This Source Code Form is subject to the terms of the Mozilla Public # License, v. 2.0. If a copy of the MPL was not distributed with this @@ -103,7 +103,7 @@ class BetaCalibrationDependent(AbstractCalibration): ---------- .. [1] Fabian Küppers, Jan Kronenberger, Amirhossein Shantia and Anselm Haselhoff: "Multivariate Confidence Calibration for Object Detection." - The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2020, in press. + The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops. .. [2] Libby, David L., and Melvin R. Novick: "Multivariate generalized beta distributions with applications to utility assessment" diff --git a/netcal/scaling/LogisticCalibration.py b/netcal/scaling/LogisticCalibration.py index a0db955..28ec6a9 100644 --- a/netcal/scaling/LogisticCalibration.py +++ b/netcal/scaling/LogisticCalibration.py @@ -1,5 +1,5 @@ -# Copyright (C) 2019-2020 Ruhr West University of Applied Sciences, Bottrop, Germany -# AND Visteon Electronics Germany GmbH, Kerpen, Germany +# Copyright (C) 2019-2021 Ruhr West University of Applied Sciences, Bottrop, Germany +# AND Elektronische Fahrwerksysteme GmbH, Gaimersheim Germany # # This Source Code Form is subject to the terms of the Mozilla Public # License, v. 2.0. If a copy of the MPL was not distributed with this @@ -90,7 +90,7 @@ class are treated as independent of each other (sigmoid). .. [3] Fabian Küppers, Jan Kronenberger, Amirhossein Shantia and Anselm Haselhoff: "Multivariate Confidence Calibration for Object Detection." - The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2020, in press. + The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops. """ @accepts(bool, bool, bool) diff --git a/netcal/scaling/LogisticCalibrationDependent.py b/netcal/scaling/LogisticCalibrationDependent.py index 4b2a2bf..bb38251 100644 --- a/netcal/scaling/LogisticCalibrationDependent.py +++ b/netcal/scaling/LogisticCalibrationDependent.py @@ -1,5 +1,5 @@ -# Copyright (C) 2019-2020 Ruhr West University of Applied Sciences, Bottrop, Germany -# AND Visteon Electronics Germany GmbH, Kerpen, Germany +# Copyright (C) 2019-2021 Ruhr West University of Applied Sciences, Bottrop, Germany +# AND Elektronische Fahrwerksysteme GmbH, Gaimersheim Germany # # This Source Code Form is subject to the terms of the Mozilla Public # License, v. 2.0. If a copy of the MPL was not distributed with this @@ -86,7 +86,7 @@ class LogisticCalibrationDependent(AbstractCalibration): ---------- .. [1] Fabian Küppers, Jan Kronenberger, Amirhossein Shantia and Anselm Haselhoff: "Multivariate Confidence Calibration for Object Detection." - The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2020, in press. + The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops. """ @accepts(bool) diff --git a/netcal/scaling/TemperatureScaling.py b/netcal/scaling/TemperatureScaling.py index 6aa970e..c2441a5 100644 --- a/netcal/scaling/TemperatureScaling.py +++ b/netcal/scaling/TemperatureScaling.py @@ -1,5 +1,5 @@ -# Copyright (C) 2019-2020 Ruhr West University of Applied Sciences, Bottrop, Germany -# AND Visteon Electronics Germany GmbH, Kerpen, Germany +# Copyright (C) 2019-2021 Ruhr West University of Applied Sciences, Bottrop, Germany +# AND Elektronische Fahrwerksysteme GmbH, Gaimersheim Germany # # This Source Code Form is subject to the terms of the Mozilla Public # License, v. 2.0. If a copy of the MPL was not distributed with this @@ -44,7 +44,7 @@ class are treated as independent of each other (sigmoid). .. [2] Fabian Küppers, Jan Kronenberger, Amirhossein Shantia and Anselm Haselhoff: "Multivariate Confidence Calibration for Object Detection." - The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2020, in press. + The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops. """ @accepts(bool, bool) diff --git a/netcal/scaling/__init__.py b/netcal/scaling/__init__.py index 4461b24..18d9ea8 100644 --- a/netcal/scaling/__init__.py +++ b/netcal/scaling/__init__.py @@ -1,5 +1,5 @@ -# Copyright (C) 2019-2020 Ruhr West University of Applied Sciences, Bottrop, Germany -# AND Visteon Electronics Germany GmbH, Kerpen, Germany +# Copyright (C) 2019-2021 Ruhr West University of Applied Sciences, Bottrop, Germany +# AND Elektronische Fahrwerksysteme GmbH, Gaimersheim Germany # # This Source Code Form is subject to the terms of the Mozilla Public # License, v. 2.0. If a copy of the MPL was not distributed with this diff --git a/setup.py b/setup.py index 93559b4..148b01e 100644 --- a/setup.py +++ b/setup.py @@ -1,6 +1,6 @@ """ -Copyright (C) 2019-2020 Ruhr West University of Applied Sciences, Bottrop, Germany -AND Visteon Electronics Germany GmbH, Kerpen, Germany +Copyright (C) 2019-2021 Ruhr West University of Applied Sciences, Bottrop, Germany +AND Elektronische Fahrwerksysteme GmbH, Gaimersheim Germany This Source Code Form is subject to the terms of the Mozilla Public License, v. 2.0. If a copy of the MPL was not distributed with this