The Bob Project

Bob is a free signal-processing and machine learning toolbox originally developed by the Biometrics group at Idiap Research Institute, Switzerland. The toolbox is written in a mix of Python and C++ and is designed to be both efficient and reduce development time.

• To learn about this project’s motivations and history, visit Motivations and Philosophy.
• For a brief summary of what you can do with Bob, have a look at Overview.
• To just get started using Bob, skip ahead to Installing Bob.
• If you make use of Bob or any Satellite Packages, we would appreciate if you cited one of our publications as described in Overview.
• For more detailed information, scroll down to the User’s Guide, Developer’s Guide or Reference manual.

We believe in free software and development standards. Bob is a freely available library, licensed under the terms of the GPL v3. For more information on licensing, please visit our Licensing Terms.

Enjoy!

Overview

• Overview
  • Mathematical and signal processing
  • Image processing
  • Machine learning
  • Storing and managing data
  • Database support
  • Performance evaluation

Installation

• Installing Bob

User’s Guide

• Introduction
  • First use
• Multi-dimensional Arrays
  • NumPy basics
  • Digital signals as multi-dimensional arrays
  • Interfacing with OpenCV and PIL
  • Random number generation
• Input/Output
  • HDF5 standard utilities
  • I/O operations using the class bob.io.HDF5File
  • Array interfaces
  • Numpy ndarray shortcuts
  • Reading and writing images
  • Dealing with videos
  • Loading and saving Matlab data
  • Loading and saving audio files
• Image and signal processing
  • Introduction
  • Simple signal processing
  • Simple image processing
  • Complex image operations
• Audio processing
  • Introduction
  • Simple audio processing
• Machines
  • Linear machine
  • Neural networks: multi-layer perceptrons (MLP)
  • Support vector machines
  • K-means machines
  • Gaussian machines
  • Gaussian mixture models
  • Gaussian mixture models Statistics
  • Joint Factor Analysis
  • Inter-Session Variability
  • Total Variability (i-vectors)
  • Probabilistic Linear Discriminant Analysis (PLDA)
• Trainers
  • Principal component analysis
  • Linear discriminant analysis
  • Neural networks: multi-layer perceptrons (MLP)
  • Support vector machines
  • K-means
  • Maximum likelihood for Gaussian mixture model
  • MAP-adaptation for Gaussian mixture model
  • Joint Factor Analysis
  • Inter-Session Variability
  • Total Variability (i-vectors)
  • Whitening
  • Within-Class Covariance Normalisation
  • Probabilistic Linear Discriminant Analysis (PLDA)
• Database
  • Iris Flower Data Set
• Performance Evaluation
  • Overview
  • Evaluation
  • Plotting
  • Full applications
• A Complete Application: Analysis of the Fisher Iris Dataset
  • The Iris dataset
  • Training a bob.machine.LinearMachine with LDA
  • Looking at the first LDA component
  • Measuring performance
• Organize Your Work in Satellite Packages
  • Anatomy of a buildout Python package
  • Document Generation and Unit Testing
  • Creating Database Satellite Packages
  • Creating C++/Python Bindings
  • Python Package Namespace
  • Distributing Your Work
  • Version Numbering Scheme
  • Release Methodology for Satellite Packages
  • Satellite Packages Available
• Bug Reporting and Feature Requesting

Developer’s Guide

• Join the Bob community
• Motivations and Philosophy
• Code Base Overview
• Dependencies
  • List of dependencies
  • Description of dependencies
  • Notes for specific platforms
• Compiling Bob Yourself
  • Cloning Bob
  • Compiling the code
• Bob Development
  • C++ development
  • Python development
  • Python bindings to C++ code
• Contributing to the Bob Project
• How to Profile and Optimize Bob Code
  • Profiling C/C++ code directly
  • Guidelines on building against Google perftools
  • Profiling Bob Python C++ extensions
• Using Videos with Bob
  • Codec and Format Availability
  • Know Your Platforms
  • Example Output in Different Platforms
• Bug Reporting and Feature Requesting
  • Guidelines
  • Examples of good and bad reports
  • Composing a new ticket

Reference

• Introduction
• Core
  • Error Reporting and Logging in Python
  • Note on Supported Array Data Types (dtypes)
  • bob.core.array.convert
  • bob.core.random.mt19937
  • bob.core.random.variate_generator
  • bob.core.random.binomial_float32
  • bob.core.random.binomial_float64
  • bob.core.random.discrete_int16
  • bob.core.random.discrete_int32
  • bob.core.random.discrete_int64
  • bob.core.random.discrete_int8
  • bob.core.random.discrete_uint16
  • bob.core.random.discrete_uint32
  • bob.core.random.discrete_uint64
  • bob.core.random.discrete_uint8
  • bob.core.random.gamma_float32
  • bob.core.random.gamma_float64
  • bob.core.random.lognormal_float32
  • bob.core.random.lognormal_float64
  • bob.core.random.normal_float32
  • bob.core.random.normal_float64
  • bob.core.random.uniform_float32
  • bob.core.random.uniform_float64
  • bob.core.random.uniform_int16
  • bob.core.random.uniform_int32
  • bob.core.random.uniform_int64
  • bob.core.random.uniform_int8
  • bob.core.random.uniform_uint16
  • bob.core.random.uniform_uint32
  • bob.core.random.uniform_uint64
• Mathematics
  • bob.math.chi_square
  • bob.math.histogram_intersection
  • bob.math.kullback_leibler
  • bob.math.linsolve
  • bob.math.linsolve_
  • bob.math.linsolve_cg_sympos
  • bob.math.linsolve_cg_sympos_
  • bob.math.linsolve_sympos
  • bob.math.linsolve_sympos_
  • bob.math.norminv
  • bob.math.normsinv
  • bob.math.pavx
  • bob.math.pavx_
  • bob.math.pavxWidth
  • bob.math.pavxWidthHeight
  • bob.math.scatter
  • bob.math.scatter_
  • bob.math.LPInteriorPoint
  • bob.math.LPInteriorPointLongstep
  • bob.math.LPInteriorPointPredictorCorrector
  • bob.math.LPInteriorPointShortstep
• Data Input/Output
  • bob.io.append
  • bob.io.create_directories_save
  • bob.io.extensions
  • bob.io.load
  • bob.io.merge
  • bob.io.peek
  • bob.io.peek_all
  • bob.io.save
  • bob.io.write
  • bob.io.File
  • bob.io.HDF5Descriptor
  • bob.io.HDF5File
  • bob.io.HDF5Type
  • bob.io.open
  • bob.io.available_video_codecs
  • bob.io.available_videoreader_formats
  • bob.io.available_videowriter_formats
  • bob.io.describe_video_decoder
  • bob.io.describe_video_encoder
  • bob.io.supported_video_codecs
  • bob.io.supported_videoreader_formats
  • bob.io.supported_videowriter_formats
  • bob.io.VideoReaderIterator
  • bob.io.VideoReader
  • bob.io.VideoWriter
• Signal Processing
  • bob.sp.dct
  • bob.sp.extrapolate
  • bob.sp.extrapolate_circular
  • bob.sp.extrapolate_constant
  • bob.sp.extrapolate_mirror
  • bob.sp.extrapolate_nearest
  • bob.sp.extrapolate_zero
  • bob.sp.fft
  • bob.sp.fftshift
  • bob.sp.idct
  • bob.sp.ifft
  • bob.sp.ifftshift
  • bob.sp.BorderType
  • bob.sp.DCT1D
  • bob.sp.DCT1DAbstract
  • bob.sp.DCT2D
  • bob.sp.DCT2DAbstract
  • bob.sp.FFT1D
  • bob.sp.FFT1DAbstract
  • bob.sp.FFT2D
  • bob.sp.FFT2DAbstract
  • bob.sp.IDCT1D
  • bob.sp.IDCT2D
  • bob.sp.IFFT1D
  • bob.sp.IFFT2D
  • bob.sp.Quantization
  • bob.sp.SizeOption
  • bob.sp.quantization_type
• Image Processing
  • bob.ip.block
  • bob.ip.crop
  • bob.ip.draw_box
  • bob.ip.draw_cross
  • bob.ip.draw_cross_plus
  • bob.ip.draw_line
  • bob.ip.draw_point
  • bob.ip.draw_point_
  • bob.ip.extrapolate_mask
  • bob.ip.flip
  • bob.ip.flop
  • bob.ip.flow_error
  • bob.ip.gamma_correction
  • bob.ip.get_angle_to_horizontal
  • bob.ip.get_block_3d_output_shape
  • bob.ip.get_block_4d_output_shape
  • bob.ip.get_rotated_output_shape
  • bob.ip.get_shear_x_shape
  • bob.ip.get_shear_y_shape
  • bob.ip.gray_to_rgb
  • bob.ip.histogram
  • bob.ip.histogram_
  • bob.ip.histogram_equalization
  • bob.ip.hog_compute_histogram
  • bob.ip.hog_compute_histogram_
  • bob.ip.hsl_to_rgb
  • bob.ip.hsv_to_rgb
  • bob.ip.integral
  • bob.ip.laplacian_avg_hs
  • bob.ip.laplacian_avg_hs_opencv
  • bob.ip.max_rect_in_mask
  • bob.ip.normalize_block
  • bob.ip.normalize_block_
  • bob.ip.normalize_gabor_jet
  • bob.ip.rgb_to_gray
  • bob.ip.rgb_to_hsl
  • bob.ip.rgb_to_hsv
  • bob.ip.rgb_to_yuv
  • bob.ip.rotate
  • bob.ip.scale
  • bob.ip.scale_as
  • bob.ip.shear_x
  • bob.ip.shear_y
  • bob.ip.shift
  • bob.ip.try_draw_point
  • bob.ip.yuv_to_rgb
  • bob.ip.zigzag
  • bob.ip.BlockNorm
  • bob.ip.CentralGradient
  • bob.ip.DCTFeatures
  • bob.ip.ELBPType
  • bob.ip.FaceEyesNorm
  • bob.ip.ForwardGradient
  • bob.ip.GLCM
  • bob.ip.GLCMProp
  • bob.ip.GSSKeypoint
  • bob.ip.GSSKeypointInfo
  • bob.ip.GaborKernel
  • bob.ip.GaborWaveletTransform
  • bob.ip.Gaussian
  • bob.ip.GaussianScaleSpace
  • bob.ip.GeomNorm
  • bob.ip.GradientMagnitudeType
  • bob.ip.GradientMaps
  • bob.ip.HOG
  • bob.ip.HornAndSchunckFlow
  • bob.ip.HornAndSchunckGradient
  • bob.ip.IsotropicGradient
  • bob.ip.LBP
  • bob.ip.LBPHSFeatures
  • bob.ip.LBPTop
  • bob.ip.Median_float64
  • bob.ip.Median_uint16
  • bob.ip.Median_uint8
  • bob.ip.MultiscaleRetinex
  • bob.ip.PrewittGradient
  • bob.ip.RescaleAlgorithm
  • bob.ip.RotateAlgorithm
  • bob.ip.SIFT
  • bob.ip.SelfQuotientImage
  • bob.ip.Sobel
  • bob.ip.SobelGradient
  • bob.ip.TanTriggs
  • bob.ip.VLDSIFT
  • bob.ip.VLSIFT
  • bob.ip.VanillaHornAndSchunckFlow
  • bob.ip.WeightedGaussian
• Audio Processing
  • bob.ap.Ceps
  • bob.ap.Energy
  • bob.ap.FrameExtractor
  • bob.ap.Spectrogram
• Machines
  • bob.machine.linear_scoring
  • bob.machine.roll
  • bob.machine.tnorm
  • bob.machine.unroll
  • bob.machine.znorm
  • bob.machine.ztnorm
  • bob.machine.ztnorm_same_value
  • bob.machine.Activation
  • bob.machine.BICMachine
  • bob.machine.GMMMachine
  • bob.machine.GMMStats
  • bob.machine.GaborGraphMachine
  • bob.machine.GaborJetSimilarity
  • bob.machine.Gaussian
  • bob.machine.HyperbolicTangentActivation
  • bob.machine.ISVBase
  • bob.machine.ISVMachine
  • bob.machine.IVectorMachine
  • bob.machine.IdentityActivation
  • bob.machine.JFABase
  • bob.machine.JFAMachine
  • bob.machine.KMeansMachine
  • bob.machine.LinearActivation
  • bob.machine.LinearMachine
  • bob.machine.LogisticActivation
  • bob.machine.MLP
  • bob.machine.MachineDoubleBase
  • bob.machine.MachineGMMStatsA1DBase
  • bob.machine.MachineGMMStatsScalarBase
  • bob.machine.MultipliedHyperbolicTangentActivation
  • bob.machine.PLDABase
  • bob.machine.PLDAMachine
  • bob.machine.SVMFile
  • bob.machine.SupportVector
  • bob.machine.WienerMachine
  • bob.machine.gabor_jet_similarity_type
  • bob.machine.svm_kernel_type
  • bob.machine.svm_type
• Trainer
  • bob.trainer.BICTrainer
  • bob.trainer.Cost
  • bob.trainer.CrossEntropyLoss
  • bob.trainer.DataShuffler
  • bob.trainer.EMPCATrainer
  • bob.trainer.EMTrainerGMM
  • bob.trainer.EMTrainerIVector
  • bob.trainer.EMTrainerKMeans
  • bob.trainer.EMTrainerLinear
  • bob.trainer.EMTrainerPLDA
  • bob.trainer.FisherLDATrainer
  • bob.trainer.GMMTrainer
  • bob.trainer.ISVTrainer
  • bob.trainer.IVectorTrainer
  • bob.trainer.JFATrainer
  • bob.trainer.KMeansTrainer
  • bob.trainer.CGLogRegTrainer
  • bob.trainer.MAP_GMMTrainer
  • bob.trainer.MLPBackPropTrainer
  • bob.trainer.MLPBaseTrainer
  • bob.trainer.MLPRPropTrainer
  • bob.trainer.ML_GMMTrainer
  • bob.trainer.PCATrainer
  • bob.trainer.PLDATrainer
  • bob.trainer.SVMTrainer
  • bob.trainer.SquareError
  • bob.trainer.WCCNTrainer
  • bob.trainer.WhiteningTrainer
  • bob.trainer.WienerTrainer
• Databases
  • bob.db.utils.SQLiteConnector
  • bob.db.utils.null
  • bob.db.driver.Interface
  • bob.db.driver.dbshell
  • bob.db.driver.dbshell_command
  • bob.db.driver.files_command
  • bob.db.driver.makedirs_safe
  • bob.db.driver.print_files
  • bob.db.driver.version
  • bob.db.driver.version_command
  • bob.db.iris.data
• Metrics
  • bob.measure.cmc
  • bob.measure.correctly_classified_negatives
  • bob.measure.correctly_classified_positives
  • bob.measure.det
  • bob.measure.eer_rocch
  • bob.measure.eer_threshold
  • bob.measure.epc
  • bob.measure.f_score
  • bob.measure.far_threshold
  • bob.measure.farfrr
  • bob.measure.frr_threshold
  • bob.measure.min_hter_threshold
  • bob.measure.min_weighted_error_rate_threshold
  • bob.measure.mse
  • bob.measure.ppndf
  • bob.measure.precision_recall
  • bob.measure.precision_recall_curve
  • bob.measure.recognition_rate
  • bob.measure.relevance
  • bob.measure.rmse
  • bob.measure.roc
  • bob.measure.roc_for_far
  • bob.measure.rocch
  • bob.measure.rocch2eer
  • bob.measure.plot.cmc
  • bob.measure.plot.det
  • bob.measure.plot.det_axis
  • bob.measure.plot.epc
  • bob.measure.plot.precision_recall_curve
  • bob.measure.plot.roc
  • bob.measure.load.cmc_five_column
  • bob.measure.load.cmc_four_column
  • bob.measure.load.five_column
  • bob.measure.load.four_column
  • bob.measure.load.split_five_column
  • bob.measure.load.split_four_column

History

• History
• Authors

Licensing

• Licensing Terms

Indices and tables

• Index
• Module Index
• Search Page