├── .dockerignore
├── .gitattributes
├── .github
├── dependabot.yml
└── workflows
│ ├── docker.yml
│ ├── ffmpeg.yml
│ ├── libvmaf.yml
│ └── windows.yml
├── .gitignore
├── .travis.yml
├── CHANGELOG.md
├── CONTRIBUTING.md
├── Dockerfile
├── Dockerfile.cuda
├── LICENSE
├── Makefile
├── OSSMETADATA
├── README.md
├── libvmaf
├── README.md
├── doc
│ ├── Doxyfile.in
│ └── meson.build
├── include
│ ├── libvmaf
│ │ ├── feature.h
│ │ ├── libvmaf.h
│ │ ├── libvmaf_cuda.h
│ │ ├── meson.build
│ │ ├── model.h
│ │ ├── picture.h
│ │ └── version.h.in
│ ├── meson.build
│ └── vcs_version.h.in
├── meson.build
├── meson_options.txt
├── src
│ ├── arm
│ │ ├── cpu.c
│ │ └── cpu.h
│ ├── compat
│ │ ├── gcc
│ │ │ └── stdatomic.h
│ │ └── msvc
│ │ │ └── stdatomic.h
│ ├── cpu.c
│ ├── cpu.h
│ ├── cuda
│ │ ├── common.c
│ │ ├── common.h
│ │ ├── cuda_helper.cuh
│ │ ├── picture_cuda.c
│ │ ├── picture_cuda.h
│ │ ├── ring_buffer.c
│ │ └── ring_buffer.h
│ ├── dict.c
│ ├── dict.h
│ ├── ext
│ │ └── x86
│ │ │ └── x86inc.asm
│ ├── feature
│ │ ├── adm.c
│ │ ├── adm.h
│ │ ├── adm_options.h
│ │ ├── adm_tools.c
│ │ ├── adm_tools.h
│ │ ├── alias.c
│ │ ├── alias.h
│ │ ├── all.c
│ │ ├── ansnr.c
│ │ ├── ansnr.h
│ │ ├── ansnr_options.h
│ │ ├── ansnr_tools.c
│ │ ├── ansnr_tools.h
│ │ ├── arm64
│ │ │ ├── adm_neon.c
│ │ │ ├── adm_neon.h
│ │ │ ├── vif_neon.c
│ │ │ └── vif_neon.h
│ │ ├── cambi.c
│ │ ├── ciede.c
│ │ ├── common
│ │ │ ├── alignment.c
│ │ │ ├── alignment.h
│ │ │ ├── blur_array.c
│ │ │ ├── blur_array.h
│ │ │ ├── convolution.c
│ │ │ ├── convolution.h
│ │ │ ├── convolution_avx.c
│ │ │ ├── convolution_internal.h
│ │ │ └── macros.h
│ │ ├── cuda
│ │ │ ├── integer_adm
│ │ │ │ ├── adm_cm.cu
│ │ │ │ ├── adm_csf.cu
│ │ │ │ ├── adm_csf_den.cu
│ │ │ │ ├── adm_decouple.cu
│ │ │ │ └── adm_dwt2.cu
│ │ │ ├── integer_adm_cuda.c
│ │ │ ├── integer_adm_cuda.h
│ │ │ ├── integer_motion
│ │ │ │ └── motion_score.cu
│ │ │ ├── integer_motion_cuda.c
│ │ │ ├── integer_motion_cuda.h
│ │ │ ├── integer_vif
│ │ │ │ ├── filter1d.cu
│ │ │ │ └── vif_statistics.cuh
│ │ │ ├── integer_vif_cuda.c
│ │ │ └── integer_vif_cuda.h
│ │ ├── feature_collector.c
│ │ ├── feature_collector.h
│ │ ├── feature_extractor.c
│ │ ├── feature_extractor.h
│ │ ├── feature_name.c
│ │ ├── feature_name.h
│ │ ├── float_adm.c
│ │ ├── float_ansnr.c
│ │ ├── float_moment.c
│ │ ├── float_motion.c
│ │ ├── float_ms_ssim.c
│ │ ├── float_psnr.c
│ │ ├── float_ssim.c
│ │ ├── float_vif.c
│ │ ├── integer_adm.c
│ │ ├── integer_adm.h
│ │ ├── integer_motion.c
│ │ ├── integer_motion.h
│ │ ├── integer_psnr.c
│ │ ├── integer_ssim.c
│ │ ├── integer_vif.c
│ │ ├── integer_vif.h
│ │ ├── iqa
│ │ │ ├── convolve.c
│ │ │ ├── convolve.h
│ │ │ ├── decimate.c
│ │ │ ├── decimate.h
│ │ │ ├── iqa.h
│ │ │ ├── iqa_options.h
│ │ │ ├── iqa_os.h
│ │ │ ├── math_utils.c
│ │ │ ├── math_utils.h
│ │ │ ├── ssim_tools.c
│ │ │ └── ssim_tools.h
│ │ ├── luminance_tools.c
│ │ ├── luminance_tools.h
│ │ ├── mkdirp.c
│ │ ├── mkdirp.h
│ │ ├── moment.c
│ │ ├── moment.h
│ │ ├── moment_options.h
│ │ ├── motion.c
│ │ ├── motion.h
│ │ ├── motion_options.h
│ │ ├── motion_tools.h
│ │ ├── ms_ssim.c
│ │ ├── ms_ssim.h
│ │ ├── null.c
│ │ ├── offset.c
│ │ ├── offset.h
│ │ ├── picture_copy.c
│ │ ├── picture_copy.h
│ │ ├── psnr.c
│ │ ├── psnr.h
│ │ ├── psnr_options.h
│ │ ├── psnr_tools.c
│ │ ├── psnr_tools.h
│ │ ├── ssim.c
│ │ ├── ssim.h
│ │ ├── third_party
│ │ │ └── xiph
│ │ │ │ └── psnr_hvs.c
│ │ ├── vif.c
│ │ ├── vif.h
│ │ ├── vif_options.h
│ │ ├── vif_tools.c
│ │ ├── vif_tools.h
│ │ └── x86
│ │ │ ├── adm_avx2.c
│ │ │ ├── adm_avx2.h
│ │ │ ├── cambi_avx2.c
│ │ │ ├── cambi_avx2.h
│ │ │ ├── motion_avx2.c
│ │ │ ├── motion_avx2.h
│ │ │ ├── motion_avx512.c
│ │ │ ├── motion_avx512.h
│ │ │ ├── vif_avx2.c
│ │ │ ├── vif_avx2.h
│ │ │ ├── vif_avx512.c
│ │ │ └── vif_avx512.h
│ ├── fex_ctx_vector.c
│ ├── fex_ctx_vector.h
│ ├── framesync.c
│ ├── framesync.h
│ ├── libvmaf.c
│ ├── log.c
│ ├── log.h
│ ├── mem.c
│ ├── mem.h
│ ├── meson.build
│ ├── metadata_handler.c
│ ├── metadata_handler.h
│ ├── model.c
│ ├── model.h
│ ├── opt.c
│ ├── opt.h
│ ├── output.c
│ ├── output.h
│ ├── pdjson.c
│ ├── pdjson.h
│ ├── picture.c
│ ├── picture.h
│ ├── predict.c
│ ├── predict.h
│ ├── read_json_model.c
│ ├── read_json_model.h
│ ├── ref.c
│ ├── ref.h
│ ├── svm.cpp
│ ├── svm.h
│ ├── thread_pool.c
│ ├── thread_pool.h
│ └── x86
│ │ ├── cpu.c
│ │ ├── cpu.h
│ │ └── cpuid.asm
├── test
│ ├── meson.build
│ ├── test.c
│ ├── test.h
│ ├── test_cambi.c
│ ├── test_ciede.c
│ ├── test_cli_parse.c
│ ├── test_context.c
│ ├── test_cpu.c
│ ├── test_cuda_pic_preallocation.c
│ ├── test_dict.c
│ ├── test_feature.c
│ ├── test_feature_collector.c
│ ├── test_feature_extractor.c
│ ├── test_framesync.c
│ ├── test_log.c
│ ├── test_luminance_tools.c
│ ├── test_model.c
│ ├── test_picture.c
│ ├── test_predict.c
│ ├── test_propagate_metadata.c
│ ├── test_psnr.c
│ ├── test_ref.c
│ ├── test_ring_buffer.c
│ └── test_thread_pool.c
└── tools
│ ├── README.md
│ ├── cli_parse.c
│ ├── cli_parse.h
│ ├── meson.build
│ ├── spinner.h
│ ├── test
│ ├── meson.build
│ └── test_vmaf_cuda_gpumask.sh
│ ├── vidinput.c
│ ├── vidinput.h
│ ├── vmaf.c
│ ├── y4m_input.c
│ └── yuv_input.c
├── matlab
├── .gitignore
├── STMAD_2011_MatlabCode
│ ├── Example.m
│ ├── MotionWeight.m
│ ├── STMAD_index.m
│ ├── calcSMADScore.m
│ ├── calcSTMADScore.m
│ ├── calculateSMADScore.m
│ ├── hi_index.m
│ ├── ical_stat.c
│ ├── ical_stat.mexa64
│ ├── ical_stat.mexmaci64
│ ├── ical_stat.mexw64
│ ├── ical_std.c
│ ├── ical_std.mexa64
│ ├── ical_std.mexmaci64
│ ├── ical_std.mexw64
│ ├── lo_index.m
│ ├── readframefromfid.m
│ ├── run_smad.m
│ ├── run_stmad.m
│ └── yuvread.m
├── SpEED
│ ├── SpEED
│ │ ├── Single_Scale_Video_SPEED.m
│ │ ├── calcSpEEDScore.m
│ │ ├── est_params.m
│ │ └── readframefromfid_all_fmts.m
│ └── run_speed.m
├── cid_icid
│ ├── BT709_f.mat
│ ├── BT709_l.mat
│ ├── iCID
│ │ └── iCID_Metric
│ │ │ ├── ColorSpaceTransformations
│ │ │ ├── FilterImageCSF.m
│ │ │ ├── ImageSRGB2XYZ.m
│ │ │ ├── ImageXYZ2LAB2000HL.m
│ │ │ ├── LAB2000HL.mat
│ │ │ ├── LAB2LAB2000HL.m
│ │ │ ├── SRGB2XYZ.m
│ │ │ ├── XYZ2LAB.m
│ │ │ └── colorspace.m
│ │ │ ├── README.txt
│ │ │ └── iCID.m
│ ├── run_icid.m
│ ├── yuv2rgb.m
│ └── yuvread.m
└── strred
│ ├── README
│ ├── SR_SIM.m
│ ├── matlabPyrTools
│ ├── ChangeLog
│ ├── Contents.m
│ ├── MEX
│ │ ├── -MacReadMe
│ │ ├── .AppleDouble
│ │ │ └── .Parent
│ │ ├── .FBCIndex
│ │ ├── .FBCLockFolder
│ │ │ └── .FBCSemaphoreFile
│ │ ├── Copy_of_corrDn.mexmac
│ │ ├── Makefile-linux
│ │ ├── Makefile-ml6-linux
│ │ ├── Makefile-osx
│ │ ├── Makefile-solaris
│ │ ├── Makefile-sun4
│ │ ├── convolve.c
│ │ ├── convolve.h
│ │ ├── corrDn.c
│ │ ├── corrDn.dll
│ │ ├── corrDn.exp
│ │ ├── corrDn.lib
│ │ ├── corrDn.mex
│ │ ├── corrDn.mex4
│ │ ├── corrDn.mexa64
│ │ ├── corrDn.mexglx
│ │ ├── corrDn.mexlx
│ │ ├── corrDn.mexmac
│ │ ├── corrDn.mexsol
│ │ ├── corrDn.mexw32
│ │ ├── edges-orig.c
│ │ ├── edges.c
│ │ ├── histo.c
│ │ ├── histo.dll
│ │ ├── histo.mex
│ │ ├── histo.mex4
│ │ ├── histo.mexglx
│ │ ├── histo.mexlx
│ │ ├── histo.mexmac
│ │ ├── histo.mexsol
│ │ ├── innerProd.c
│ │ ├── innerProd.dll
│ │ ├── innerProd.mexglx
│ │ ├── innerProd.mexlx
│ │ ├── innerProd.mexmac
│ │ ├── innerProd.mexsol
│ │ ├── pointOp.c
│ │ ├── pointOp.dll
│ │ ├── pointOp.mex
│ │ ├── pointOp.mex4
│ │ ├── pointOp.mexglx
│ │ ├── pointOp.mexlx
│ │ ├── pointOp.mexmac
│ │ ├── pointOp.mexsol
│ │ ├── pointOp.o
│ │ ├── range2.c
│ │ ├── range2.dll
│ │ ├── range2.mex
│ │ ├── range2.mex4
│ │ ├── range2.mexglx
│ │ ├── range2.mexlx
│ │ ├── range2.mexmac
│ │ ├── range2.mexsol
│ │ ├── range2.o
│ │ ├── upConv.c
│ │ ├── upConv.dll
│ │ ├── upConv.mex
│ │ ├── upConv.mex4
│ │ ├── upConv.mexglx
│ │ ├── upConv.mexlx
│ │ ├── upConv.mexmac
│ │ ├── upConv.mexsol
│ │ ├── upConv.o
│ │ └── wrap.c
│ ├── README
│ ├── TUTORIALS
│ │ ├── README
│ │ ├── matlabPyrTools.m
│ │ └── pyramids.m
│ ├── binomialFilter.m
│ ├── blur.m
│ ├── blurDn.m
│ ├── buildGpyr.m
│ ├── buildLpyr.m
│ ├── buildSCFpyr.m
│ ├── buildSCFpyrLevs.m
│ ├── buildSFpyr.m
│ ├── buildSFpyrLevs.m
│ ├── buildSpyr.m
│ ├── buildSpyrLevs.m
│ ├── buildWpyr.m
│ ├── cconv2.m
│ ├── clip.m
│ ├── corrDn.m
│ ├── einstein.pgm
│ ├── entropy2.m
│ ├── factorial.m
│ ├── feynman.pgm
│ ├── histo.m
│ ├── histoMatch.m
│ ├── ifftshift.m
│ ├── imGradient.m
│ ├── imStats.m
│ ├── innerProd.m
│ ├── kurt2.m
│ ├── lplot.m
│ ├── lpyrHt.m
│ ├── maxPyrHt.m
│ ├── mean2.m
│ ├── mkAngle.m
│ ├── mkAngularSine.m
│ ├── mkDisc.m
│ ├── mkFract.m
│ ├── mkGaussian.m
│ ├── mkImpulse.m
│ ├── mkR.m
│ ├── mkRamp.m
│ ├── mkSine.m
│ ├── mkSquare.m
│ ├── mkZonePlate.m
│ ├── mod1.m
│ ├── model_pyr.m
│ ├── modulateFlip.m
│ ├── namedFilter.m
│ ├── nextFig.m
│ ├── pgmRead.m
│ ├── pgmWrite.m
│ ├── pixelAxes.m
│ ├── pointOp.m
│ ├── pwd2path.m
│ ├── pyrBand.m
│ ├── pyrBandIndices.m
│ ├── pyrLow.m
│ ├── range2.m
│ ├── rconv2.m
│ ├── rcosFn.m
│ ├── reconLpyr.m
│ ├── reconSCFpyr.m
│ ├── reconSFpyr.m
│ ├── reconSFpyrLevs.m
│ ├── reconSpyr.m
│ ├── reconSpyrLevs.m
│ ├── reconWpyr.m
│ ├── setPyrBand.m
│ ├── shift.m
│ ├── showIm.m
│ ├── showLpyr.m
│ ├── showSpyr.m
│ ├── showWpyr.m
│ ├── simulate.m
│ ├── skew2.m
│ ├── sp0Filters.m
│ ├── sp1Filters.m
│ ├── sp3Filters.m
│ ├── sp5Filters.m
│ ├── spyrBand.m
│ ├── spyrHigh.m
│ ├── spyrHt.m
│ ├── spyrLev.m
│ ├── spyrNumBands.m
│ ├── steer.m
│ ├── steer2HarmMtx.m
│ ├── subMtx.m
│ ├── upBlur.m
│ ├── upConv.m
│ ├── var2.m
│ ├── vectify.m
│ ├── wpyrBand.m
│ ├── wpyrHt.m
│ ├── wpyrLev.m
│ └── zconv2.m
│ ├── run_strred.m
│ ├── run_strred_opt.m
│ ├── strred
│ ├── buildSpyr_single.m
│ ├── calcStrredScore.m
│ ├── calcStrredScore_opt.m
│ ├── est_params.m
│ ├── extract_info.m
│ ├── extract_info_opt.m
│ ├── ind2wtree.m
│ ├── readframefromfid.m
│ └── rred2dmos.m
│ └── workspace
│ └── .gitignore
├── model
├── other_models
│ ├── model_V8a.model
│ ├── nflx_v1.json
│ ├── nflx_v1.pkl
│ ├── nflx_v1.pkl.model
│ ├── nflx_vmaff_rf_v1.pkl
│ ├── nflx_vmaff_rf_v2.pkl
│ ├── nflxall_libsvmnusvr_currentbest.pkl
│ ├── nflxall_libsvmnusvr_currentbest.pkl.model
│ ├── nflxall_vmafv1.pkl
│ ├── nflxall_vmafv1.pkl.model
│ ├── nflxall_vmafv2.pkl
│ ├── nflxall_vmafv2.pkl.model
│ ├── nflxall_vmafv3.pkl
│ ├── nflxall_vmafv3.pkl.model
│ ├── nflxall_vmafv3a.pkl
│ ├── nflxall_vmafv3a.pkl.model
│ ├── nflxall_vmafv4.pkl
│ ├── nflxall_vmafv4.pkl.model
│ ├── nflxtrain_libsvmnusvr_currentbest.pkl
│ ├── nflxtrain_libsvmnusvr_currentbest.pkl.model
│ ├── nflxtrain_norm_type_none.json
│ ├── nflxtrain_norm_type_none.pkl
│ ├── nflxtrain_norm_type_none.pkl.model
│ ├── nflxtrain_vmafv1.pkl
│ ├── nflxtrain_vmafv1.pkl.model
│ ├── nflxtrain_vmafv2.pkl
│ ├── nflxtrain_vmafv2.pkl.model
│ ├── nflxtrain_vmafv3.pkl
│ ├── nflxtrain_vmafv3.pkl.model
│ ├── nflxtrain_vmafv3a.pkl
│ ├── nflxtrain_vmafv3a.pkl.model
│ ├── niqe_v0.1.pkl
│ ├── vmaf_4k_v0.6.1rc.pkl
│ ├── vmaf_4k_v0.6.1rc.pkl.model
│ ├── vmaf_v0.6.0.json
│ ├── vmaf_v0.6.0.pkl
│ ├── vmaf_v0.6.0.pkl.model
│ └── vmaf_v0.6.1mfz.json
├── vmaf_4k_rb_v0.6.2
│ ├── vmaf_4k_rb_v0.6.2.json
│ ├── vmaf_4k_rb_v0.6.2.pkl
│ ├── vmaf_4k_rb_v0.6.2.pkl.0001
│ ├── vmaf_4k_rb_v0.6.2.pkl.0001.model
│ ├── vmaf_4k_rb_v0.6.2.pkl.0002
│ ├── vmaf_4k_rb_v0.6.2.pkl.0002.model
│ ├── vmaf_4k_rb_v0.6.2.pkl.0003
│ ├── vmaf_4k_rb_v0.6.2.pkl.0003.model
│ ├── vmaf_4k_rb_v0.6.2.pkl.0004
│ ├── vmaf_4k_rb_v0.6.2.pkl.0004.model
│ ├── vmaf_4k_rb_v0.6.2.pkl.0005
│ ├── vmaf_4k_rb_v0.6.2.pkl.0005.model
│ ├── vmaf_4k_rb_v0.6.2.pkl.0006
│ ├── vmaf_4k_rb_v0.6.2.pkl.0006.model
│ ├── vmaf_4k_rb_v0.6.2.pkl.0007
│ ├── vmaf_4k_rb_v0.6.2.pkl.0007.model
│ ├── vmaf_4k_rb_v0.6.2.pkl.0008
│ ├── vmaf_4k_rb_v0.6.2.pkl.0008.model
│ ├── vmaf_4k_rb_v0.6.2.pkl.0009
│ ├── vmaf_4k_rb_v0.6.2.pkl.0009.model
│ ├── vmaf_4k_rb_v0.6.2.pkl.0010
│ ├── vmaf_4k_rb_v0.6.2.pkl.0010.model
│ ├── vmaf_4k_rb_v0.6.2.pkl.0011
│ ├── vmaf_4k_rb_v0.6.2.pkl.0011.model
│ ├── vmaf_4k_rb_v0.6.2.pkl.0012
│ ├── vmaf_4k_rb_v0.6.2.pkl.0012.model
│ ├── vmaf_4k_rb_v0.6.2.pkl.0013
│ ├── vmaf_4k_rb_v0.6.2.pkl.0013.model
│ ├── vmaf_4k_rb_v0.6.2.pkl.0014
│ ├── vmaf_4k_rb_v0.6.2.pkl.0014.model
│ ├── vmaf_4k_rb_v0.6.2.pkl.0015
│ ├── vmaf_4k_rb_v0.6.2.pkl.0015.model
│ ├── vmaf_4k_rb_v0.6.2.pkl.0016
│ ├── vmaf_4k_rb_v0.6.2.pkl.0016.model
│ ├── vmaf_4k_rb_v0.6.2.pkl.0017
│ ├── vmaf_4k_rb_v0.6.2.pkl.0017.model
│ ├── vmaf_4k_rb_v0.6.2.pkl.0018
│ ├── vmaf_4k_rb_v0.6.2.pkl.0018.model
│ ├── vmaf_4k_rb_v0.6.2.pkl.0019
│ ├── vmaf_4k_rb_v0.6.2.pkl.0019.model
│ └── vmaf_4k_rb_v0.6.2.pkl.model
├── vmaf_4k_v0.6.1.json
├── vmaf_4k_v0.6.1neg.json
├── vmaf_b_v0.6.3.json
├── vmaf_float_4k_v0.6.1.json
├── vmaf_float_b_v0.6.3.json
├── vmaf_float_b_v0.6.3
│ ├── vmaf_float_b_v0.6.3.json
│ ├── vmaf_float_b_v0.6.3.pkl
│ ├── vmaf_float_b_v0.6.3.pkl.0001
│ ├── vmaf_float_b_v0.6.3.pkl.0001.model
│ ├── vmaf_float_b_v0.6.3.pkl.0002
│ ├── vmaf_float_b_v0.6.3.pkl.0002.model
│ ├── vmaf_float_b_v0.6.3.pkl.0003
│ ├── vmaf_float_b_v0.6.3.pkl.0003.model
│ ├── vmaf_float_b_v0.6.3.pkl.0004
│ ├── vmaf_float_b_v0.6.3.pkl.0004.model
│ ├── vmaf_float_b_v0.6.3.pkl.0005
│ ├── vmaf_float_b_v0.6.3.pkl.0005.model
│ ├── vmaf_float_b_v0.6.3.pkl.0006
│ ├── vmaf_float_b_v0.6.3.pkl.0006.model
│ ├── vmaf_float_b_v0.6.3.pkl.0007
│ ├── vmaf_float_b_v0.6.3.pkl.0007.model
│ ├── vmaf_float_b_v0.6.3.pkl.0008
│ ├── vmaf_float_b_v0.6.3.pkl.0008.model
│ ├── vmaf_float_b_v0.6.3.pkl.0009
│ ├── vmaf_float_b_v0.6.3.pkl.0009.model
│ ├── vmaf_float_b_v0.6.3.pkl.0010
│ ├── vmaf_float_b_v0.6.3.pkl.0010.model
│ ├── vmaf_float_b_v0.6.3.pkl.0011
│ ├── vmaf_float_b_v0.6.3.pkl.0011.model
│ ├── vmaf_float_b_v0.6.3.pkl.0012
│ ├── vmaf_float_b_v0.6.3.pkl.0012.model
│ ├── vmaf_float_b_v0.6.3.pkl.0013
│ ├── vmaf_float_b_v0.6.3.pkl.0013.model
│ ├── vmaf_float_b_v0.6.3.pkl.0014
│ ├── vmaf_float_b_v0.6.3.pkl.0014.model
│ ├── vmaf_float_b_v0.6.3.pkl.0015
│ ├── vmaf_float_b_v0.6.3.pkl.0015.model
│ ├── vmaf_float_b_v0.6.3.pkl.0016
│ ├── vmaf_float_b_v0.6.3.pkl.0016.model
│ ├── vmaf_float_b_v0.6.3.pkl.0017
│ ├── vmaf_float_b_v0.6.3.pkl.0017.model
│ ├── vmaf_float_b_v0.6.3.pkl.0018
│ ├── vmaf_float_b_v0.6.3.pkl.0018.model
│ ├── vmaf_float_b_v0.6.3.pkl.0019
│ ├── vmaf_float_b_v0.6.3.pkl.0019.model
│ ├── vmaf_float_b_v0.6.3.pkl.0020
│ ├── vmaf_float_b_v0.6.3.pkl.0020.model
│ └── vmaf_float_b_v0.6.3.pkl.model
├── vmaf_float_v0.6.1.json
├── vmaf_float_v0.6.1.pkl
├── vmaf_float_v0.6.1.pkl.model
├── vmaf_float_v0.6.1neg.json
├── vmaf_float_v0.6.1neg.pkl
├── vmaf_float_v0.6.1neg.pkl.model
├── vmaf_rb_v0.6.2
│ ├── vmaf_rb_v0.6.2.json
│ ├── vmaf_rb_v0.6.2.pkl
│ ├── vmaf_rb_v0.6.2.pkl.0001
│ ├── vmaf_rb_v0.6.2.pkl.0001.model
│ ├── vmaf_rb_v0.6.2.pkl.0002
│ ├── vmaf_rb_v0.6.2.pkl.0002.model
│ ├── vmaf_rb_v0.6.2.pkl.0003
│ ├── vmaf_rb_v0.6.2.pkl.0003.model
│ ├── vmaf_rb_v0.6.2.pkl.0004
│ ├── vmaf_rb_v0.6.2.pkl.0004.model
│ ├── vmaf_rb_v0.6.2.pkl.0005
│ ├── vmaf_rb_v0.6.2.pkl.0005.model
│ ├── vmaf_rb_v0.6.2.pkl.0006
│ ├── vmaf_rb_v0.6.2.pkl.0006.model
│ ├── vmaf_rb_v0.6.2.pkl.0007
│ ├── vmaf_rb_v0.6.2.pkl.0007.model
│ ├── vmaf_rb_v0.6.2.pkl.0008
│ ├── vmaf_rb_v0.6.2.pkl.0008.model
│ ├── vmaf_rb_v0.6.2.pkl.0009
│ ├── vmaf_rb_v0.6.2.pkl.0009.model
│ ├── vmaf_rb_v0.6.2.pkl.0010
│ ├── vmaf_rb_v0.6.2.pkl.0010.model
│ ├── vmaf_rb_v0.6.2.pkl.0011
│ ├── vmaf_rb_v0.6.2.pkl.0011.model
│ ├── vmaf_rb_v0.6.2.pkl.0012
│ ├── vmaf_rb_v0.6.2.pkl.0012.model
│ ├── vmaf_rb_v0.6.2.pkl.0013
│ ├── vmaf_rb_v0.6.2.pkl.0013.model
│ ├── vmaf_rb_v0.6.2.pkl.0014
│ ├── vmaf_rb_v0.6.2.pkl.0014.model
│ ├── vmaf_rb_v0.6.2.pkl.0015
│ ├── vmaf_rb_v0.6.2.pkl.0015.model
│ ├── vmaf_rb_v0.6.2.pkl.0016
│ ├── vmaf_rb_v0.6.2.pkl.0016.model
│ ├── vmaf_rb_v0.6.2.pkl.0017
│ ├── vmaf_rb_v0.6.2.pkl.0017.model
│ ├── vmaf_rb_v0.6.2.pkl.0018
│ ├── vmaf_rb_v0.6.2.pkl.0018.model
│ ├── vmaf_rb_v0.6.2.pkl.0019
│ ├── vmaf_rb_v0.6.2.pkl.0019.model
│ └── vmaf_rb_v0.6.2.pkl.model
├── vmaf_rb_v0.6.3
│ ├── vmaf_rb_v0.6.3.json
│ ├── vmaf_rb_v0.6.3.pkl
│ ├── vmaf_rb_v0.6.3.pkl.0001
│ ├── vmaf_rb_v0.6.3.pkl.0001.model
│ ├── vmaf_rb_v0.6.3.pkl.0002
│ ├── vmaf_rb_v0.6.3.pkl.0002.model
│ ├── vmaf_rb_v0.6.3.pkl.0003
│ ├── vmaf_rb_v0.6.3.pkl.0003.model
│ ├── vmaf_rb_v0.6.3.pkl.0004
│ ├── vmaf_rb_v0.6.3.pkl.0004.model
│ ├── vmaf_rb_v0.6.3.pkl.0005
│ ├── vmaf_rb_v0.6.3.pkl.0005.model
│ ├── vmaf_rb_v0.6.3.pkl.0006
│ ├── vmaf_rb_v0.6.3.pkl.0006.model
│ ├── vmaf_rb_v0.6.3.pkl.0007
│ ├── vmaf_rb_v0.6.3.pkl.0007.model
│ ├── vmaf_rb_v0.6.3.pkl.0008
│ ├── vmaf_rb_v0.6.3.pkl.0008.model
│ ├── vmaf_rb_v0.6.3.pkl.0009
│ ├── vmaf_rb_v0.6.3.pkl.0009.model
│ ├── vmaf_rb_v0.6.3.pkl.0010
│ ├── vmaf_rb_v0.6.3.pkl.0010.model
│ ├── vmaf_rb_v0.6.3.pkl.0011
│ ├── vmaf_rb_v0.6.3.pkl.0011.model
│ ├── vmaf_rb_v0.6.3.pkl.0012
│ ├── vmaf_rb_v0.6.3.pkl.0012.model
│ ├── vmaf_rb_v0.6.3.pkl.0013
│ ├── vmaf_rb_v0.6.3.pkl.0013.model
│ ├── vmaf_rb_v0.6.3.pkl.0014
│ ├── vmaf_rb_v0.6.3.pkl.0014.model
│ ├── vmaf_rb_v0.6.3.pkl.0015
│ ├── vmaf_rb_v0.6.3.pkl.0015.model
│ ├── vmaf_rb_v0.6.3.pkl.0016
│ ├── vmaf_rb_v0.6.3.pkl.0016.model
│ ├── vmaf_rb_v0.6.3.pkl.0017
│ ├── vmaf_rb_v0.6.3.pkl.0017.model
│ ├── vmaf_rb_v0.6.3.pkl.0018
│ ├── vmaf_rb_v0.6.3.pkl.0018.model
│ ├── vmaf_rb_v0.6.3.pkl.0019
│ ├── vmaf_rb_v0.6.3.pkl.0019.model
│ ├── vmaf_rb_v0.6.3.pkl.0020
│ ├── vmaf_rb_v0.6.3.pkl.0020.model
│ └── vmaf_rb_v0.6.3.pkl.model
├── vmaf_v0.6.1.json
└── vmaf_v0.6.1neg.json
├── python
├── .gitignore
├── DEVELOP.md
├── README.rst
├── pyproject.toml
├── requirements.txt
├── setup.py
├── test
│ ├── __init__.py
│ ├── asset_test.py
│ ├── bd_rate_calculator_test.py
│ ├── bootstrap_train_test_model_test.py
│ ├── calculate_bd_rate_test.py
│ ├── cambi_test.py
│ ├── command_line_test.py
│ ├── conftest.py
│ ├── cross_validation_test.py
│ ├── cy_test.py
│ ├── doctest_test.py
│ ├── executor_test.py
│ ├── feature_assembler_test.py
│ ├── feature_extractor_test.py
│ ├── local_explainer_test.py
│ ├── niqe_train_test_model_test.py
│ ├── noref_feature_extractor_test.py
│ ├── perf_metric_test.py
│ ├── quality_runner_test.py
│ ├── raw_extractor_test.py
│ ├── reader_test.py
│ ├── requirements.txt
│ ├── resource
│ │ ├── NFLX_dataset_public_raw.py
│ │ ├── data_Toyama.mat
│ │ ├── dataset_sample.py
│ │ ├── example_batch_input
│ │ ├── example_dataset.py
│ │ ├── example_dataset_crop_pad.py
│ │ ├── example_dataset_crop_pad_duration_sec.py
│ │ ├── example_raw_dataset.py
│ │ ├── example_raw_dataset2.py
│ │ ├── example_raw_dataset3.py
│ │ ├── example_raw_dataset4.py
│ │ ├── feature_param_sample.py
│ │ ├── feature_param_sample_with_optional_dict.py
│ │ ├── feature_param_sample_with_optional_dict_good.py
│ │ ├── model
│ │ │ ├── vmaf_float_v0.6.1_nvd6.json
│ │ │ ├── vmaf_float_v0.6.1_rdh540.json
│ │ │ ├── vmaf_float_v0.6.1_vifks1o2.json
│ │ │ ├── vmaf_float_v0.6.1_vifks2.json
│ │ │ ├── vmaf_float_v0.6.1_vifks24o10.json
│ │ │ ├── vmaf_float_v0.6.1_vifks2o3.json
│ │ │ ├── vmaf_float_v0.6.1_vifks360o97.json
│ │ │ ├── vmaf_float_v0.6.1_vifks3o2.json
│ │ │ ├── vmaf_v0.6.1_nvd6.json
│ │ │ ├── vmaf_v0.6.1_rdh2160_nvd1d5.json
│ │ │ ├── vmaf_v0.6.1_rdh540.json
│ │ │ ├── vmafplus_v0.5.2_test.json
│ │ │ ├── vmafplus_v0.5.2boot_test.json
│ │ │ ├── vmafplus_v0.5.2boot_test.pkl
│ │ │ ├── vmafplus_v0.5.2boot_test.pkl.0001
│ │ │ ├── vmafplus_v0.5.2boot_test.pkl.0001.model
│ │ │ ├── vmafplus_v0.5.2boot_test.pkl.0002
│ │ │ ├── vmafplus_v0.5.2boot_test.pkl.0002.model
│ │ │ ├── vmafplus_v0.5.2boot_test.pkl.0003
│ │ │ ├── vmafplus_v0.5.2boot_test.pkl.0003.model
│ │ │ ├── vmafplus_v0.5.2boot_test.pkl.0004
│ │ │ ├── vmafplus_v0.5.2boot_test.pkl.0004.model
│ │ │ ├── vmafplus_v0.5.2boot_test.pkl.model
│ │ │ ├── vmafplus_v0.5.2boot_test2.json
│ │ │ ├── vmafplus_v0.5.2boot_test2.pkl
│ │ │ ├── vmafplus_v0.5.2boot_test2.pkl.0001
│ │ │ ├── vmafplus_v0.5.2boot_test2.pkl.0001.model
│ │ │ ├── vmafplus_v0.5.2boot_test2.pkl.0002
│ │ │ ├── vmafplus_v0.5.2boot_test2.pkl.0002.model
│ │ │ ├── vmafplus_v0.5.2boot_test2.pkl.0003
│ │ │ ├── vmafplus_v0.5.2boot_test2.pkl.0003.model
│ │ │ ├── vmafplus_v0.5.2boot_test2.pkl.0004
│ │ │ ├── vmafplus_v0.5.2boot_test2.pkl.0004.model
│ │ │ ├── vmafplus_v0.5.2boot_test2.pkl.0005
│ │ │ ├── vmafplus_v0.5.2boot_test2.pkl.0005.model
│ │ │ ├── vmafplus_v0.5.2boot_test2.pkl.0006
│ │ │ ├── vmafplus_v0.5.2boot_test2.pkl.0006.model
│ │ │ ├── vmafplus_v0.5.2boot_test2.pkl.0007
│ │ │ ├── vmafplus_v0.5.2boot_test2.pkl.0007.model
│ │ │ ├── vmafplus_v0.5.2boot_test2.pkl.0008
│ │ │ ├── vmafplus_v0.5.2boot_test2.pkl.0008.model
│ │ │ ├── vmafplus_v0.5.2boot_test2.pkl.0009
│ │ │ ├── vmafplus_v0.5.2boot_test2.pkl.0009.model
│ │ │ └── vmafplus_v0.5.2boot_test2.pkl.model
│ │ ├── model_param_sample.py
│ │ ├── raw_dataset_sample.py
│ │ ├── result_with_none.txt
│ │ ├── ssim_result_for_test.txt
│ │ ├── test_dataset.py
│ │ ├── test_dataset_bad_fps_rebufinds.py
│ │ ├── test_dataset_diffyuv.py
│ │ ├── test_dataset_fps_bad_rebufinds.py
│ │ ├── test_dataset_fps_rebufinds.py
│ │ ├── test_dataset_mixed.py
│ │ ├── test_image_dataset.py
│ │ ├── test_image_dataset_diffdim.py
│ │ ├── test_image_dataset_diffdim2.py
│ │ ├── test_image_dataset_diffdim_qualitywh.py
│ │ ├── test_image_dataset_diffdim_qualitywh2.py
│ │ ├── test_image_dataset_noisy.py
│ │ ├── test_image_dataset_notyuv.py
│ │ ├── test_image_dataset_notyuv_workfile_yuv_type.py
│ │ ├── test_model_transform_add40.json
│ │ ├── test_model_transform_add40.pkl
│ │ ├── test_model_transform_add40.pkl.model
│ │ ├── test_model_transform_add40_outltein.json
│ │ ├── test_model_transform_add40_outltein.pkl
│ │ ├── test_model_transform_add40_outltein.pkl.model
│ │ ├── test_model_transform_add40_piecewiselinear.json
│ │ ├── test_model_transform_add40_piecewiselinear_forced.json
│ │ ├── test_motion2.json
│ │ ├── test_motion2.pkl
│ │ ├── test_motion2.pkl.model
│ │ ├── test_read_dataset_dataset.py
│ │ ├── test_read_dataset_dataset2.py
│ │ ├── test_read_dataset_dataset3.py
│ │ ├── vmaf_float_v0.6.1neg.inconsist.json
│ │ ├── vmaf_float_v0.6.1neg.inconsist.pkl
│ │ ├── vmaf_float_v0.6.1neg.inconsist.pkl.model
│ │ ├── vmaf_v4.py
│ │ ├── vmafplus_laptop_480source_vmafplusv2_sa.json
│ │ ├── vmafplus_laptop_480source_vmafplusv2_sa.pkl
│ │ ├── vmafplus_laptop_480source_vmafplusv2_sa.pkl.model
│ │ ├── vmafplus_v6_bootstrap_test.py
│ │ └── vmafplus_v6_bootstrap_test2.py
│ ├── result_test.py
│ ├── routine_test.py
│ ├── testutil.py
│ ├── third_party
│ │ └── xiph
│ │ │ └── vmafexec_feature_extractor_test.py
│ ├── tools_test.py
│ ├── train_test_model_test.py
│ ├── vmafexec_feature_extractor_test.py
│ └── vmafexec_test.py
├── tox.ini
└── vmaf
│ ├── __init__.py
│ ├── config.py
│ ├── core
│ ├── __init__.py
│ ├── adm_dwt2_cy.pyx
│ ├── adm_dwt2_py.py
│ ├── adm_dwt2_tools.py
│ ├── asset.py
│ ├── cambi_feature_extractor.py
│ ├── cambi_quality_runner.py
│ ├── cross_validation.py
│ ├── executor.py
│ ├── feature_assembler.py
│ ├── feature_extractor.py
│ ├── h5py_mixin.py
│ ├── local_explainer.py
│ ├── matlab_feature_extractor.py
│ ├── matlab_quality_runner.py
│ ├── mixin.py
│ ├── niqe_train_test_model.py
│ ├── nn_train_test_model.py
│ ├── noref_feature_extractor.py
│ ├── perf_metric.py
│ ├── proc_func.py
│ ├── quality_runner.py
│ ├── quality_runner_extra.py
│ ├── raw_extractor.py
│ ├── result.py
│ ├── result_store.py
│ ├── train_test_model.py
│ └── vmafexec_feature_extractor.py
│ ├── model
│ ├── vmaf_v0.6.1.json
│ └── vmaf_v0.6.1neg.json
│ ├── routine.py
│ ├── script
│ ├── __init__.py
│ ├── convert_model_from_pkl_to_json.py
│ ├── convert_vmaf_model_to_vmaf_no_enhn_gain_model.py
│ ├── run_cleaning_cache.py
│ ├── run_psnr.py
│ ├── run_result_assembly.py
│ ├── run_testing.py
│ ├── run_toddnoiseclassifier.py
│ ├── run_vmaf.py
│ ├── run_vmaf_cross_validation.py
│ └── run_vmaf_training.py
│ ├── third_party
│ ├── __init__.py
│ └── xiph
│ │ ├── __init__.py
│ │ └── vmafexec_feature_extractor.py
│ └── tools
│ ├── __init__.py
│ ├── bd_rate.py
│ ├── bd_rate_calculator.py
│ ├── convex_hull.py
│ ├── decorator.py
│ ├── exceptions.py
│ ├── interpolation_utils.py
│ ├── kimchi.py
│ ├── misc.py
│ ├── plot.py
│ ├── reader.py
│ ├── resource
│ └── Hanley_McNeil.mat
│ ├── scanf.py
│ ├── sigproc.py
│ ├── stats.py
│ ├── testutils.py
│ ├── typing_utils.py
│ └── writer.py
├── resource
├── dataset
│ ├── BSDS500_noisy_dataset.py
│ ├── NFLX_dataset_public.py
│ ├── NFLX_dataset_public_raw.py
│ ├── NFLX_dataset_public_raw_last4outliers.py
│ ├── VQEGHD3_dataset.py
│ └── VQEGHD3_dataset_raw.py
├── doc
│ ├── aom_ctc.md
│ ├── bad_cases.md
│ ├── cambi.md
│ ├── conf_interval.md
│ ├── datasets.md
│ ├── docker.md
│ ├── external_resource.md
│ ├── faq.md
│ ├── features.md
│ ├── ffmpeg.md
│ ├── index.md
│ ├── matlab_usage.md
│ ├── models.md
│ ├── nflx_ctc.md
│ ├── papers
│ │ └── CAMBI_PCS2021.pdf
│ ├── presentations
│ │ ├── VMAF_ICIP17.pdf
│ │ ├── VQEG_SAM_2018_023_VMAF_Variability.pdf
│ │ ├── VQEG_SAM_2018_025_VMAF_4K.pdf
│ │ └── VQEG_SAM_2018_111_AnalysisToolsInVMAF.pdf
│ ├── python.md
│ ├── references.md
│ ├── release.md
│ └── windows.md
├── example
│ ├── example_batch_input
│ ├── example_dataset.py
│ ├── example_raw_dataset.py
│ └── externals.py
├── feature_param
│ ├── ssim.py
│ ├── vmaf_feature_v1.py
│ ├── vmaf_feature_v2.py
│ ├── vmaf_feature_v3.py
│ └── vmaf_feature_v6.py
├── images
│ ├── CI.png
│ ├── phone_model.png
│ ├── scatter_testing.png
│ ├── scatter_training.png
│ ├── subsample.png
│ ├── uml.png
│ └── vmaf_logo.jpg
├── model_param
│ ├── 5PL_v1.py
│ ├── libsvmnusvr_v1.py
│ ├── libsvmnusvr_v2.py
│ ├── libsvmnusvr_v3.py
│ └── randomforest_v1.py
└── param
│ ├── vmaf_v1.py
│ ├── vmaf_v2.py
│ ├── vmaf_v3.py
│ ├── vmaf_v4.py
│ ├── vmaf_v6.py
│ ├── vmaf_v6_bootstrap.py
│ ├── vmaf_v6_residue_bootstrap.py
│ ├── vmaf_v7.2_bootstrap.py
│ ├── vmaf_v7_bootstrap.py
│ ├── vmaf_v8.py
│ └── vmaf_v8_bootstrap.py
├── unittest
└── workspace
├── checkpoints_dir
└── .gitignore
├── dataset
└── .gitignore
├── encode
└── .gitignore
├── model
└── .gitignore
├── model_param
└── .gitignore
├── output
└── .gitignore
├── result_store_dir
└── .gitignore
└── workdir
└── .gitignore
/.dockerignore:
--------------------------------------------------------------------------------
1 | matlab
2 | workspace
3 | python/.tox
4 | .git
5 | .venv
6 | *.mp4
7 | *.yuv
8 | *.mov
9 |
--------------------------------------------------------------------------------
/.gitattributes:
--------------------------------------------------------------------------------
1 | # Set the default behavior, in case people don't have core.autocrlf set.
2 | * text=auto
3 |
4 | # The model file parser requires LF line endings
5 | *.pkl text eol=lf
6 | *.model text eol=lf
7 |
--------------------------------------------------------------------------------
/.github/dependabot.yml:
--------------------------------------------------------------------------------
1 | version: 2
2 | updates:
3 | # Maintain dependencies for GitHub Actions
4 | - package-ecosystem: "github-actions"
5 | directory: "/"
6 | schedule:
7 | interval: "weekly"
8 |
--------------------------------------------------------------------------------
/.github/workflows/docker.yml:
--------------------------------------------------------------------------------
1 | name: Docker
2 | on:
3 | push:
4 | pull_request:
5 |
6 | jobs:
7 | docker:
8 | runs-on: ubuntu-latest
9 | steps:
10 | - uses: actions/checkout@v4
11 | - name: Build Docker Image
12 | run: |
13 | docker build -t vmaf .
14 |
--------------------------------------------------------------------------------
/.gitignore:
--------------------------------------------------------------------------------
1 | # Caches, build artifacts
2 | .DS_Store
3 | .cache/
4 | *.egg*
5 | .gradle/
6 | .idea/
7 | *.py[cod]
8 | .pypirc
9 | .tox/
10 | .*version
11 | .venv*/
12 | __pycache__/
13 | build/
14 | dist/
15 | vmaf_output.xml
16 | compile_commands.json
17 |
--------------------------------------------------------------------------------
/Dockerfile:
--------------------------------------------------------------------------------
1 | FROM ubuntu:22.04
2 |
3 | # get and install building tools
4 | RUN apt-get update && \
5 | apt-get install -y \
6 | build-essential \
7 | ninja-build \
8 | nasm \
9 | doxygen \
10 | python3 \
11 | python3-pip \
12 | python3-venv \
13 | xxd
14 |
15 | # retrieve source code
16 | COPY . /vmaf
17 |
18 | # setup environment
19 | ENV PATH=/vmaf:/vmaf/libvmaf/build/tools:$PATH
20 |
21 | # make vmaf
22 | RUN cd /vmaf && make clean && make
23 |
24 | # install python tools
25 | RUN pip3 install --no-cache-dir -r /vmaf/python/requirements.txt
26 |
27 | WORKDIR /vmaf
28 |
29 | ENV PYTHONPATH=python
30 |
31 | ENTRYPOINT [ "vmaf" ]
32 |
--------------------------------------------------------------------------------
/OSSMETADATA:
--------------------------------------------------------------------------------
1 | osslifecycle=active
--------------------------------------------------------------------------------
/libvmaf/doc/Doxyfile.in:
--------------------------------------------------------------------------------
1 | PROJECT_NAME = libvmaf
2 | OUTPUT_DIRECTORY = @DOXYGEN_OUTPUT@
3 | STRIP_FROM_PATH = @DOXYGEN_STRIP@
4 | OUTPUT_LANGUAGE = English
5 | TAB_SIZE = 4
6 | EXTRACT_ALL = YES
7 | OPTIMIZE_OUTPUT_FOR_C = YES
8 | DOXYFILE_ENCODING = UTF-8
9 | TYPEDEF_HIDES_STRUCT = YES
10 |
11 | QUIET = YES
12 | WARNINGS = YES
13 | WARN_IF_UNDOCUMENTED = YES
14 |
15 | INPUT = @DOXYGEN_INPUT@
16 | FILE_PATTERNS = *.h
17 |
18 | GENERATE_HTML = YES
19 | GENERATE_LATEX = NO
20 |
--------------------------------------------------------------------------------
/libvmaf/doc/meson.build:
--------------------------------------------------------------------------------
1 | if not get_option('enable_docs')
2 | subdir_done()
3 | endif
4 |
5 | doxygen = find_program('doxygen', required: false)
6 |
7 | if doxygen.found()
8 | conf_data = configuration_data()
9 | doxygen_input = [join_paths(meson.project_source_root(), 'include/libvmaf'),
10 | join_paths(meson.project_source_root(), 'src/feature'),
11 | ]
12 |
13 | conf_data.set('DOXYGEN_INPUT', ' '.join(doxygen_input))
14 | conf_data.set('DOXYGEN_STRIP', join_paths(meson.project_source_root(), 'include'))
15 | conf_data.set('DOXYGEN_OUTPUT', meson.current_build_dir())
16 | doxyfile = configure_file(input: 'Doxyfile.in',
17 | output: 'Doxyfile',
18 | configuration: conf_data)
19 |
20 | custom_target('doc',
21 | build_by_default: false,
22 | command: [doxygen, doxyfile],
23 | output: ['html']
24 | )
25 | endif
26 |
--------------------------------------------------------------------------------
/libvmaf/include/libvmaf/feature.h:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2020 Netflix, Inc.
4 | *
5 | * Licensed under the BSD+Patent License (the "License");
6 | * you may not use this file except in compliance with the License.
7 | * You may obtain a copy of the License at
8 | *
9 | * https://opensource.org/licenses/BSDplusPatent
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
18 |
19 | #ifndef __VMAF_FEATURE_H__
20 | #define __VMAF_FEATURE_H__
21 |
22 | #ifdef __cplusplus
23 | extern "C" {
24 | #endif
25 |
26 | typedef struct VmafFeatureDictionary VmafFeatureDictionary;
27 |
28 | int vmaf_feature_dictionary_set(VmafFeatureDictionary **dict, const char *key,
29 | const char *val);
30 |
31 | int vmaf_feature_dictionary_free(VmafFeatureDictionary **dict);
32 |
33 | #ifdef __cplusplus
34 | }
35 | #endif
36 |
37 | #endif /* __VMAF_FEATURE_H__ */
38 |
--------------------------------------------------------------------------------
/libvmaf/include/libvmaf/meson.build:
--------------------------------------------------------------------------------
1 | # installed version.h header generation
2 | version_h_data = configuration_data()
3 | version_h_data.set('VMAF_API_VERSION_MAJOR', vmaf_api_version_major)
4 | version_h_data.set('VMAF_API_VERSION_MINOR', vmaf_api_version_minor)
5 | version_h_data.set('VMAF_API_VERSION_PATCH', vmaf_api_version_revision)
6 | version_h_target = configure_file(input: 'version.h.in',
7 | output: 'version.h',
8 | configuration: version_h_data)
9 |
10 | is_cuda_enabled = get_option('enable_cuda') == true
11 |
12 | platform_specific_headers = []
13 |
14 | if is_cuda_enabled
15 | platform_specific_headers += 'libvmaf_cuda.h'
16 | endif
17 |
18 | # install headers
19 | install_headers(['libvmaf.h',
20 | 'feature.h',
21 | 'model.h',
22 | 'picture.h'],
23 | version_h_target,
24 | platform_specific_headers,
25 | subdir : 'libvmaf')
26 |
--------------------------------------------------------------------------------
/libvmaf/include/libvmaf/version.h.in:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2020 Netflix, Inc.
4 | *
5 | * Licensed under the BSD+Patent License (the "License");
6 | * you may not use this file except in compliance with the License.
7 | * You may obtain a copy of the License at
8 | *
9 | * https://opensource.org/licenses/BSDplusPatent
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
18 |
19 | #ifndef VMAF_VERSION_H
20 | #define VMAF_VERSION_H
21 |
22 | #define VMAF_API_VERSION_MAJOR @VMAF_API_VERSION_MAJOR@
23 | #define VMAF_API_VERSION_MINOR @VMAF_API_VERSION_MINOR@
24 | #define VMAF_API_VERSION_PATCH @VMAF_API_VERSION_PATCH@
25 |
26 | #endif /* VMAF_VERSION_H */
27 |
--------------------------------------------------------------------------------
/libvmaf/include/meson.build:
--------------------------------------------------------------------------------
1 | # Revision file (vcs_version.h) generation
2 | vmaf_git_dir = join_paths(libvmaf_src_root + '/../', '.git')
3 | rev_target = vcs_tag(command: [
4 | 'git', '--git-dir', vmaf_git_dir,
5 | 'describe', '--tags', '--long',
6 | '--match', '?.*.*', '--always'
7 | ],
8 | input: 'vcs_version.h.in',
9 | output: 'vcs_version.h'
10 | )
11 |
12 | subdir('libvmaf')
13 |
--------------------------------------------------------------------------------
/libvmaf/include/vcs_version.h.in:
--------------------------------------------------------------------------------
1 | /* auto-generated, do not edit */
2 | #define VMAF_VERSION "@VCS_TAG@"
3 |
--------------------------------------------------------------------------------
/libvmaf/meson_options.txt:
--------------------------------------------------------------------------------
1 | option('enable_tests',
2 | type: 'boolean',
3 | value: true,
4 | description: 'Build libvmaf tests')
5 |
6 | option('enable_docs',
7 | type: 'boolean',
8 | value: true,
9 | description: 'Build libvmaf documentation')
10 |
11 | option('enable_asm',
12 | type: 'boolean',
13 | value: true,
14 | description: 'Build asm files, if available')
15 |
16 | option('enable_avx512',
17 | type: 'boolean',
18 | value: true,
19 | description: 'Build AVX-512 asm files, requires nasm 2.14')
20 |
21 | option('built_in_models',
22 | type: 'boolean',
23 | value: true,
24 | description: 'Compile default vmaf models into the library')
25 |
26 | option('enable_float',
27 | type: 'boolean',
28 | value: false,
29 | description: 'Compile floating-point feature extractors into the library')
30 |
31 | option('enable_cuda',
32 | type: 'boolean',
33 | value: false,
34 | description: 'Enable CUDA support')
35 |
36 | option('enable_nvtx',
37 | type: 'boolean',
38 | value: false,
39 | description: 'Enable NVTX range support')
40 |
--------------------------------------------------------------------------------
/libvmaf/src/arm/cpu.c:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2022 Netflix, Inc.
4 | *
5 | * Licensed under the BSD+Patent License (the "License");
6 | * you may not use this file except in compliance with the License.
7 | * You may obtain a copy of the License at
8 | *
9 | * https://opensource.org/licenses/BSDplusPatent
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
18 |
19 | #include "config.h"
20 |
21 | #include "arm/cpu.h"
22 |
23 | unsigned vmaf_get_cpu_flags_arm(void) {
24 | unsigned flags = 0;
25 |
26 | #ifdef ARCH_AARCH64
27 | flags |= VMAF_ARM_CPU_FLAG_NEON;
28 | #endif
29 |
30 | return flags;
31 | }
32 |
--------------------------------------------------------------------------------
/libvmaf/src/arm/cpu.h:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2022 Netflix, Inc.
4 | *
5 | * Licensed under the BSD+Patent License (the "License");
6 | * you may not use this file except in compliance with the License.
7 | * You may obtain a copy of the License at
8 | *
9 | * https://opensource.org/licenses/BSDplusPatent
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
18 |
19 | #ifndef __VMAF_SRC_ARM_CPU_H__
20 | #define __VMAF_SRC_ARM_CPU_H__
21 |
22 | enum CpuFlags {
23 | VMAF_ARM_CPU_FLAG_NEON = 1 << 0,
24 | };
25 |
26 | unsigned vmaf_get_cpu_flags_arm(void);
27 |
28 | #endif /* __VMAF_SRC_ARM_CPU_H__ */
29 |
--------------------------------------------------------------------------------
/libvmaf/src/cpu.c:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2020 Netflix, Inc.
4 | *
5 | * Licensed under the BSD+Patent License (the "License");
6 | * you may not use this file except in compliance with the License.
7 | * You may obtain a copy of the License at
8 | *
9 | * https://opensource.org/licenses/BSDplusPatent
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
18 |
19 | #include "config.h"
20 | #include "cpu.h"
21 |
22 | static unsigned flags = 0;
23 | static unsigned flags_mask = -1;
24 |
25 | void vmaf_init_cpu(void)
26 | {
27 | #if ARCH_X86
28 | flags = vmaf_get_cpu_flags_x86();
29 | #elif ARCH_AARCH64
30 | flags = vmaf_get_cpu_flags_arm();
31 | #endif
32 | }
33 |
34 | void vmaf_set_cpu_flags_mask(const unsigned mask)
35 | {
36 | flags_mask = mask;
37 | }
38 |
39 | unsigned vmaf_get_cpu_flags(void)
40 | {
41 | return flags & flags_mask;
42 | }
43 |
--------------------------------------------------------------------------------
/libvmaf/src/cpu.h:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2020 Netflix, Inc.
4 | *
5 | * Licensed under the BSD+Patent License (the "License");
6 | * you may not use this file except in compliance with the License.
7 | * You may obtain a copy of the License at
8 | *
9 | * https://opensource.org/licenses/BSDplusPatent
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
18 |
19 | #ifndef __VMAF_SRC_CPU_H__
20 | #define __VMAF_SRC_CPU_H__
21 |
22 | #ifdef __cplusplus
23 | extern "C" {
24 | #endif
25 |
26 | #include "config.h"
27 |
28 | #if ARCH_X86
29 | #include "x86/cpu.h"
30 | #elif ARCH_AARCH64
31 | #include "arm/cpu.h"
32 | #endif
33 |
34 | void vmaf_init_cpu(void);
35 | void vmaf_set_cpu_flags_mask(const unsigned mask);
36 | unsigned vmaf_get_cpu_flags(void);
37 |
38 | #ifdef __cplusplus
39 | }
40 | #endif
41 |
42 | #endif /* __VMAF_SRC_CPU_H__ */
43 |
--------------------------------------------------------------------------------
/libvmaf/src/feature/adm.h:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2020 Netflix, Inc.
4 | *
5 | * Licensed under the BSD+Patent License (the "License");
6 | * you may not use this file except in compliance with the License.
7 | * You may obtain a copy of the License at
8 | *
9 | * https://opensource.org/licenses/BSDplusPatent
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
18 |
19 | int compute_adm(const float *ref, const float *dis, int w, int h,
20 | int ref_stride, int dis_stride, double *score,
21 | double *score_num, double *score_den, double *scores,
22 | double border_factor, double adm_enhn_gain_limit,
23 | double adm_norm_view_dist, int adm_ref_display_height,
24 | int adm_csf_mode);
25 |
--------------------------------------------------------------------------------
/libvmaf/src/feature/alias.h:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2020 Netflix, Inc.
4 | *
5 | * Licensed under the BSD+Patent License (the "License");
6 | * you may not use this file except in compliance with the License.
7 | * You may obtain a copy of the License at
8 | *
9 | * https://opensource.org/licenses/BSDplusPatent
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
18 |
19 | const char *vmaf_feature_name_alias(const char *feature_name);
20 |
--------------------------------------------------------------------------------
/libvmaf/src/feature/ansnr.h:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2020 Netflix, Inc.
4 | *
5 | * Licensed under the BSD+Patent License (the "License");
6 | * you may not use this file except in compliance with the License.
7 | * You may obtain a copy of the License at
8 | *
9 | * https://opensource.org/licenses/BSDplusPatent
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
18 |
19 | int compute_ansnr(const float *ref, const float *dis, int w, int h,
20 | int ref_stride, int dis_stride,
21 | double *score, double *score_psnr, double peak, double psnr_max);
22 |
--------------------------------------------------------------------------------
/libvmaf/src/feature/ansnr_options.h:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2020 Netflix, Inc.
4 | *
5 | * Licensed under the BSD+Patent License (the "License");
6 | * you may not use this file except in compliance with the License.
7 | * You may obtain a copy of the License at
8 | *
9 | * https://opensource.org/licenses/BSDplusPatent
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
18 |
19 | #pragma once
20 |
21 | #ifndef ANSNR_OPTIONS_H_
22 | #define ANSNR_OPTIONS_H_
23 |
24 | /* Whether to use border replication instead of zero extension. */
25 | /* #define ANSNR_OPT_BORDER_REPLICATE */
26 |
27 | /* Whether to save intermediate results to files. */
28 | /* #define ANSNR_OPT_DEBUG_DUMP */
29 |
30 | /* Whether to use a 1-D approximation of filters. */
31 | /* #define ANSNR_OPT_FILTER_1D */
32 |
33 | /* Whether to normalize result by dividing against maximum ANSNR. */
34 | /* #define ANSNR_OPT_NORMALIZE */
35 |
36 | #endif /* ANSNR_OPTIONS_H_ */
37 |
--------------------------------------------------------------------------------
/libvmaf/src/feature/arm64/adm_neon.h:
--------------------------------------------------------------------------------
1 |
2 | #ifndef ARM_64_ADM_H_
3 | #define ARM_64_ADM_H_
4 |
5 | #include "feature/integer_adm.h"
6 |
7 | void adm_dwt2_8_neon(const uint8_t *src, const adm_dwt_band_t *dst,
8 | AdmBuffer *buf, int w, int h, int src_stride,
9 | int dst_stride);
10 |
11 | #endif /* ARM64_ADM_H_ */
12 |
--------------------------------------------------------------------------------
/libvmaf/src/feature/arm64/vif_neon.h:
--------------------------------------------------------------------------------
1 |
2 | #ifndef ARM64_VIF_H_
3 | #define ARM64_VIF_H_
4 |
5 | #include "feature/integer_vif.h"
6 |
7 | void vif_subsample_rd_8_neon(VifBuffer buf, unsigned w, unsigned h);
8 |
9 | void vif_subsample_rd_16_neon(VifBuffer buf, unsigned w, unsigned h, int scale,
10 | int bpc);
11 |
12 | void vif_statistic_8_neon(struct VifPublicState *s, float *num, float *den, unsigned w, unsigned h);
13 |
14 | void vif_statistic_16_neon(struct VifPublicState *s, float *num, float *den, unsigned w, unsigned h, int bpc, int scale);
15 |
16 | #endif /* ARM64_VIF_H_ */
17 |
--------------------------------------------------------------------------------
/libvmaf/src/feature/common/alignment.c:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2020 Netflix, Inc.
4 | *
5 | * Licensed under the BSD+Patent License (the "License");
6 | * you may not use this file except in compliance with the License.
7 | * You may obtain a copy of the License at
8 | *
9 | * https://opensource.org/licenses/BSDplusPatent
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
18 |
19 | #include "alignment.h"
20 |
21 | int vmaf_floorn(int n, int m)
22 | {
23 | return n - n % m;
24 | }
25 |
26 | int vmaf_ceiln(int n, int m)
27 | {
28 | return n % m ? n + (m - n % m) : n;
29 | }
30 |
--------------------------------------------------------------------------------
/libvmaf/src/feature/common/alignment.h:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2020 Netflix, Inc.
4 | *
5 | * Licensed under the BSD+Patent License (the "License");
6 | * you may not use this file except in compliance with the License.
7 | * You may obtain a copy of the License at
8 | *
9 | * https://opensource.org/licenses/BSDplusPatent
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
18 |
19 | #ifndef ALIGNMENT_H_
20 | #define ALIGNMENT_H_
21 |
22 | /* Required for AVX. */
23 | #define VMAF_ALIGNMENT 32
24 |
25 | int vmaf_floorn(int n, int m);
26 | int vmaf_ceiln(int n, int m);
27 |
28 | #endif // ALIGNMENT_H_
29 |
--------------------------------------------------------------------------------
/libvmaf/src/feature/common/blur_array.h:
--------------------------------------------------------------------------------
1 | /*
2 | * blur_array.h
3 | *
4 | * Created on: 12.02.2018
5 | * Author: thomas
6 | */
7 |
8 | #ifndef VMAF_FEATURE_SRC_BLUR_ARRAY_H_
9 | #define VMAF_FEATURE_SRC_BLUR_ARRAY_H_
10 |
11 | #include <stdlib.h>
12 | #include <pthread.h>
13 | #include "mem.h"
14 |
15 | #define MAX_NUM_THREADS 128
16 | typedef struct
17 | {
18 | int frame_idx;
19 | float *blur_buf;
20 | int reference_count;
21 |
22 |
23 | } BLUR_BUF_STRUCT;
24 |
25 | typedef struct
26 | {
27 | BLUR_BUF_STRUCT blur_buf_array[MAX_NUM_THREADS];
28 | int actual_length;
29 | size_t buffer_size;
30 | pthread_mutex_t block;
31 |
32 | } BLUR_BUF_ARRAY;
33 |
34 | int init_blur_array(BLUR_BUF_ARRAY* arr, int array_length, size_t size, size_t alignement);
35 |
36 | float* get_free_blur_buf_slot(BLUR_BUF_ARRAY* arr, int frame_idx);
37 |
38 | int get_blur_buf_reference_count(BLUR_BUF_ARRAY* arr, int frame_idx);
39 |
40 | int release_blur_buf_slot(BLUR_BUF_ARRAY* arr, int search_frame_idx);
41 |
42 | int release_blur_buf_reference(BLUR_BUF_ARRAY* arr, int search_frame_idx);
43 |
44 | float* get_blur_buf(BLUR_BUF_ARRAY* arr, int search_frame_idx);
45 |
46 | int put_blur_buf(BLUR_BUF_ARRAY* arr, int frame_idx, float* blur_buf);
47 |
48 | void free_blur_buf(BLUR_BUF_ARRAY* arr);
49 |
50 | #endif /* VMAF_FEATURE_SRC_BLUR_ARRAY_H_ */
51 |
--------------------------------------------------------------------------------
/libvmaf/src/feature/common/macros.h:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2020 Netflix, Inc.
4 | *
5 | * Licensed under the BSD+Patent License (the "License");
6 | * you may not use this file except in compliance with the License.
7 | * You may obtain a copy of the License at
8 | *
9 | * https://opensource.org/licenses/BSDplusPatent
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
18 |
19 | #ifndef MACROS_H_
20 | #define MACROS_H_
21 |
22 | #if defined(_MSC_VER)
23 | #define FORCE_INLINE __forceinline
24 | #define UNUSED_FUNCTION /**/
25 | #else
26 | #define FORCE_INLINE __attribute__((always_inline)) inline
27 | #define UNUSED_FUNCTION __attribute__((unused))
28 | #endif
29 | #define RESTRICT __restrict
30 |
31 | #endif // MACROS_H_
32 |
--------------------------------------------------------------------------------
/libvmaf/src/feature/cuda/integer_motion_cuda.h:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2023 Netflix, Inc.
4 | * Copyright 2021 NVIDIA Corporation.
5 | *
6 | * Licensed under the BSD+Patent License (the "License");
7 | * you may not use this file except in compliance with the License.
8 | * You may obtain a copy of the License at
9 | *
10 | * https://opensource.org/licenses/BSDplusPatent
11 | *
12 | * Unless required by applicable law or agreed to in writing, software
13 | * distributed under the License is distributed on an "AS IS" BASIS,
14 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
15 | * See the License for the specific language governing permissions and
16 | * limitations under the License.
17 | *
18 | */
19 |
20 | #ifndef FEATURE_MOTION_CUDA_H_
21 | #define FEATURE_MOTION_CUDA_H_
22 |
23 | #include <stdint.h>
24 | #include "integer_motion.h"
25 | #include "common.h"
26 |
27 | extern const unsigned char motion_score_ptx[];
28 | #endif /* _FEATURE_MOTION_CUDA_H_ */
29 |
--------------------------------------------------------------------------------
/libvmaf/src/feature/feature_name.h:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2020 Netflix, Inc.
4 | *
5 | * Licensed under the BSD+Patent License (the "License");
6 | * you may not use this file except in compliance with the License.
7 | * You may obtain a copy of the License at
8 | *
9 | * https://opensource.org/licenses/BSDplusPatent
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
18 |
19 | #ifndef __VMAF_FEATURE_NAME_H__
20 | #define __VMAF_FEATURE_NAME_H__
21 |
22 | #include "dict.h"
23 | #include "opt.h"
24 |
25 | char *vmaf_feature_name_from_options(const char *name, const VmafOption *opts,
26 | void *obj);
27 |
28 | VmafDictionary *
29 | vmaf_feature_name_dict_from_provided_features(const char **provided_features,
30 | const VmafOption *opts, void *obj);
31 |
32 | #endif /* __VMAF_FEATURE_NAME_H__ */
33 |
--------------------------------------------------------------------------------
/libvmaf/src/feature/iqa/iqa_options.h:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2020 Netflix, Inc.
4 | *
5 | * Licensed under the BSD+Patent License (the "License");
6 | * you may not use this file except in compliance with the License.
7 | * You may obtain a copy of the License at
8 | *
9 | * https://opensource.org/licenses/BSDplusPatent
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
18 |
19 | #pragma once
20 |
21 | #ifndef IQA_OPTIONS_H_
22 | #define IQA_OPTIONS_H_
23 |
24 | /* Whether to use 1D separable convolution */
25 | #define IQA_CONVOLVE_1D
26 |
27 | #endif /* IQA_OPTIONS_H_ */
28 |
--------------------------------------------------------------------------------
/libvmaf/src/feature/mkdirp.h:
--------------------------------------------------------------------------------
1 |
2 | //
3 | // mkdirp.h
4 | //
5 | // Copyright (c) 2013 Stephen Mathieson
6 | // MIT licensed
7 | //
8 |
9 | #ifndef MKDIRP
10 | #define MKDIRP
11 |
12 | #include <sys/types.h>
13 | #include <sys/stat.h>
14 |
15 | /*
16 | * Recursively `mkdir(path, mode)`
17 | */
18 |
19 | int mkdirp(const char *, mode_t );
20 |
21 | #endif
22 |
--------------------------------------------------------------------------------
/libvmaf/src/feature/moment.h:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2020 Netflix, Inc.
4 | *
5 | * Licensed under the BSD+Patent License (the "License");
6 | * you may not use this file except in compliance with the License.
7 | * You may obtain a copy of the License at
8 | *
9 | * https://opensource.org/licenses/BSDplusPatent
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
18 |
19 | int compute_1st_moment(const float *pic, int w, int h, int stride, double *score);
20 | int compute_2nd_moment(const float *pic, int w, int h, int stride, double *score);
21 |
--------------------------------------------------------------------------------
/libvmaf/src/feature/moment_options.h:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2020 Netflix, Inc.
4 | *
5 | * Licensed under the BSD+Patent License (the "License");
6 | * you may not use this file except in compliance with the License.
7 | * You may obtain a copy of the License at
8 | *
9 | * https://opensource.org/licenses/BSDplusPatent
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
18 |
19 | #pragma once
20 |
21 | #ifndef MOMENT_OPTIONS_H_
22 | #define MOMENT_OPTIONS_H_
23 |
24 | #endif /* MOMENT_OPTIONS_H_ */
25 |
--------------------------------------------------------------------------------
/libvmaf/src/feature/motion.h:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2020 Netflix, Inc.
4 | *
5 | * Licensed under the BSD+Patent License (the "License");
6 | * you may not use this file except in compliance with the License.
7 | * You may obtain a copy of the License at
8 | *
9 | * https://opensource.org/licenses/BSDplusPatent
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
18 |
19 | int compute_motion(const float *ref, const float *dis, int w, int h, int ref_stride, int dis_stride, double *score);
20 |
--------------------------------------------------------------------------------
/libvmaf/src/feature/motion_options.h:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2020 Netflix, Inc.
4 | *
5 | * Licensed under the BSD+Patent License (the "License");
6 | * you may not use this file except in compliance with the License.
7 | * You may obtain a copy of the License at
8 | *
9 | * https://opensource.org/licenses/BSDplusPatent
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
18 |
19 | #pragma once
20 |
21 | #ifndef MOTION_OPTIONS_H_
22 | #define MOTION_OPTIONS_H_
23 |
24 | #endif /* MOTION_OPTIONS_H_ */
25 |
--------------------------------------------------------------------------------
/libvmaf/src/feature/motion_tools.h:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2020 Netflix, Inc.
4 | *
5 | * Licensed under the BSD+Patent License (the "License");
6 | * you may not use this file except in compliance with the License.
7 | * You may obtain a copy of the License at
8 | *
9 | * https://opensource.org/licenses/BSDplusPatent
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
18 |
19 | #pragma once
20 |
21 | #ifndef MOTION_TOOLS_H_
22 | #define MOTION_TOOLS_H_
23 |
24 | static const float FILTER_5_s[5] = {
25 | 0.054488685,
26 | 0.244201342,
27 | 0.402619947,
28 | 0.244201342,
29 | 0.054488685};
30 |
31 | #endif /* MOTION_TOOLS_H_ */
32 |
--------------------------------------------------------------------------------
/libvmaf/src/feature/ms_ssim.h:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2020 Netflix, Inc.
4 | *
5 | * Licensed under the BSD+Patent License (the "License");
6 | * you may not use this file except in compliance with the License.
7 | * You may obtain a copy of the License at
8 | *
9 | * https://opensource.org/licenses/BSDplusPatent
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
18 |
19 | int compute_ms_ssim(const float *ref, const float *cmp, int w, int h,
20 | int ref_stride, int cmp_stride, double *score,
21 | double* l_scores, double* c_scores, double* s_scores);
22 |
--------------------------------------------------------------------------------
/libvmaf/src/feature/offset.c:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2020 Netflix, Inc.
4 | *
5 | * Licensed under the BSD+Patent License (the "License");
6 | * you may not use this file except in compliance with the License.
7 | * You may obtain a copy of the License at
8 | *
9 | * https://opensource.org/licenses/BSDplusPatent
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
18 |
19 | /**
20 | * Note: stride is in terms of bytes
21 | */
22 | int offset_image_s(float *buf, float off, int width, int height, int stride)
23 | {
24 | char *byte_ptr = (char *)buf;
25 | int ret = 1;
26 | int i, j;
27 |
28 | for (i = 0; i < height; ++i)
29 | {
30 | float *row_ptr = (float *)byte_ptr;
31 |
32 | for (j = 0; j < width; ++j)
33 | {
34 | row_ptr[j] += off;
35 | }
36 |
37 | byte_ptr += stride;
38 | }
39 |
40 | ret = 0;
41 |
42 | return ret;
43 | }
44 |
--------------------------------------------------------------------------------
/libvmaf/src/feature/offset.h:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2020 Netflix, Inc.
4 | *
5 | * Licensed under the BSD+Patent License (the "License");
6 | * you may not use this file except in compliance with the License.
7 | * You may obtain a copy of the License at
8 | *
9 | * https://opensource.org/licenses/BSDplusPatent
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
18 |
19 | #ifndef OFFSET_H_
20 | #define OFFSET_H_
21 |
22 | /* Whether to use [0,255] or [-128,127] input pixel range. */
23 | //#define OPT_RANGE_PIXEL_OFFSET 0
24 | #define OPT_RANGE_PIXEL_OFFSET (-128)
25 |
26 | int offset_image_s(float *buf, float off, int width, int height, int stride);
27 |
28 | #endif /* OFFSET_H_ */
29 |
--------------------------------------------------------------------------------
/libvmaf/src/feature/picture_copy.h:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2020 Netflix, Inc.
4 | *
5 | * Licensed under the BSD+Patent License (the "License");
6 | * you may not use this file except in compliance with the License.
7 | * You may obtain a copy of the License at
8 | *
9 | * https://opensource.org/licenses/BSDplusPatent
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
18 | #include <stddef.h>
19 |
20 | void picture_copy(float *dst, ptrdiff_t dst_stride, VmafPicture *src,
21 | int offset, unsigned bpc);
22 |
--------------------------------------------------------------------------------
/libvmaf/src/feature/psnr.h:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2020 Netflix, Inc.
4 | *
5 | * Licensed under the BSD+Patent License (the "License");
6 | * you may not use this file except in compliance with the License.
7 | * You may obtain a copy of the License at
8 | *
9 | * https://opensource.org/licenses/BSDplusPatent
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
18 |
19 | int compute_psnr(const float *ref, const float *dis, int w, int h,
20 | int ref_stride, int dis_stride,
21 | double *score, double peak, double psnr_max);
22 |
--------------------------------------------------------------------------------
/libvmaf/src/feature/psnr_options.h:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2020 Netflix, Inc.
4 | *
5 | * Licensed under the BSD+Patent License (the "License");
6 | * you may not use this file except in compliance with the License.
7 | * You may obtain a copy of the License at
8 | *
9 | * https://opensource.org/licenses/BSDplusPatent
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
18 |
19 | #pragma once
20 |
21 | #ifndef PSNR_OPTIONS_H_
22 | #define PSNR_OPTIONS_H_
23 |
24 | #endif /* PSNR_OPTIONS_H_ */
25 |
--------------------------------------------------------------------------------
/libvmaf/src/feature/psnr_tools.h:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2020 Netflix, Inc.
4 | *
5 | * Licensed under the BSD+Patent License (the "License");
6 | * you may not use this file except in compliance with the License.
7 | * You may obtain a copy of the License at
8 | *
9 | * https://opensource.org/licenses/BSDplusPatent
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
18 |
19 | #ifndef PSNR_TOOLS_H_
20 | #define PSNR_TOOLS_H_
21 |
22 | int psnr_constants(const char *fmt, double *peak, double *psnr_max);
23 |
24 | #endif /* PSNR_TOOLS_H_ */
--------------------------------------------------------------------------------
/libvmaf/src/feature/ssim.h:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2020 Netflix, Inc.
4 | *
5 | * Licensed under the BSD+Patent License (the "License");
6 | * you may not use this file except in compliance with the License.
7 | * You may obtain a copy of the License at
8 | *
9 | * https://opensource.org/licenses/BSDplusPatent
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
18 |
19 | int compute_ssim(const float *ref, const float *cmp, int w, int h,
20 | int ref_stride, int cmp_stride, double *score,
21 | double *l_score, double *c_score, double *s_score);
22 |
--------------------------------------------------------------------------------
/libvmaf/src/feature/vif.h:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2020 Netflix, Inc.
4 | *
5 | * Licensed under the BSD+Patent License (the "License");
6 | * you may not use this file except in compliance with the License.
7 | * You may obtain a copy of the License at
8 | *
9 | * https://opensource.org/licenses/BSDplusPatent
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
18 |
19 | int compute_vif(const float *ref, const float *dis, int w, int h, int ref_stride, int dis_stride,
20 | double *score, double *score_num, double *score_den, double *scores,
21 | double vif_enhn_gain_limit, double vif_kernelscale);
22 |
--------------------------------------------------------------------------------
/libvmaf/src/feature/x86/adm_avx2.h:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2020 Netflix, Inc.
4 | *
5 | * Licensed under the BSD+Patent License (the "License");
6 | * you may not use this file except in compliance with the License.
7 | * You may obtain a copy of the License at
8 | *
9 | * https://opensource.org/licenses/BSDplusPatent
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
18 |
19 | #ifndef X86_AVX2_ADM_H_
20 | #define X86_AVX2_ADM_H_
21 |
22 | #include "feature/integer_adm.h"
23 |
24 | void adm_dwt2_8_avx2(const uint8_t *src, const adm_dwt_band_t *dst,
25 | AdmBuffer *buf, int w, int h, int src_stride,
26 | int dst_stride);
27 |
28 | #endif /* X86_AVX2_ADM_H_ */
29 |
--------------------------------------------------------------------------------
/libvmaf/src/feature/x86/cambi_avx2.h:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2020 Netflix, Inc.
4 | *
5 | * Licensed under the BSD+Patent License (the "License");
6 | * you may not use this file except in compliance with the License.
7 | * You may obtain a copy of the License at
8 | *
9 | * https://opensource.org/licenses/BSDplusPatent
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
18 |
19 | #ifndef X86_AVX2_CAMBI_H_
20 | #define X86_AVX2_CAMBI_H_
21 |
22 | #include <stddef.h>
23 | #include <stdint.h>
24 |
25 | void cambi_increment_range_avx2(uint16_t *arr, int left, int right);
26 |
27 | void cambi_decrement_range_avx2(uint16_t *arr, int left, int right);
28 |
29 | void get_derivative_data_for_row_avx2(const uint16_t *image_data, uint16_t *derivative_buffer, int width, int height, int row, int stride);
30 |
31 | #endif /* X86_AVX2_CAMBI_H_ */
32 |
--------------------------------------------------------------------------------
/libvmaf/src/feature/x86/motion_avx2.h:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2020 Netflix, Inc.
4 | *
5 | * Licensed under the BSD+Patent License (the "License");
6 | * you may not use this file except in compliance with the License.
7 | * You may obtain a copy of the License at
8 | *
9 | * https://opensource.org/licenses/BSDplusPatent
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
18 |
19 | #ifndef X86_AVX2_MOTION_H_
20 | #define X86_AVX2_MOTION_H_
21 |
22 | #include <stdint.h>
23 |
24 | void x_convolution_16_avx2(const uint16_t *src, uint16_t *dst, unsigned width,
25 | unsigned height, ptrdiff_t src_stride,
26 | ptrdiff_t dst_stride);
27 |
28 | #endif /* X86_AVX2_MOTION_H_ */
29 |
--------------------------------------------------------------------------------
/libvmaf/src/feature/x86/motion_avx512.h:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2020 Netflix, Inc.
4 | *
5 | * Licensed under the BSD+Patent License (the "License");
6 | * you may not use this file except in compliance with the License.
7 | * You may obtain a copy of the License at
8 | *
9 | * https://opensource.org/licenses/BSDplusPatent
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
18 |
19 | #ifndef X86_AVX512_MOTION_H_
20 | #define X86_AVX512_MOTION_H_
21 |
22 | #include <stdint.h>
23 |
24 | void x_convolution_16_avx512(const uint16_t *src, uint16_t *dst, unsigned width,
25 | unsigned height, ptrdiff_t src_stride,
26 | ptrdiff_t dst_stride);
27 |
28 | #endif /* X86_AVX512_MOTION_H_ */
29 |
--------------------------------------------------------------------------------
/libvmaf/src/feature/x86/vif_avx512.h:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2020 Netflix, Inc.
4 | *
5 | * Licensed under the BSD+Patent License (the "License");
6 | * you may not use this file except in compliance with the License.
7 | * You may obtain a copy of the License at
8 | *
9 | * https://opensource.org/licenses/BSDplusPatent
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
18 |
19 | #ifndef X86_AVX512_VIF_H_
20 | #define X86_AVX512_VIF_H_
21 |
22 | #include "feature/integer_vif.h"
23 |
24 | void vif_subsample_rd_8_avx512(VifBuffer buf, unsigned w, unsigned h);
25 |
26 | void vif_subsample_rd_16_avx512(VifBuffer buf, unsigned w, unsigned h, int scale,
27 | int bpc);
28 |
29 | void vif_statistic_8_avx512(struct VifPublicState *s, float *num, float *den, unsigned w, unsigned h);
30 |
31 | void vif_statistic_16_avx512(struct VifPublicState *s, float *num, float *den, unsigned w, unsigned h, int bpc, int scale);
32 |
33 | #endif /* X86_AVX512_VIF_H_ */
34 |
--------------------------------------------------------------------------------
/libvmaf/src/log.h:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2020 Netflix, Inc.
4 | *
5 | * Licensed under the BSD+Patent License (the "License");
6 | * you may not use this file except in compliance with the License.
7 | * You may obtain a copy of the License at
8 | *
9 | * https://opensource.org/licenses/BSDplusPatent
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
18 |
19 | #ifndef __VMAF_SRC_LOG_H__
20 | #define __VMAF_SRC_LOG_H__
21 |
22 | #include "libvmaf/libvmaf.h"
23 |
24 | void vmaf_set_log_level(enum VmafLogLevel log_level);
25 | void vmaf_log(enum VmafLogLevel log_level, const char *fmt, ...);
26 |
27 | #endif /* __VMAF_SRC_LOG_H__ */
28 |
--------------------------------------------------------------------------------
/libvmaf/src/mem.c:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2020 Netflix, Inc.
4 | *
5 | * Licensed under the BSD+Patent License (the "License");
6 | * you may not use this file except in compliance with the License.
7 | * You may obtain a copy of the License at
8 | *
9 | * https://opensource.org/licenses/BSDplusPatent
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
18 |
19 | #define _POSIX_C_SOURCE 200112L
20 |
21 | #include <stddef.h>
22 | #include <stdlib.h>
23 | #include "mem.h"
24 |
25 | void *aligned_malloc(size_t size, size_t alignment)
26 | {
27 | void *ptr;
28 |
29 | #if defined(_MSC_VER) || defined(__MINGW32__)
30 | if ((ptr = _aligned_malloc(size, alignment)) == NULL)
31 | #else
32 | if (posix_memalign(&ptr, alignment, size))
33 | #endif
34 | return 0;
35 | else
36 | return ptr;
37 | }
38 |
39 | void aligned_free(void *ptr)
40 | {
41 | #if defined(_MSC_VER) || defined(__MINGW32__)
42 | _aligned_free(ptr);
43 | #else
44 | free(ptr);
45 | #endif
46 | }
47 |
--------------------------------------------------------------------------------
/libvmaf/src/mem.h:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2020 Netflix, Inc.
4 | *
5 | * Licensed under the BSD+Patent License (the "License");
6 | * you may not use this file except in compliance with the License.
7 | * You may obtain a copy of the License at
8 | *
9 | * https://opensource.org/licenses/BSDplusPatent
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
18 |
19 | #ifndef __VMAF_MEM_H__
20 | #define __VMAF_MEM_H__
21 |
22 | #include <stddef.h>
23 |
24 | #define MAX_ALIGN 32
25 |
26 | #define ALIGN_FLOOR(x) ((x) - (x) % MAX_ALIGN)
27 | #define ALIGN_CEIL(x) ((x) + ((x) % MAX_ALIGN ? MAX_ALIGN - (x) % MAX_ALIGN : 0))
28 |
29 | void *aligned_malloc(size_t size, size_t alignment);
30 |
31 | void aligned_free(void *ptr);
32 |
33 | #endif /* __VMAF_MEM_H__ */
34 |
--------------------------------------------------------------------------------
/libvmaf/src/ref.h:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2020 Netflix, Inc.
4 | *
5 | * Licensed under the BSD+Patent License (the "License");
6 | * you may not use this file except in compliance with the License.
7 | * You may obtain a copy of the License at
8 | *
9 | * https://opensource.org/licenses/BSDplusPatent
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
18 |
19 | #ifndef __VMAF_SRC_REF_H__
20 | #define __VMAF_SRC_REF_H__
21 |
22 | #include <stdatomic.h>
23 |
24 | typedef struct VmafRef {
25 | atomic_int cnt;
26 | } VmafRef;
27 |
28 | int vmaf_ref_init(VmafRef **ref);
29 | void vmaf_ref_fetch_increment(VmafRef *ref);
30 | long vmaf_ref_fetch_decrement(VmafRef *ref);
31 | long vmaf_ref_load(VmafRef *ref);
32 | int vmaf_ref_close(VmafRef *ref);
33 |
34 | #endif /* __VMAF_SRC_REF_H__ */
35 |
--------------------------------------------------------------------------------
/libvmaf/src/thread_pool.h:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2020 Netflix, Inc.
4 | *
5 | * Licensed under the BSD+Patent License (the "License");
6 | * you may not use this file except in compliance with the License.
7 | * You may obtain a copy of the License at
8 | *
9 | * https://opensource.org/licenses/BSDplusPatent
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
18 |
19 | #ifndef __VMAF_THREAD_POOL_H__
20 | #define __VMAF_THREAD_POOL_H__
21 |
22 | #include <pthread.h>
23 |
24 | typedef struct VmafThreadPool VmafThreadPool;
25 |
26 | int vmaf_thread_pool_create(VmafThreadPool **tpool, unsigned n_threads);
27 |
28 | int vmaf_thread_pool_enqueue(VmafThreadPool *pool, void (*func)(void *data),
29 | void *data, size_t data_sz);
30 |
31 | int vmaf_thread_pool_wait(VmafThreadPool *pool);
32 |
33 | int vmaf_thread_pool_destroy(VmafThreadPool *tpool);
34 |
35 | #endif /* __VMAF_THREAD_POOL_H__ */
36 |
--------------------------------------------------------------------------------
/libvmaf/src/x86/cpu.h:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2020 Netflix, Inc.
4 | *
5 | * Licensed under the BSD+Patent License (the "License");
6 | * you may not use this file except in compliance with the License.
7 | * You may obtain a copy of the License at
8 | *
9 | * https://opensource.org/licenses/BSDplusPatent
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
18 |
19 | #ifndef __VMAF_SRC_X86_CPU_H__
20 | #define __VMAF_SRC_X86_CPU_H__
21 |
22 | enum VmafCpuFlags {
23 | VMAF_X86_CPU_FLAG_SSE2 = 1 << 0,
24 | VMAF_X86_CPU_FLAG_SSSE3 = 1 << 1,
25 | VMAF_X86_CPU_FLAG_SSE41 = 1 << 2,
26 | VMAF_X86_CPU_FLAG_AVX2 = 1 << 3,
27 | VMAF_X86_CPU_FLAG_AVX512 = 1 << 4,
28 | VMAF_X86_CPU_FLAG_AVX512ICL = 1 << 5,
29 | };
30 |
31 | unsigned vmaf_get_cpu_flags_x86(void);
32 |
33 | #endif /* __VMAF_SRC_X86_CPU_H__ */
34 |
--------------------------------------------------------------------------------
/libvmaf/test/test.c:
--------------------------------------------------------------------------------
1 | /**
2 | *
3 | * Copyright 2016-2020 Netflix, Inc.
4 | *
5 | * Licensed under the BSD+Patent License (the "License");
6 | * you may not use this file except in compliance with the License.
7 | * You may obtain a copy of the License at
8 | *
9 | * https://opensource.org/licenses/BSDplusPatent
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
18 |
19 | #include "test.h"
20 | #include <stdio.h>
21 |
22 | int mu_tests_run;
23 |
24 | int main(void)
25 | {
26 | char *msg = run_tests();
27 |
28 | if (msg)
29 | fprintf(stderr, "\033[31m, %s\n%d tests run, 1 failed\033[0m\n", msg, mu_tests_run);
30 | else
31 | fprintf(stderr, "\033[32m%d tests run, %d passed\033[0m\n", mu_tests_run, mu_tests_run);
32 |
33 | return msg != 0;
34 | }
35 |
--------------------------------------------------------------------------------
/libvmaf/tools/meson.build:
--------------------------------------------------------------------------------
1 | compat_cflags = []
2 | if cc.has_function('strsep')
3 | compat_cflags += '-DHAVE_STRSEP'
4 | endif
5 |
6 | vmaf = executable(
7 | 'vmaf',
8 | ['vmaf.c', 'cli_parse.c', 'y4m_input.c', 'vidinput.c', 'yuv_input.c'],
9 | include_directories : [libvmaf_inc, vmaf_include],
10 | dependencies: [stdatomic_dependency, cuda_dependency],
11 | c_args : [vmaf_cflags_common, compat_cflags],
12 | link_with : get_option('default_library') == 'both' ? libvmaf.get_static_lib() : libvmaf,
13 | install : true,
14 | )
15 |
16 | subdir('test')
17 |
--------------------------------------------------------------------------------
/libvmaf/tools/spinner.h:
--------------------------------------------------------------------------------
1 | const char *spinner[] = {
2 | "⢀⠀","⡀⠀","⠄⠀","⢂⠀","⡂⠀","⠅⠀","⢃⠀","⡃⠀","⠍⠀","⢋⠀","⡋⠀","⠍⠁","⢋⠁","⡋⠁","⠍⠉",
3 | "⠋⠉","⠋⠉","⠉⠙","⠉⠙","⠉⠩","⠈⢙","⠈⡙","⢈⠩","⡀⢙","⠄⡙","⢂⠩","⡂⢘","⠅⡘","⢃⠨","⡃⢐",
4 | "⠍⡐","⢋⠠","⡋⢀","⠍⡁","⢋⠁","⡋⠁","⠍⠉","⠋⠉","⠋⠉","⠉⠙","⠉⠙","⠉⠩","⠈⢙","⠈⡙","⠈⠩",
5 | "⠀⢙","⠀⡙","⠀⠩","⠀⢘","⠀⡘","⠀⠨","⠀⢐","⠀⡐","⠀⠠","⠀⢀","⠀⡀"
6 | };
7 |
8 | const unsigned spinner_length = sizeof(spinner) / sizeof(spinner[0]);
9 |
--------------------------------------------------------------------------------
/libvmaf/tools/test/meson.build:
--------------------------------------------------------------------------------
1 | if get_option('enable_cuda')
2 | test_vmaf_cuda_gpumask = find_program('test_vmaf_cuda_gpumask.sh')
3 | test('test_vmaf_cuda_gpumask', test_vmaf_cuda_gpumask)
4 | endif
5 |
--------------------------------------------------------------------------------
/libvmaf/tools/test/test_vmaf_cuda_gpumask.sh:
--------------------------------------------------------------------------------
1 | #!/bin/sh -x
2 | set -e
3 |
4 | # no gpumask: use cuda
5 | ./tools/vmaf \
6 | --reference /dev/zero \
7 | --distorted /dev/zero \
8 | --width 1920 --height 1080 --pixel_format 420 --bitdepth 8 \
9 | --frame_cnt 2 \
10 | --gpumask 0
11 |
12 | # gpumask: use cpu
13 | ./tools/vmaf \
14 | --reference /dev/zero \
15 | --distorted /dev/zero \
16 | --width 1920 --height 1080 --pixel_format 420 --bitdepth 8 \
17 | --frame_cnt 2 \
18 | --gpumask -1
19 |
20 | # no gpumask: use cuda for vmaf features, cpu for psnr
21 | ./tools/vmaf \
22 | --reference /dev/zero \
23 | --distorted /dev/zero \
24 | --width 1920 --height 1080 --pixel_format 420 --bitdepth 8 \
25 | --frame_cnt 2 \
26 | --gpumask 0 \
27 | --feature psnr \
28 | --output /dev/stdout
29 |
30 | # gpumask: use cpu for vmaf features and psnr
31 | ./tools/vmaf \
32 | --reference /dev/zero \
33 | --distorted /dev/zero \
34 | --width 1920 --height 1080 --pixel_format 420 --bitdepth 8 \
35 | --frame_cnt 2 \
36 | --gpumask -1 \
37 | --feature psnr
38 |
--------------------------------------------------------------------------------
/matlab/.gitignore:
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1 | *~
--------------------------------------------------------------------------------
/matlab/STMAD_2011_MatlabCode/Example.m:
--------------------------------------------------------------------------------
1 | clc;
2 | clear;
3 | close all;
4 |
5 | Hei = 324;
6 | Wid = 576;
7 | OrgFile = '../../python/test/resource/yuv/src01_hrc00_576x324.yuv';
8 | DstFile = '../../python/test/resource/yuv/src01_hrc01_576x324.yuv';
9 |
10 | run_stmad(OrgFile, DstFile, Wid, Hei);
11 |
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/matlab/STMAD_2011_MatlabCode/STMAD_index.m:
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/matlab/STMAD_2011_MatlabCode/calcSMADScore.m:
--------------------------------------------------------------------------------
1 | function calcSMADScore(rname,dname,colms,rows)
2 |
3 | rfid = fopen(rname);
4 | dfid = fopen(dname);
5 |
6 | iframe = 0;
7 | while 1
8 |
9 | [yr,~,~] = readframefromfid(rfid,rows,colms);
10 | [yd,~,~] = readframefromfid(dfid,rows,colms);
11 |
12 | if feof(rfid) || feof(dfid)
13 | break;
14 | end
15 |
16 | % read successful, can then reshape
17 | OrgImg = reshape(yr,[colms rows])';
18 | DstImg = reshape(yd,[colms rows])';
19 |
20 | HiIndex = hi_index(OrgImg, DstImg);
21 | LoIndex = lo_index(OrgImg, DstImg);
22 |
23 | disp(sprintf('HiIndex: %d %f', iframe, HiIndex));
24 | disp(sprintf('LoIndex: %d %f', iframe, LoIndex));
25 |
26 | iframe = iframe+1;
27 |
28 | end
29 |
30 | % repeat reading for last frame
31 | % disp(sprintf('HiIndex: %d %f', iframe, HiIndex));
32 | % disp(sprintf('LoIndex: %d %f', iframe, LoIndex));
33 |
34 | fclose(rfid);
35 | fclose(dfid);
36 |
37 | end
38 |
39 |
--------------------------------------------------------------------------------
/matlab/STMAD_2011_MatlabCode/calculateSMADScore.m:
--------------------------------------------------------------------------------
1 | function calcSMADScore(rname,dname,rows,colms)
2 |
3 | rfid = fopen(rname);
4 | dfid = fopen(dname);
5 |
6 | iframe = -1;
7 | while 1
8 |
9 | [yr,cbr,crr] = readframefromfid(rfid,rows,colms);
10 | [yd,cbr,crr] = readframefromfid(dfid,rows,colms);
11 |
12 | if feof(rfid) || feof(dfid)
13 | break;
14 | end
15 |
16 | % read successful, can then reshape
17 | OrgImg = reshape(yr,rows,colms)';
18 | DstImg = reshape(yd,rows,colms)';
19 |
20 | HiIndex = hi_index(OrgImg, DstImg);
21 | LoIndex = lo_index(OrgImg, DstImg);
22 |
23 | disp(sprintf('HiIndex: %d %f', iframe, HiIndex));
24 | disp(sprintf('LoIndex: %d %f', iframe, LoIndex));
25 |
26 | iframe = iframe+1;
27 |
28 | end
29 |
30 | % repeat reading for last frame
31 | disp(sprintf('HiIndex: %d %f', iframe, HiIndex));
32 | disp(sprintf('LoIndex: %d %f', iframe, LoIndex));
33 |
34 | fclose(rfid);
35 | fclose(dfid);
36 |
37 | end
38 |
39 |
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/matlab/STMAD_2011_MatlabCode/readframefromfid.m:
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1 | function [y,cb,cr]=readframefromfid(fid,height,width)
2 |
3 | % for now, read yuv420p only
4 |
5 | y=fread(fid,width*height, 'uchar')';
6 | cb=fread(fid,width*height/4, 'uchar')';
7 | cr=fread(fid,width*height/4, 'uchar')';
8 |
9 | end
--------------------------------------------------------------------------------
/matlab/STMAD_2011_MatlabCode/run_smad.m:
--------------------------------------------------------------------------------
1 | function run_smad(ref_filename, dis_filename, width, height)
2 |
3 | path(path,'./STMAD_2011_MatlabCode');
4 |
5 | calcSMADScore(ref_filename, dis_filename, width, height);
6 |
7 | % dmos_score = rred2dmos(strred_score)
8 |
9 | end
10 |
11 |
12 |
13 |
14 |
15 |
16 |
17 |
18 |
19 |
20 |
21 |
22 |
23 |
24 |
25 |
26 |
27 |
28 |
29 |
30 |
31 |
32 |
33 |
34 |
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/matlab/STMAD_2011_MatlabCode/run_stmad.m:
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1 | function run_stmad(ref_filename, dis_filename, width, height)
2 |
3 | path(path,'./STMAD_2011_MatlabCode');
4 |
5 | calcSTMADScore(ref_filename, dis_filename, width, height);
6 |
7 | % dmos_score = rred2dmos(strred_score)
8 |
9 | end
10 |
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/matlab/SpEED/run_speed.m:
--------------------------------------------------------------------------------
1 | function run_speed(ref_filename, dis_filename, width, height, bands, yuv_type)
2 | %RUN_SPEED Summary of this function goes here
3 | % Detailed explanation goes here
4 |
5 | path(path,'./SpEED');
6 | calcSpEEDScore(ref_filename, dis_filename, width, height, bands, yuv_type)
7 | end
8 |
9 |
10 |
11 |
12 |
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/matlab/cid_icid/run_icid.m:
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1 | function run_icid(ref_filename, dis_filename, width, height, yuv_type)
2 |
3 | path(path,'./iCID/iCID_Metric');
4 | path(path,'./iCID/iCID_Metric/ColorSpaceTransformations');
5 |
6 | yuv_ref = yuvread(ref_filename,width,height,yuv_type,1);
7 | yuv_dis = yuvread(dis_filename,width,height,yuv_type,1);
8 |
9 | len = min(length(yuv_ref), length(yuv_dis));
10 |
11 | result = zeros(1,len);
12 |
13 | for idx = 1:len
14 | OrgImg = yuv_ref(idx).cdata;
15 | DstImg = yuv_dis(idx).cdata;
16 | OrgImg = yuv2rgb(OrgImg(:,:,1), OrgImg(:,:,2), OrgImg(:,:,3),'YUV444_8');
17 | DstImg = yuv2rgb(DstImg(:,:,1), DstImg(:,:,2), DstImg(:,:,3),'YUV444_8');
18 | [result(idx), ~] = iCID(OrgImg, DstImg);
19 | end
20 |
21 |
22 | for frame_ind = 0 : len - 1
23 | disp(sprintf('icid: %d %f', frame_ind, result(frame_ind + 1)));
24 | end;
25 |
26 | end
27 |
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/matlab/strred/README:
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1 | ** modifications **
2 |
3 | (12/19/2016 zli@netflix.com) Three modifications are made to fit into the VDK framework:
4 | 1) Instead of specifying number of seconds to read, read file until the end.
5 | 2) Instead of calculating a frame score every two frames, change it to one score
6 | every frame.
7 | 3) Original algorithm averages frame SRRED and TRRED scores first, and the final
8 | STRRED score is the product of the two. In this modified version, only the per-
9 | frame SRRED and TRRED scores are calculated and passed out. The computation of
10 | the STRRED score is performed outside, by first computing the per-frame STRRED
11 | score via:
12 | per-frame STRRED = (per-frame SRRED) * (per-frame TRRED)
13 | and then aggregating (e.g. via taking the mean).
14 |
15 | ** run **
16 |
17 | Command run_strred takes in arguments:
18 | ref_yuv_file_path dis_yuv_file_path width height
19 |
20 | After installing Matlab and setting path, run STRRED in command line:
21 | matlab -nodisplay -nosplash -nodesktop -r "run_strred('../../python/test/resource/yuv/src01_hrc00_576x324.yuv', '../../python/test/resource/yuv/src01_hrc01_576x324.yuv', 576, 324); exit;"
22 |
23 |
24 |
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1 | ������
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/matlab/strred/matlabPyrTools/MEX/Makefile-linux:
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1 | MLAB = /usr/local/matlab5.1
2 |
3 | MXSFX = mexlx
4 | MEX = ${MLAB}/bin/mex
5 |
6 | MFLAGS = -V4
7 | INC = -I ${MLAB}/extern/include
8 | LIB = -L ${MLAB}/extern/lib
9 |
10 | CC = gcc -Wall -pedantic
11 | C_OPTIMIZE_SWITCH = -O2 ## For GCC
12 | CFLAGS = ${C_OPTIMIZE_SWITCH} ${INC} ${LIB}
13 |
14 | all: corrDn.${MXSFX} upConv.${MXSFX} pointOp.${MXSFX} \
15 | histo.${MXSFX} range2.${MXSFX}
16 |
17 | clean:
18 | /bin/rm *.o
19 |
20 | corrDn.${MXSFX}: corrDn.o wrap.o convolve.o edges.o
21 | ${MEX} ${MFLAGS} corrDn.o wrap.o convolve.o edges.o
22 |
23 | upConv.${MXSFX}: upConv.o wrap.o convolve.o edges.o
24 | ${MEX} ${MFLAGS} upConv.o wrap.o convolve.o edges.o
25 |
26 | pointOp.${MXSFX}: pointOp.o
27 | ${MEX} ${MFLAGS} pointOp.o
28 |
29 | histo.${MXSFX}: histo.o
30 | ${MEX} ${MFLAGS} histo.o
31 |
32 | range2.${MXSFX}: range2.o
33 | ${MEX} ${MFLAGS} range2.o
34 |
35 | convolve.o wrap.o edges.o: convolve.h
36 |
37 | %.o : %.c
38 | ${CC} -c ${CFLAGS} lt;
39 |
40 |
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/matlab/strred/matlabPyrTools/MEX/Makefile-ml6-linux:
--------------------------------------------------------------------------------
1 | MLAB = /usr/local/matlab6.0
2 |
3 | MXSFX = mexglx
4 | MEX = ${MLAB}/bin/mex
5 |
6 | MFLAGS = -V4
7 | INC = -I ${MLAB}/extern/include
8 | LIB = -L ${MLAB}/extern/lib
9 |
10 | CC = gcc -Wall -pedantic
11 | C_OPTIMIZE_SWITCH = -O2 ## For GCC
12 | CFLAGS = ${C_OPTIMIZE_SWITCH} ${INC} ${LIB}
13 |
14 | all: corrDn.${MXSFX} upConv.${MXSFX} pointOp.${MXSFX} \
15 | histo.${MXSFX} range2.${MXSFX}
16 |
17 | clean:
18 | /bin/rm *.o
19 |
20 | corrDn.${MXSFX}: corrDn.o wrap.o convolve.o edges.o
21 | ${MEX} ${MFLAGS} corrDn.o wrap.o convolve.o edges.o
22 |
23 | upConv.${MXSFX}: upConv.o wrap.o convolve.o edges.o
24 | ${MEX} ${MFLAGS} upConv.o wrap.o convolve.o edges.o
25 |
26 | pointOp.${MXSFX}: pointOp.o
27 | ${MEX} ${MFLAGS} pointOp.o
28 |
29 | histo.${MXSFX}: histo.o
30 | ${MEX} ${MFLAGS} histo.o
31 |
32 | range2.${MXSFX}: range2.o
33 | ${MEX} ${MFLAGS} range2.o
34 |
35 | convolve.o wrap.o edges.o: convolve.h
36 |
37 | %.o : %.c
38 | ${CC} -c ${CFLAGS} lt;
39 |
40 |
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/matlab/strred/matlabPyrTools/MEX/Makefile-osx:
--------------------------------------------------------------------------------
1 | MLAB = /share/wotan/matlab13
2 |
3 | MXSFX = mexosx
4 | MEX = ${MLAB}/bin/mex
5 |
6 | MFLAGS =
7 | INC = -I ${MLAB}/extern/include
8 | LIB = -L ${MLAB}/extern/lib
9 |
10 | CC = cc -Wall -pedantic -no-cpp-precomp
11 | C_OPTIMIZE_SWITCH = -O2 ## For GCC
12 | CFLAGS = ${C_OPTIMIZE_SWITCH} ${INC} ${LIB}
13 |
14 | all: corrDn.${MXSFX} upConv.${MXSFX} pointOp.${MXSFX} \
15 | histo.${MXSFX} range2.${MXSFX}
16 |
17 | clean:
18 | /bin/rm *.o
19 |
20 | corrDn.${MXSFX}: corrDn.o wrap.o convolve.o edges.o
21 | ${MEX} ${MFLAGS} corrDn.o wrap.o convolve.o edges.o
22 |
23 | upConv.${MXSFX}: upConv.o wrap.o convolve.o edges.o
24 | ${MEX} ${MFLAGS} upConv.o wrap.o convolve.o edges.o
25 |
26 | pointOp.${MXSFX}: pointOp.o
27 | ${MEX} ${MFLAGS} pointOp.o
28 |
29 | histo.${MXSFX}: histo.o
30 | ${MEX} ${MFLAGS} histo.o
31 |
32 | range2.${MXSFX}: range2.o
33 | ${MEX} ${MFLAGS} range2.o
34 |
35 | convolve.o wrap.o edges.o: convolve.h
36 |
37 | %.o : %.c
38 | ${CC} -c ${CFLAGS} lt;
39 |
40 |
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/matlab/strred/matlabPyrTools/MEX/Makefile-solaris:
--------------------------------------------------------------------------------
1 | MLAB = /export/home/Solaris2/matlab5.1
2 |
3 | MXSFX = mexsol
4 | MEX = ${MLAB}/bin/mex
5 |
6 | MFLAGS = -V4
7 | INC = -I ${MLAB}/extern/include
8 | LIB = -L ${MLAB}/extern/lib
9 |
10 | CC = gcc -Wall -pedantic
11 | C_OPTIMIZE_SWITCH = -O2 ## For GCC
12 | CFLAGS = ${C_OPTIMIZE_SWITCH} ${INC} ${LIB}
13 |
14 | all: corrDn.${MXSFX} upConv.${MXSFX} pointOp.${MXSFX} \
15 | histo.${MXSFX} range2.${MXSFX}
16 |
17 | clean:
18 | /bin/rm *.o
19 |
20 | corrDn.${MXSFX}: corrDn.o wrap.o convolve.o edges.o
21 | ${MEX} ${MFLAGS} corrDn.o wrap.o convolve.o edges.o
22 |
23 | upConv.${MXSFX}: upConv.o wrap.o convolve.o edges.o
24 | ${MEX} ${MFLAGS} upConv.o wrap.o convolve.o edges.o
25 |
26 | pointOp.${MXSFX}: pointOp.o
27 | ${MEX} ${MFLAGS} pointOp.o
28 |
29 | histo.${MXSFX}: histo.o
30 | ${MEX} ${MFLAGS} histo.o
31 |
32 | range2.${MXSFX}: range2.o
33 | ${MEX} ${MFLAGS} range2.o
34 |
35 | convolve.o wrap.o edges.o: convolve.h
36 |
37 | %.o : %.c
38 | ${CC} -c ${CFLAGS} lt;
39 |
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/matlab/strred/matlabPyrTools/MEX/Makefile-sun4:
--------------------------------------------------------------------------------
1 | MLAB = /home/alberich/matlab4
2 |
3 | MXSFX = mex4
4 | MEX = ${MLAB}/bin/cmex
5 |
6 | MFLAGS =
7 | INC = -I ${MLAB}/extern/include
8 | LIB = -L ${MLAB}/extern/lib/sun4
9 |
10 | CC = gcc
11 | C_OPTIMIZE_SWITCH = -O2 ## For GCC
12 | CFLAGS = ${C_OPTIMIZE_SWITCH} ${INC} ${LIB}
13 |
14 | all: corrDn.${MXSFX} upConv.${MXSFX} pointOp.${MXSFX} \
15 | histo.${MXSFX} range2.${MXSFX}
16 |
17 | clean:
18 | /bin/rm *.o
19 |
20 | corrDn.${MXSFX}: corrDn.o wrap.o convolve.o edges.o
21 | ${MEX} ${MFLAGS} corrDn.o wrap.o convolve.o edges.o
22 |
23 | upConv.${MXSFX}: upConv.o wrap.o convolve.o edges.o
24 | ${MEX} ${MFLAGS} upConv.o wrap.o convolve.o edges.o
25 |
26 | pointOp.${MXSFX}: pointOp.o
27 | ${MEX} ${MFLAGS} pointOp.o
28 |
29 | histo.${MXSFX}: histo.o
30 | ${MEX} ${MFLAGS} histo.o
31 |
32 | range2.${MXSFX}: range2.o
33 | ${MEX} ${MFLAGS} range2.o
34 |
35 | convolve.o wrap.o edges.o: convolve.h
36 |
37 | %.o : %.c
38 | ${CC} -c ${CFLAGS} lt;
39 |
40 |
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2 | _mexFunction _mexFunction
3 |
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/matlab/strred/matlabPyrTools/TUTORIALS/README:
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1 |
2 | This directory contains some Matlab script files that serve to give
3 | example usage of this code, and also to explain some of the
4 | representations and algorithms.
5 |
6 | The files are NOT meant to be executed from the MatLab prompt (like many
7 | of the MatLab demos). You should instead read through the comments,
8 | executing the subsequent pieces of code. This gives you a chance to
9 | explore as you go...
10 |
11 | matlabPyrTools.m - Example usage of the code in the distribution.
12 |
13 | pyramids.m - An introduction to multi-scale pyramid representations,
14 | covering Laplacian, QMF/Wavelet, and Steerable pyramids. The
15 | file assumes a knowledge of linear systems, matrix algebra,
16 | and 2D Fourier transforms.
17 |
18 | more to come....
19 |
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/matlab/strred/matlabPyrTools/binomialFilter.m:
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1 | % KERNEL = binomialFilter(size)
2 | %
3 | % Returns a vector of binomial coefficients of order (size-1) .
4 |
5 | % Eero Simoncelli, 2/97.
6 |
7 | function [kernel] = binomialFilter(sz)
8 |
9 | if (sz < 2)
10 | error('size argument must be larger than 1');
11 | end
12 |
13 | kernel = [0.5 0.5]';
14 |
15 | for n=1:sz-2
16 | kernel = conv([0.5 0.5]', kernel);
17 | end
18 |
19 |
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/matlab/strred/matlabPyrTools/blur.m:
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1 | % RES = blur(IM, LEVELS, FILT)
2 | %
3 | % Blur an image, by filtering and downsampling LEVELS times
4 | % (default=1), followed by upsampling and filtering LEVELS times. The
5 | % blurring is done with filter kernel specified by FILT (default =
6 | % 'binom5'), which can be a string (to be passed to namedFilter), a
7 | % vector (applied separably as a 1D convolution kernel in X and Y), or
8 | % a matrix (applied as a 2D convolution kernel). The downsampling is
9 | % always by 2 in each direction.
10 |
11 | % Eero Simoncelli, 3/04.
12 |
13 | function res = blur(im, nlevs, filt)
14 |
15 | %------------------------------------------------------------
16 | %% OPTIONAL ARGS:
17 |
18 | if (exist('nlevs') ~= 1)
19 | nlevs = 1;
20 | end
21 |
22 | if (exist('filt') ~= 1)
23 | filt = 'binom5';
24 | end
25 |
26 | %------------------------------------------------------------
27 |
28 | res = upBlur(blurDn(im,nlevs,filt));
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/matlab/strred/matlabPyrTools/buildSpyrLevs.m:
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1 | % [PYR, INDICES] = buildSpyrLevs(LOIM, HEIGHT, LOFILT, BFILTS, EDGES)
2 | %
3 | % Recursive function for constructing levels of a steerable pyramid. This
4 | % is called by buildSpyr, and is not usually called directly.
5 |
6 | % Eero Simoncelli, 6/96.
7 |
8 | function [pyr,pind] = buildSpyrLevs(lo0,ht,lofilt,bfilts,edges);
9 |
10 | if (ht <= 0)
11 |
12 | pyr = lo0(:);
13 | pind = size(lo0);
14 |
15 | else
16 |
17 | % Assume square filters:
18 | bfiltsz = round(sqrt(size(bfilts,1)));
19 |
20 | bands = zeros(prod(size(lo0)),size(bfilts,2));
21 | bind = zeros(size(bfilts,2),2);
22 |
23 | for b = 1:size(bfilts,2)
24 | filt = reshape(bfilts(:,b),bfiltsz,bfiltsz);
25 | band = corrDn(lo0, filt, edges);
26 | bands(:,b) = band(:);
27 | bind(b,:) = size(band);
28 | end
29 |
30 | lo = corrDn(lo0, lofilt, edges, [2 2], [1 1]);
31 |
32 | [npyr,nind] = buildSpyrLevs(lo, ht-1, lofilt, bfilts, edges);
33 |
34 | pyr = [bands(:); npyr];
35 | pind = [bind; nind];
36 |
37 | end
38 |
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/matlab/strred/matlabPyrTools/clip.m:
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1 | % [RES] = clip(IM, MINVALorRANGE, MAXVAL)
2 | %
3 | % Clip values of matrix IM to lie between minVal and maxVal:
4 | % RES = max(min(IM,MAXVAL),MINVAL)
5 | % The first argument can also specify both min and max, as a 2-vector.
6 | % If only one argument is passed, the range defaults to [0,1].
7 |
8 | function res = clip(im, minValOrRange, maxVal)
9 |
10 | if (exist('minValOrRange') ~= 1)
11 | minVal = 0;
12 | maxVal = 1;
13 | elseif (length(minValOrRange) == 2)
14 | minVal = minValOrRange(1);
15 | maxVal = minValOrRange(2);
16 | elseif (length(minValOrRange) == 1)
17 | minVal = minValOrRange;
18 | if (exist('maxVal') ~= 1)
19 | maxVal=minVal+1;
20 | end
21 | else
22 | error('MINVAL must be a scalar or a 2-vector');
23 | end
24 |
25 | if ( maxVal < minVal )
26 | error('MAXVAL should be less than MINVAL');
27 | end
28 |
29 | res = im;
30 | res(find(im < minVal)) = minVal;
31 | res(find(im > maxVal)) = maxVal;
32 |
33 |
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/matlab/strred/matlabPyrTools/einstein.pgm:
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https://raw.githubusercontent.com/Netflix/vmaf/b9ac69e6c4231fad0465021f9e31a841a18261db/matlab/strred/matlabPyrTools/einstein.pgm
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/matlab/strred/matlabPyrTools/entropy2.m:
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1 | % E = ENTROPY2(MTX,BINSIZE)
2 | %
3 | % Compute the first-order sample entropy of MTX. Samples of VEC are
4 | % first discretized. Optional argument BINSIZE controls the
5 | % discretization, and defaults to 256/(max(VEC)-min(VEC)).
6 | %
7 | % NOTE: This is a heavily biased estimate of entropy when you
8 | % don't have much data.
9 |
10 | % Eero Simoncelli, 6/96.
11 |
12 | function res = entropy2(mtx,binsize)
13 |
14 | %% Ensure it's a vector, not a matrix.
15 | vec = mtx(:);
16 | [mn,mx] = range2(vec);
17 |
18 | if (exist('binsize') == 1)
19 | nbins = max((mx-mn)/binsize, 1);
20 | else
21 | nbins = 256;
22 | end
23 |
24 | [bincount,bins] = histo(vec,nbins);
25 |
26 | %% Collect non-zero bins:
27 | H = bincount(find(bincount));
28 | H = H/sum(H);
29 |
30 | res = -sum(H .* log2(H));
31 |
32 |
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/matlab/strred/matlabPyrTools/factorial.m:
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1 | %% RES = factorial(NUM)
2 | %
3 | % Factorial function that works on matrices (matlab's does not).
4 |
5 | % EPS, 11/02
6 |
7 | function res = factorial(num)
8 |
9 | res = ones(size(num));
10 |
11 | ind = find(num > 0);
12 | if ( ~isempty(ind) )
13 | subNum = num(ind);
14 | res(ind) = subNum .* factorial(subNum-1);
15 | end
16 |
17 |
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/matlab/strred/matlabPyrTools/feynman.pgm:
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https://raw.githubusercontent.com/Netflix/vmaf/b9ac69e6c4231fad0465021f9e31a841a18261db/matlab/strred/matlabPyrTools/feynman.pgm
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/matlab/strred/matlabPyrTools/histoMatch.m:
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1 | % RES = histoMatch(MTX, N, X)
2 | %
3 | % Modify elements of MTX so that normalized histogram matches that
4 | % specified by vectors X and N, where N contains the histogram counts
5 | % and X the histogram bin positions (see histo).
6 |
7 | % Eero Simoncelli, 7/96.
8 |
9 | function res = histoMatch(mtx, N, X)
10 |
11 | if ( exist('histo') == 3 )
12 | [oN, oX] = histo(mtx(:), size(X(:),1));
13 | else
14 | [oN, oX] = hist(mtx(:), size(X(:),1));
15 | end
16 |
17 | oStep = oX(2) - oX(1);
18 | oC = [0, cumsum(oN)]/sum(oN);
19 | oX = [oX(1)-oStep/2, oX+oStep/2];
20 |
21 | N = N(:)';
22 | X = X(:)';
23 | N = N + mean(N)/(1e8); %% HACK: no empty bins ensures nC strictly monotonic
24 |
25 | nStep = X(2) - X(1);
26 | nC = [0, cumsum(N)]/sum(N);
27 | nX = [X(1)-nStep/2, X+nStep/2];
28 |
29 | nnX = interp1(nC, nX, oC, 'linear');
30 |
31 | if ( exist('pointOp') == 3 )
32 | res = pointOp(mtx, nnX, oX(1), oStep);
33 | else
34 | res = reshape(interp1(oX, nnX, mtx(:)),size(mtx,1),size(mtx,2));
35 | end
36 |
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/matlab/strred/matlabPyrTools/ifftshift.m:
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1 | % [RES] = ifftshift (MTX)
2 | %
3 | % Inverse of MatLab's FFTSHIFT. That is,
4 | % ifftshift(fftshift(MTX)) = MTX
5 | % for any size MTX.
6 |
7 | % Eero Simoncelli, 2/97.
8 |
9 | function [res] = ifftshift(mtx)
10 |
11 | sz = size(mtx);
12 | DC = ceil((sz+1)./2); % location of DC term in a matlab fft.
13 |
14 | res = [mtx(DC(1):sz(1), DC(2):sz(2)) , mtx(DC(1):sz(1), 1:DC(2)-1); ...
15 | mtx(1:DC(1)-1, DC(2):sz(2)) , mtx(1:DC(1)-1, 1:DC(2)-1)];
16 |
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/matlab/strred/matlabPyrTools/imStats.m:
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1 | % imStats(IM1,IM2)
2 | %
3 | % Report image (matrix) statistics.
4 | % When called on a single image IM1, report min, max, mean, stdev,
5 | % and kurtosis.
6 | % When called on two images (IM1 and IM2), report min, max, mean,
7 | % stdev of the difference, and also SNR (relative to IM1).
8 |
9 | % Eero Simoncelli, 6/96.
10 |
11 | function [] = imStats(im1,im2)
12 |
13 | if (~isreal(im1))
14 | error('Args must be real-valued matrices');
15 | end
16 |
17 | if (exist('im2') == 1)
18 | difference = im1 - im2;
19 | [mn,mx] = range2(difference);
20 | mean = mean2(difference);
21 | v = var2(difference,mean);
22 | if (v < realmin)
23 | snr = Inf;
24 | else
25 | snr = 10 * log10(var2(im1)/v);
26 | end
27 | fprintf(1, 'Difference statistics:\n');
28 | fprintf(1, ' Range: [%c, %c]\n',mn,mx);
29 | fprintf(1, ' Mean: %f, Stdev (rmse): %f, SNR (dB): %f\n',...
30 | mean,sqrt(v),snr);
31 | else
32 | [mn,mx] = range2(im1);
33 | mean = mean2(im1);
34 | var = var2(im1);
35 | stdev = sqrt(real(var))+sqrt(imag(var));
36 | kurt = kurt2(im1, mean, stdev^2);
37 | fprintf(1, 'Image statistics:\n');
38 | fprintf(1, ' Range: [%f, %f]\n',mn,mx);
39 | fprintf(1, ' Mean: %f, Stdev: %f, Kurtosis: %f\n',mean,stdev,kurt);
40 | end
41 |
42 |
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/matlab/strred/matlabPyrTools/innerProd.m:
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1 | % RES = innerProd(MTX)
2 | %
3 | % Compute (MTX' * MTX) efficiently (i.e., without copying the matrix)
4 |
5 | function res = innerProd(mtx)
6 |
7 | fprintf(1,['WARNING: You should compile the MEX version of' ...
8 | ' "innerProd.c",\n found in the MEX subdirectory' ...
9 | ' of matlabPyrTools, and put it in your matlab path.' ...
10 | ' It is MUCH faster and requires less memory.\n']);
11 |
12 | res = mtx' * mtx;
13 |
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/matlab/strred/matlabPyrTools/kurt2.m:
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1 | % K = KURT2(MTX,MEAN,VAR)
2 | %
3 | % Sample kurtosis (fourth moment divided by squared variance)
4 | % of a matrix. Kurtosis of a Gaussian distribution is 3.
5 | % MEAN (optional) and VAR (optional) make the computation faster.
6 |
7 | % Eero Simoncelli, 6/96.
8 |
9 | function res = kurt2(mtx, mn, v)
10 |
11 | if (exist('mn') ~= 1)
12 | mn = mean(mean(mtx));
13 | end
14 |
15 | if (exist('v') ~= 1)
16 | v = var2(mtx,mn);
17 | end
18 |
19 | if (isreal(mtx))
20 | res = mean(mean(abs(mtx-mn).^4)) / (v^2);
21 | else
22 | res = mean(mean(real(mtx-mn).^4)) / (real(v)^2) + ...
23 | i*mean(mean(imag(mtx-mn).^4)) / (imag(v)^2);
24 | end
25 |
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/matlab/strred/matlabPyrTools/lplot.m:
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1 | % lplot(VEC, XRANGE)
2 | %
3 | % Plot VEC, a vector, in "lollipop" format.
4 | % XRANGE (optional, default = [1,length(VEC)]), should be a 2-vector
5 | % specifying the X positions (for labeling purposes) of the first and
6 | % last sample of VEC.
7 |
8 | % Mark Liberman, Linguistics Dept, UPenn, 1994.
9 |
10 | function lplot(x,xrange)
11 |
12 | if (exist('xrange') ~= 1)
13 | xrange = [1,length(x)];
14 | end
15 |
16 | msize = size(x);
17 | if ( msize(2) == 1)
18 | x = x';
19 | elseif (msize(1) ~= 1)
20 | error('First arg must be a vector');
21 | end
22 |
23 | if (~isreal(x))
24 | fprintf(1,'Warning: Imaginary part of signal ignored\n');
25 | x = abs(x);
26 | end
27 |
28 | N = length(x);
29 | index = xrange(1) + (xrange(2)-xrange(1))*[0:(N-1)]/(N-1)
30 | xinc = index(2)-index(1);
31 |
32 | xx = [zeros(1,N);x;zeros(1,N)];
33 | indexis = [index;index;index];
34 | xdiscrete = [0 xx(:)' 0];
35 | idiscrete = [index(1)-xinc indexis(:)' index(N)+xinc];
36 |
37 | [mn,mx] = range2(xdiscrete);
38 | ypad = (mx-mn)/12; % MAGIC NUMBER: graph padding
39 |
40 | plot(idiscrete, xdiscrete, index, x, 'o');
41 | axis([index(1)-xinc, index(N)+xinc, mn-ypad, mx+ypad]);
42 |
43 | return
44 |
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/matlab/strred/matlabPyrTools/lpyrHt.m:
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1 | % [HEIGHT] = lpyrHt(INDICES)
2 | %
3 | % Compute height of Laplacian pyramid with given its INDICES matrix.
4 | % See buildLpyr.m
5 |
6 | % Eero Simoncelli, 6/96.
7 |
8 | function [ht] = lpyrHt(pind)
9 |
10 | % Don't count lowpass residual band
11 | ht = size(pind,1)-1;
12 |
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/matlab/strred/matlabPyrTools/maxPyrHt.m:
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1 | % HEIGHT = maxPyrHt(IMSIZE, FILTSIZE)
2 | %
3 | % Compute maximum pyramid height for given image and filter sizes.
4 | % Specifically: the number of corrDn operations that can be sequentially
5 | % performed when subsampling by a factor of 2.
6 |
7 | % Eero Simoncelli, 6/96.
8 |
9 | function height = maxPyrHt(imsz, filtsz)
10 |
11 | imsz = imsz(:);
12 | filtsz = filtsz(:);
13 |
14 | if any(imsz == 1) % 1D image
15 | imsz = prod(imsz);
16 | filtsz = prod(filtsz);
17 | elseif any(filtsz == 1) % 2D image, 1D filter
18 | filtsz = [filtsz(1); filtsz(1)];
19 | end
20 |
21 | if any(imsz < filtsz)
22 | height = 0;
23 | else
24 | height = 1 + maxPyrHt( floor(imsz/2), filtsz );
25 | end
26 |
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/matlab/strred/matlabPyrTools/mean2.m:
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1 | % M = MEAN2(MTX)
2 | %
3 | % Sample mean of a matrix.
4 |
5 | function res = mean2(mtx)
6 |
7 | res = mean(mean(mtx));
8 |
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/matlab/strred/matlabPyrTools/mkAngle.m:
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1 | % IM = mkAngle(SIZE, PHASE, ORIGIN)
2 | %
3 | % Compute a matrix of dimension SIZE (a [Y X] 2-vector, or a scalar)
4 | % containing samples of the polar angle (in radians, CW from the
5 | % X-axis, ranging from -pi to pi), relative to angle PHASE (default =
6 | % 0), about ORIGIN pixel (default = (size+1)/2).
7 |
8 | % Eero Simoncelli, 6/96.
9 |
10 | function [res] = mkAngle(sz, phase, origin)
11 |
12 | sz = sz(:);
13 | if (size(sz,1) == 1)
14 | sz = [sz,sz];
15 | end
16 |
17 | % -----------------------------------------------------------------
18 | % OPTIONAL args:
19 |
20 | if (exist('origin') ~= 1)
21 | origin = (sz+1)/2;
22 | end
23 |
24 | % -----------------------------------------------------------------
25 |
26 | [xramp,yramp] = meshgrid( [1:sz(2)]-origin(2), [1:sz(1)]-origin(1) );
27 |
28 | res = atan2(yramp,xramp);
29 |
30 | if (exist('phase') == 1)
31 | res = mod(res+(pi-phase),2*pi)-pi;
32 | end
33 |
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/matlab/strred/matlabPyrTools/mkAngularSine.m:
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1 | % IM = mkAngularSine(SIZE, HARMONIC, AMPL, PHASE, ORIGIN)
2 | %
3 | % Make an angular sinusoidal image:
4 | % AMPL * sin( HARMONIC*theta + PHASE),
5 | % where theta is the angle about the origin.
6 | % SIZE specifies the matrix size, as for zeros().
7 | % AMPL (default = 1) and PHASE (default = 0) are optional.
8 |
9 | % Eero Simoncelli, 2/97.
10 |
11 | function [res] = mkAngularSine(sz, harmonic, ampl, ph, origin)
12 |
13 | sz = sz(:);
14 | if (size(sz,1) == 1)
15 | sz = [sz,sz];
16 | end
17 |
18 | mxsz = max(sz(1),sz(2));
19 |
20 | %------------------------------------------------------------
21 | %% OPTIONAL ARGS:
22 |
23 | if (exist('harmonic') ~= 1)
24 | harmonic = 1;
25 | end
26 |
27 | if (exist('ampl') ~= 1)
28 | ampl = 1;
29 | end
30 |
31 | if (exist('ph') ~= 1)
32 | ph = 0;
33 | end
34 |
35 | if (exist('origin') ~= 1)
36 | origin = (sz+1)/2;
37 | end
38 |
39 | %------------------------------------------------------------
40 |
41 | res = ampl * sin(harmonic*mkAngle(sz,ph,origin) + ph);
42 |
43 |
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/matlab/strred/matlabPyrTools/mkFract.m:
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1 | % IM = mkFract(SIZE, FRACT_DIM)
2 | %
3 | % Make a matrix of dimensions SIZE (a [Y X] 2-vector, or a scalar)
4 | % containing fractal (pink) noise with power spectral density of the
5 | % form: 1/f^(5-2*FRACT_DIM). Image variance is normalized to 1.0.
6 | % FRACT_DIM defaults to 1.0
7 |
8 | % Eero Simoncelli, 6/96.
9 |
10 | %% TODO: Verify that this matches Mandelbrot defn of fractal dimension.
11 | %% Make this more efficient!
12 |
13 | function res = mkFract(dims, fract_dim)
14 |
15 | if (exist('fract_dim') ~= 1)
16 | fract_dim = 1.0;
17 | end
18 |
19 | res = randn(dims);
20 | fres = fft2(res);
21 |
22 | sz = size(res);
23 | ctr = ceil((sz+1)./2);
24 |
25 | shape = ifftshift(mkR(sz, -(2.5-fract_dim), ctr));
26 | shape(1,1) = 1; %%DC term
27 |
28 | fres = shape .* fres;
29 | fres = ifft2(fres);
30 |
31 | if (max(max(abs(imag(fres)))) > 1e-10)
32 | error('Symmetry error in creating fractal');
33 | else
34 | res = real(fres);
35 | res = res / sqrt(var2(res));
36 | end
37 |
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/matlab/strred/matlabPyrTools/mkImpulse.m:
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1 | % IM = mkImpulse(SIZE, ORIGIN, AMPLITUDE)
2 | %
3 | % Compute a matrix of dimension SIZE (a [Y X] 2-vector, or a scalar)
4 | % containing a single non-zero entry, at position ORIGIN (defaults to
5 | % ceil(size/2)), of value AMPLITUDE (defaults to 1).
6 |
7 | % Eero Simoncelli, 6/96.
8 |
9 | function [res] = mkImpulse(sz, origin, amplitude)
10 |
11 | sz = sz(:)';
12 | if (size(sz,2) == 1)
13 | sz = [sz sz];
14 | end
15 |
16 | if (exist('origin') ~= 1)
17 | origin = ceil(sz/2);
18 | end
19 |
20 | if (exist('amplitude') ~= 1)
21 | amplitude = 1;
22 | end
23 |
24 | res = zeros(sz);
25 | res(origin(1),origin(2)) = amplitude;
26 |
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/matlab/strred/matlabPyrTools/mkR.m:
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1 | % IM = mkR(SIZE, EXPT, ORIGIN)
2 | %
3 | % Compute a matrix of dimension SIZE (a [Y X] 2-vector, or a scalar)
4 | % containing samples of a radial ramp function, raised to power EXPT
5 | % (default = 1), with given ORIGIN (default = (size+1)/2, [1 1] =
6 | % upper left). All but the first argument are optional.
7 |
8 | % Eero Simoncelli, 6/96.
9 |
10 | function [res] = mkR(sz, expt, origin)
11 |
12 | sz = sz(:);
13 | if (size(sz,1) == 1)
14 | sz = [sz,sz];
15 | end
16 |
17 | % -----------------------------------------------------------------
18 | % OPTIONAL args:
19 |
20 | if (exist('expt') ~= 1)
21 | expt = 1;
22 | end
23 |
24 | if (exist('origin') ~= 1)
25 | origin = (sz+1)/2;
26 | end
27 |
28 | % -----------------------------------------------------------------
29 |
30 | [xramp,yramp] = meshgrid( [1:sz(2)]-origin(2), [1:sz(1)]-origin(1) );
31 |
32 | res = (xramp.^2 + yramp.^2).^(expt/2);
33 |
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/matlab/strred/matlabPyrTools/mkRamp.m:
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1 | % IM = mkRamp(SIZE, DIRECTION, SLOPE, INTERCEPT, ORIGIN)
2 | %
3 | % Compute a matrix of dimension SIZE (a [Y X] 2-vector, or a scalar)
4 | % containing samples of a ramp function, with given gradient DIRECTION
5 | % (radians, CW from X-axis, default = 0), SLOPE (per pixel, default =
6 | % 1), and a value of INTERCEPT (default = 0) at the ORIGIN (default =
7 | % (size+1)/2, [1 1] = upper left). All but the first argument are
8 | % optional.
9 |
10 | % Eero Simoncelli, 6/96. 2/97: adjusted coordinate system.
11 |
12 | function [res] = mkRamp(sz, dir, slope, intercept, origin)
13 |
14 | sz = sz(:);
15 | if (size(sz,1) == 1)
16 | sz = [sz,sz];
17 | end
18 |
19 | % -----------------------------------------------------------------
20 | % OPTIONAL args:
21 |
22 | if (exist('dir') ~= 1)
23 | dir = 0;
24 | end
25 |
26 | if (exist('slope') ~= 1)
27 | slope = 1;
28 | end
29 |
30 | if (exist('intercept') ~= 1)
31 | intercept = 0;
32 | end
33 |
34 | if (exist('origin') ~= 1)
35 | origin = (sz+1)/2;
36 | end
37 |
38 | % -----------------------------------------------------------------
39 |
40 | xinc = slope*cos(dir);
41 | yinc = slope*sin(dir);
42 |
43 | [xramp,yramp] = meshgrid( xinc*([1:sz(2)]-origin(2)), ...
44 | yinc*([1:sz(1)]-origin(1)) );
45 |
46 | res = intercept + xramp + yramp;
47 |
48 |
--------------------------------------------------------------------------------
/matlab/strred/matlabPyrTools/mkZonePlate.m:
--------------------------------------------------------------------------------
1 | % IM = mkZonePlate(SIZE, AMPL, PHASE)
2 | %
3 | % Make a "zone plate" image:
4 | % AMPL * cos( r^2 + PHASE)
5 | % SIZE specifies the matrix size, as for zeros().
6 | % AMPL (default = 1) and PHASE (default = 0) are optional.
7 |
8 | % Eero Simoncelli, 6/96.
9 |
10 | function [res] = mkZonePlate(sz, ampl, ph)
11 |
12 | sz = sz(:);
13 | if (size(sz,1) == 1)
14 | sz = [sz,sz];
15 | end
16 |
17 | mxsz = max(sz(1),sz(2));
18 |
19 | %------------------------------------------------------------
20 | %% OPTIONAL ARGS:
21 |
22 | if (exist('ampl') ~= 1)
23 | ampl = 1;
24 | end
25 |
26 | if (exist('ph') ~= 1)
27 | ph = 0;
28 | end
29 |
30 | %------------------------------------------------------------
31 |
32 | res = ampl * cos( (pi/mxsz) * mkR(sz,2) + ph );
33 |
34 |
--------------------------------------------------------------------------------
/matlab/strred/matlabPyrTools/mod1.m:
--------------------------------------------------------------------------------
1 | % M = mod(A,B)
2 | %
3 | % Modulus operator: returns A mod B.
4 | % Works on matrics, vectors or scalars.
5 | %
6 | % NOTE: This function is a Matlab-5 builtin, but was missing from Matlab-4.
7 |
8 | % Eero Simoncelli, 7/96.
9 |
10 | function m = mod(a,n)
11 |
12 | m = a - n .* floor(a./n);
13 | return;
14 |
15 |
--------------------------------------------------------------------------------
/matlab/strred/matlabPyrTools/modulateFlip.m:
--------------------------------------------------------------------------------
1 | % [HFILT] = modulateFlipShift(LFILT)
2 | %
3 | % QMF/Wavelet highpass filter construction: modulate by (-1)^n,
4 | % reverse order (and shift by one, which is handled by the convolution
5 | % routines). This is an extension of the original definition of QMF's
6 | % (e.g., see Simoncelli90).
7 |
8 | % Eero Simoncelli, 7/96.
9 |
10 | function [hfilt] = modulateFlipShift(lfilt)
11 |
12 | lfilt = lfilt(:);
13 |
14 | sz = size(lfilt,1);
15 | sz2 = ceil(sz/2);
16 |
17 | ind = [sz:-1:1]';
18 |
19 | hfilt = lfilt(ind) .* (-1).^(ind-sz2);
20 |
--------------------------------------------------------------------------------
/matlab/strred/matlabPyrTools/nextFig.m:
--------------------------------------------------------------------------------
1 | % nextFig (MAXFIGS, SKIP)
2 | %
3 | % Make figure number mod((GCF+SKIP), MAXFIGS) the current figure.
4 | % MAXFIGS is optional, and defaults to 2.
5 | % SKIP is optional, and defaults to 1.
6 |
7 | % Eero Simoncelli, 2/97.
8 |
9 | function nextFig(maxfigs, skip)
10 |
11 | if (exist('maxfigs') ~= 1)
12 | maxfigs = 2;
13 | end
14 |
15 | if (exist('skip') ~= 1)
16 | skip = 1;
17 | end
18 |
19 | figure(1+mod(gcf-1+skip,maxfigs));
20 |
--------------------------------------------------------------------------------
/matlab/strred/matlabPyrTools/pointOp.m:
--------------------------------------------------------------------------------
1 | % RES = pointOp(IM, LUT, ORIGIN, INCREMENT, WARNINGS)
2 | %
3 | % Apply a point operation, specified by lookup table LUT, to image IM.
4 | % LUT must be a row or column vector, and is assumed to contain
5 | % (equi-spaced) samples of the function. ORIGIN specifies the
6 | % abscissa associated with the first sample, and INCREMENT specifies the
7 | % spacing between samples. Between-sample values are estimated via
8 | % linear interpolation. If WARNINGS is non-zero, the function prints
9 | % a warning whenever the lookup table is extrapolated.
10 | %
11 | % This function is much faster than MatLab's interp1, and allows
12 | % extrapolation beyond the lookup table domain. The drawbacks are
13 | % that the lookup table must be equi-spaced, and the interpolation is
14 | % linear.
15 |
16 | % Eero Simoncelli, 8/96.
17 |
18 | function res = pointOp(im, lut, origin, increment, warnings)
19 |
20 | %% NOTE: THIS CODE IS NOT ACTUALLY USED! (MEX FILE IS CALLED INSTEAD)
21 |
22 | fprintf(1,'WARNING: You should compile the MEX version of "pointOp.c",\n found in the MEX subdirectory of matlabPyrTools, and put it in your matlab path. It is MUCH faster.\n');
23 |
24 | X = origin + increment*[0:size(lut(:),1)-1];
25 | Y = lut(:);
26 |
27 | res = reshape(interp1(X, Y, im(:), 'linear', 'extrap'),size(im));
28 |
29 |
--------------------------------------------------------------------------------
/matlab/strred/matlabPyrTools/pwd2path.m:
--------------------------------------------------------------------------------
1 | % PWD2PATH()
2 | %
3 | % add current working directory (pwd) to path.
4 |
5 | P = path;
6 | path(pwd,P);
7 |
--------------------------------------------------------------------------------
/matlab/strred/matlabPyrTools/pyrBand.m:
--------------------------------------------------------------------------------
1 | % RES = pyrBand(PYR, INDICES, BAND_NUM)
2 | %
3 | % Access a subband from a pyramid (gaussian, laplacian, QMF/wavelet,
4 | % or steerable). Subbands are numbered consecutively, from finest
5 | % (highest spatial frequency) to coarsest (lowest spatial frequency).
6 |
7 | % Eero Simoncelli, 6/96.
8 |
9 | function res = pyrBand(pyr, pind, band)
10 |
11 | res = reshape( pyr(pyrBandIndices(pind,band)), pind(band,1), pind(band,2) );
12 |
--------------------------------------------------------------------------------
/matlab/strred/matlabPyrTools/pyrBandIndices.m:
--------------------------------------------------------------------------------
1 | % RES = pyrBandIndices(INDICES, BAND_NUM)
2 | %
3 | % Return indices for accessing a subband from a pyramid
4 | % (gaussian, laplacian, QMF/wavelet, steerable).
5 |
6 | % Eero Simoncelli, 6/96.
7 |
8 | function indices = pyrBandIndices(pind,band)
9 |
10 | if ((band > size(pind,1)) | (band < 1))
11 | error(sprintf('BAND_NUM must be between 1 and number of pyramid bands (%d).', ...
12 | size(pind,1)));
13 | end
14 |
15 | if (size(pind,2) ~= 2)
16 | error('INDICES must be an Nx2 matrix indicating the size of the pyramid subbands');
17 | end
18 |
19 | ind = 1;
20 | for l=1:band-1
21 | ind = ind + prod(pind(l,:));
22 | end
23 |
24 | indices = ind:ind+prod(pind(band,:))-1;
25 |
--------------------------------------------------------------------------------
/matlab/strred/matlabPyrTools/pyrLow.m:
--------------------------------------------------------------------------------
1 | % RES = pyrLow(PYR, INDICES)
2 | %
3 | % Access the lowpass subband from a pyramid
4 | % (gaussian, laplacian, QMF/wavelet, steerable).
5 |
6 | % Eero Simoncelli, 6/96.
7 |
8 | function res = pyrLow(pyr,pind)
9 |
10 | band = size(pind,1);
11 |
12 | res = reshape( pyr(pyrBandIndices(pind,band)), pind(band,1), pind(band,2) );
13 |
--------------------------------------------------------------------------------
/matlab/strred/matlabPyrTools/range2.m:
--------------------------------------------------------------------------------
1 | % [MIN, MAX] = range2(MTX)
2 | %
3 | % Compute minimum and maximum values of MTX, returning them as a 2-vector.
4 |
5 | % Eero Simoncelli, 3/97.
6 |
7 | function [mn, mx] = range2(mtx)
8 |
9 | %% NOTE: THIS CODE IS NOT ACTUALLY USED! (MEX FILE IS CALLED INSTEAD)
10 |
11 | fprintf(1,'WARNING: You should compile the MEX version of "range2.c",\n found in the MEX subdirectory of matlabPyrTools, and put it in your matlab path. It is MUCH faster.\n');
12 |
13 | if (~isreal(mtx))
14 | error('MTX must be real-valued');
15 | end
16 |
17 | mn = min(min(mtx));
18 | mx = max(max(mtx));
19 |
--------------------------------------------------------------------------------
/matlab/strred/matlabPyrTools/rcosFn.m:
--------------------------------------------------------------------------------
1 | % [X, Y] = rcosFn(WIDTH, POSITION, VALUES)
2 | %
3 | % Return a lookup table (suitable for use by INTERP1)
4 | % containing a "raised cosine" soft threshold function:
5 | %
6 | % Y = VALUES(1) + (VALUES(2)-VALUES(1)) *
7 | % cos^2( PI/2 * (X - POSITION + WIDTH)/WIDTH )
8 | %
9 | % WIDTH is the width of the region over which the transition occurs
10 | % (default = 1). POSITION is the location of the center of the
11 | % threshold (default = 0). VALUES (default = [0,1]) specifies the
12 | % values to the left and right of the transition.
13 |
14 | % Eero Simoncelli, 7/96.
15 |
16 | function [X, Y] = rcosFn(width,position,values)
17 |
18 | %------------------------------------------------------------
19 | % OPTIONAL ARGS:
20 |
21 | if (exist('width') ~= 1)
22 | width = 1;
23 | end
24 |
25 | if (exist('position') ~= 1)
26 | position = 0;
27 | end
28 |
29 | if (exist('values') ~= 1)
30 | values = [0,1];
31 | end
32 |
33 | %------------------------------------------------------------
34 |
35 | sz = 256; %% arbitrary!
36 |
37 | X = pi * [-sz-1:1] / (2*sz);
38 |
39 | Y = values(1) + (values(2)-values(1)) * cos(X).^2;
40 |
41 | % Make sure end values are repeated, for extrapolation...
42 | Y(1) = Y(2);
43 | Y(sz+3) = Y(sz+2);
44 |
45 | X = position + (2*width/pi) * (X + pi/4);
46 |
--------------------------------------------------------------------------------
/matlab/strred/matlabPyrTools/reconSpyrLevs.m:
--------------------------------------------------------------------------------
1 | % RES = reconSpyrLevs(PYR,INDICES,LOFILT,BFILTS,EDGES,LEVS,BANDS)
2 | %
3 | % Recursive function for reconstructing levels of a steerable pyramid
4 | % representation. This is called by reconSpyr, and is not usually
5 | % called directly.
6 |
7 | % Eero Simoncelli, 6/96.
8 |
9 | function res = reconSpyrLevs(pyr,pind,lofilt,bfilts,edges,levs,bands);
10 |
11 | nbands = size(bfilts,2);
12 | lo_ind = nbands+1;
13 | res_sz = pind(1,:);
14 |
15 | % Assume square filters:
16 | bfiltsz = round(sqrt(size(bfilts,1)));
17 |
18 | if any(levs > 1)
19 |
20 | if (size(pind,1) > lo_ind)
21 | nres = reconSpyrLevs( pyr(1+sum(prod(pind(1:lo_ind-1,:)')):size(pyr,1)), ...
22 | pind(lo_ind:size(pind,1),:), ...
23 | lofilt, bfilts, edges, levs-1, bands);
24 | else
25 | nres = pyrBand(pyr,pind,lo_ind); % lowpass subband
26 | end
27 |
28 | res = upConv(nres, lofilt, edges, [2 2], [1 1], res_sz);
29 |
30 | else
31 |
32 | res = zeros(res_sz);
33 |
34 | end
35 |
36 | if any(levs == 1)
37 | ind = 1;
38 | for b = 1:nbands
39 | if any(bands == b)
40 | bfilt = reshape(bfilts(:,b), bfiltsz, bfiltsz);
41 | upConv(reshape(pyr(ind:ind+prod(res_sz)-1), res_sz(1), res_sz(2)), ...
42 | bfilt, edges, [1 1], [1 1], res_sz, res);
43 | end
44 | ind = ind + prod(res_sz);
45 | end
46 | end
47 |
--------------------------------------------------------------------------------
/matlab/strred/matlabPyrTools/setPyrBand.m:
--------------------------------------------------------------------------------
1 | % NEWPYR = setPyrBand(PYR, INDICES, BAND, BAND_NUM)
2 | %
3 | % Insert an image (BAND) into a pyramid (gaussian, laplacian, QMF/wavelet,
4 | % or steerable). Subbands are numbered consecutively, from finest
5 | % (highest spatial frequency) to coarsest (lowest spatial frequency).
6 |
7 | % Eero Simoncelli, 1/03.
8 |
9 | function pyr = pyrBand(pyr, pind, band, bandNum)
10 |
11 | %% Check: PIND a valid index matrix?
12 | if ( ~(ndims(pind) == 2) | ~(size(pind,2) == 2) | ~all(pind==round(pind)) )
13 | pind
14 | error('pyrTools:badArg',...
15 | 'PIND argument is not an Nbands X 2 matrix of integers');
16 | end
17 |
18 | %% Check: PIND consistent with size of PYR?
19 | if ( length(pyr) ~= sum(prod(pind,2)) )
20 | error('pyrTools:badPyr',...
21 | 'Pyramid data vector length is inconsistent with index matrix PIND');
22 | end
23 |
24 | %% Check: size of BAND consistent with desired BANDNUM?
25 | if (~all(size(band) == pind(bandNum,:)))
26 | size(band)
27 | pind(bandNum,:)
28 | error('pyrTools:badArg',...
29 | 'size of BAND to be inserted is inconsistent with BAND_NUM');
30 | end
31 |
32 | pyr(pyrBandIndices(pind,bandNum)) = vectify(band);
33 |
--------------------------------------------------------------------------------
/matlab/strred/matlabPyrTools/shift.m:
--------------------------------------------------------------------------------
1 | % [RES] = shift(MTX, OFFSET)
2 | %
3 | % Circular shift 2D matrix samples by OFFSET (a [Y,X] 2-vector),
4 | % such that RES(POS) = MTX(POS-OFFSET).
5 |
6 | function res = shift(mtx, offset)
7 |
8 | dims = size(mtx);
9 |
10 | offset = mod(-offset,dims);
11 |
12 | res = [ mtx(offset(1)+1:dims(1), offset(2)+1:dims(2)), ...
13 | mtx(offset(1)+1:dims(1), 1:offset(2)); ...
14 | mtx(1:offset(1), offset(2)+1:dims(2)), ...
15 | mtx(1:offset(1), 1:offset(2)) ];
16 |
--------------------------------------------------------------------------------
/matlab/strred/matlabPyrTools/simulate.m:
--------------------------------------------------------------------------------
1 | clear all; close all; clc
2 | path('D:\GSM\matlabPyrTools\',path);
3 | im = pgmRead('einstein.pgm');
4 | Nsc = 4; Nor = 3;
5 | [pyr,pind] = buildSFpyr(im,Nsc,Nor);
6 | nband = 2;
7 | aux = pyrBand(pyr, pind, nband);
--------------------------------------------------------------------------------
/matlab/strred/matlabPyrTools/skew2.m:
--------------------------------------------------------------------------------
1 | % S = SKEW2(MTX,MEAN,VAR)
2 | %
3 | % Sample skew (third moment divided by variance^3/2) of a matrix.
4 | % MEAN (optional) and VAR (optional) make the computation faster.
5 |
6 | function res = skew2(mtx, mn, v)
7 |
8 | if (exist('mn') ~= 1)
9 | mn = mean2(mtx);
10 | end
11 |
12 | if (exist('v') ~= 1)
13 | v = var2(mtx,mn);
14 | end
15 |
16 | if (isreal(mtx))
17 | res = mean(mean((mtx-mn).^3)) / (v^(3/2));
18 | else
19 | res = mean(mean(real(mtx-mn).^3)) / (real(v)^(3/2)) + ...
20 | i * mean(mean(imag(mtx-mn).^3)) / (imag(v)^(3/2));
21 | end
22 |
--------------------------------------------------------------------------------
/matlab/strred/matlabPyrTools/spyrBand.m:
--------------------------------------------------------------------------------
1 | % [LEV,IND] = spyrBand(PYR,INDICES,LEVEL,BAND)
2 | %
3 | % Access a band from a steerable pyramid.
4 | %
5 | % LEVEL indicates the scale (finest = 1, coarsest = spyrHt(INDICES)).
6 | %
7 | % BAND (optional, default=1) indicates which subband
8 | % (1 = vertical, rest proceeding anti-clockwise).
9 |
10 | % Eero Simoncelli, 6/96.
11 |
12 | function res = spyrBand(pyr,pind,level,band)
13 |
14 | if (exist('level') ~= 1)
15 | level = 1;
16 | end
17 |
18 | if (exist('band') ~= 1)
19 | band = 1;
20 | end
21 |
22 | nbands = spyrNumBands(pind);
23 | if ((band > nbands) | (band < 1))
24 | error(sprintf('Bad band number (%d) should be in range [1,%d].', band, nbands));
25 | end
26 |
27 | maxLev = spyrHt(pind);
28 | if ((level > maxLev) | (level < 1))
29 | error(sprintf('Bad level number (%d), should be in range [1,%d].', level, maxLev));
30 | end
31 |
32 | firstband = 1 + band + nbands*(level-1);
33 | res = pyrBand(pyr, pind, firstband);
34 |
35 |
--------------------------------------------------------------------------------
/matlab/strred/matlabPyrTools/spyrHigh.m:
--------------------------------------------------------------------------------
1 | % RES = spyrHigh(PYR, INDICES)
2 | %
3 | % Access the highpass residual band from a steerable pyramid.
4 |
5 | % Eero Simoncelli, 6/96.
6 |
7 | function res = spyrHigh(pyr,pind)
8 |
9 | res = pyrBand(pyr, pind, 1);
10 |
11 |
--------------------------------------------------------------------------------
/matlab/strred/matlabPyrTools/spyrHt.m:
--------------------------------------------------------------------------------
1 | % [HEIGHT] = spyrHt(INDICES)
2 | %
3 | % Compute height of steerable pyramid with given index matrix.
4 |
5 | % Eero Simoncelli, 6/96.
6 |
7 | function [ht] = spyrHt(pind)
8 |
9 | nbands = spyrNumBands(pind);
10 |
11 | % Don't count lowpass, or highpass residual bands
12 | if (size(pind,1) > 2)
13 | ht = (size(pind,1)-2)/nbands;
14 | else
15 | ht = 0;
16 | end
17 |
--------------------------------------------------------------------------------
/matlab/strred/matlabPyrTools/spyrLev.m:
--------------------------------------------------------------------------------
1 | % [LEV,IND] = spyrLev(PYR,INDICES,LEVEL)
2 | %
3 | % Access a level from a steerable pyramid.
4 | % Return as an SxB matrix, B = number of bands, S = total size of a band.
5 | % Also returns an Bx2 matrix containing dimensions of the subbands.
6 |
7 | % Eero Simoncelli, 6/96.
8 |
9 | function [lev,ind] = spyrLev(pyr,pind,level)
10 |
11 | nbands = spyrNumBands(pind);
12 |
13 | if ((level > spyrHt(pind)) | (level < 1))
14 | error(sprintf('Level number must be in the range [1, %d].', spyrHt(pind)));
15 | end
16 |
17 | firstband = 2 + nbands*(level-1);
18 | firstind = 1;
19 | for l=1:firstband-1
20 | firstind = firstind + prod(pind(l,:));
21 | end
22 |
23 | ind = pind(firstband:firstband+nbands-1,:);
24 | lev = pyr(firstind:firstind+sum(prod(ind'))-1);
25 |
--------------------------------------------------------------------------------
/matlab/strred/matlabPyrTools/spyrNumBands.m:
--------------------------------------------------------------------------------
1 | % [NBANDS] = spyrNumBands(INDICES)
2 | %
3 | % Compute number of orientation bands in a steerable pyramid with
4 | % given index matrix. If the pyramid contains only the highpass and
5 | % lowpass bands (i.e., zero levels), returns 0.
6 |
7 | % Eero Simoncelli, 2/97.
8 |
9 | function [nbands] = spyrNumBands(pind)
10 |
11 | if (size(pind,1) == 2)
12 | nbands = 0;
13 | else
14 | % Count number of orientation bands:
15 | b = 3;
16 | while ((b <= size(pind,1)) & all( pind(b,:) == pind(2,:)) )
17 | b = b+1;
18 | end
19 | nbands = b-2;
20 | end
21 |
--------------------------------------------------------------------------------
/matlab/strred/matlabPyrTools/subMtx.m:
--------------------------------------------------------------------------------
1 | % MTX = subMtx(VEC, DIMENSIONS, START_INDEX)
2 | %
3 | % Reshape a portion of VEC starting from START_INDEX (optional,
4 | % default=1) to the given dimensions.
5 |
6 | % Eero Simoncelli, 6/96.
7 |
8 | function mtx = subMtx(vec, sz, offset)
9 |
10 | if (exist('offset') ~= 1)
11 | offset = 1;
12 | end
13 |
14 | vec = vec(:);
15 | sz = sz(:);
16 |
17 | if (size(sz,1) ~= 2)
18 | error('DIMENSIONS must be a 2-vector.');
19 | end
20 |
21 | mtx = reshape( vec(offset:offset+prod(sz)-1), sz(1), sz(2) );
22 |
--------------------------------------------------------------------------------
/matlab/strred/matlabPyrTools/var2.m:
--------------------------------------------------------------------------------
1 | % V = VAR2(MTX,MEAN)
2 | %
3 | % Sample variance of a matrix.
4 | % Passing MEAN (optional) makes the calculation faster.
5 |
6 | function res = var2(mtx, mn)
7 |
8 | if (exist('mn') ~= 1)
9 | mn = mean2(mtx);
10 | end
11 |
12 | if (isreal(mtx))
13 | res = sum(sum(abs(mtx-mn).^2)) / max((prod(size(mtx)) - 1),1);
14 | else
15 | res = sum(sum(real(mtx-mn).^2)) + i*sum(sum(imag(mtx-mn).^2));
16 | res = res / max((prod(size(mtx)) - 1),1);
17 | end
18 |
--------------------------------------------------------------------------------
/matlab/strred/matlabPyrTools/vectify.m:
--------------------------------------------------------------------------------
1 | % [VEC] = columnize(MTX)
2 | %
3 | % Pack elements of MTX into a column vector. Just provides a
4 | % function-call notatoin for the operation MTX(:)
5 |
6 | function vec = columnize(mtx)
7 |
8 | vec = mtx(:);
9 |
--------------------------------------------------------------------------------
/matlab/strred/matlabPyrTools/wpyrBand.m:
--------------------------------------------------------------------------------
1 | % RES = wpyrBand(PYR, INDICES, LEVEL, BAND)
2 | %
3 | % Access a subband from a separable QMF/wavelet pyramid.
4 | %
5 | % LEVEL (optional, default=1) indicates the scale (finest = 1,
6 | % coarsest = wpyrHt(INDICES)).
7 | %
8 | % BAND (optional, default=1) indicates which subband (1=horizontal,
9 | % 2=vertical, 3=diagonal).
10 |
11 | % Eero Simoncelli, 6/96.
12 |
13 | function im = wpyrBand(pyr,pind,level,band)
14 |
15 | if (exist('level') ~= 1)
16 | level = 1;
17 | end
18 |
19 | if (exist('band') ~= 1)
20 | band = 1;
21 | end
22 |
23 | if ((pind(1,1) == 1) | (pind(1,2) ==1))
24 | nbands = 1;
25 | else
26 | nbands = 3;
27 | end
28 |
29 | if ((band > nbands) | (band < 1))
30 | error(sprintf('Bad band number (%d) should be in range [1,%d].', band, nbands));
31 | end
32 |
33 | maxLev = wpyrHt(pind);
34 | if ((level > maxLev) | (level < 1))
35 | error(sprintf('Bad level number (%d), should be in range [1,%d].', level, maxLev));
36 | end
37 |
38 | band = band + nbands*(level-1);
39 | im = pyrBand(pyr,pind,band);
40 |
--------------------------------------------------------------------------------
/matlab/strred/matlabPyrTools/wpyrHt.m:
--------------------------------------------------------------------------------
1 | % [HEIGHT] = wpyrHt(INDICES)
2 | %
3 | % Compute height of separable QMF/wavelet pyramid with given index matrix.
4 |
5 | % Eero Simoncelli, 6/96.
6 |
7 | function [ht] = wpyrHt(pind)
8 |
9 | if ((pind(1,1) == 1) | (pind(1,2) ==1))
10 | nbands = 1;
11 | else
12 | nbands = 3;
13 | end
14 |
15 | ht = (size(pind,1)-1)/nbands;
16 |
--------------------------------------------------------------------------------
/matlab/strred/matlabPyrTools/wpyrLev.m:
--------------------------------------------------------------------------------
1 | % [LEV,IND] = wpyrLev(PYR,INDICES,LEVEL)
2 | %
3 | % Access a level from a separable QMF/wavelet pyramid.
4 | % Return as an SxB matrix, B = number of bands, S = total size of a band.
5 | % Also returns an Bx2 matrix containing dimensions of the subbands.
6 |
7 | % Eero Simoncelli, 6/96.
8 |
9 | function [lev,ind] = wpyrLev(pyr,pind,level)
10 |
11 | if ((pind(1,1) == 1) | (pind(1,2) ==1))
12 | nbands = 1;
13 | else
14 | nbands = 3;
15 | end
16 |
17 | if ((level > wpyrHt(pind)) | (level < 1))
18 | error(sprintf('Level number must be in the range [1, %d].', wpyrHt(pind)));
19 | end
20 |
21 | firstband = 1 + nbands*(level-1)
22 | firstind = 1;
23 | for l=1:firstband-1
24 | firstind = firstind + prod(pind(l,:));
25 | end
26 |
27 |
28 | ind = pind(firstband:firstband+nbands-1,:);
29 | lev = pyr(firstind:firstind+sum(prod(ind'))-1);
30 |
31 |
--------------------------------------------------------------------------------
/matlab/strred/matlabPyrTools/zconv2.m:
--------------------------------------------------------------------------------
1 | % RES = ZCONV2(MTX1, MTX2, CTR)
2 | %
3 | % Convolution of two matrices, with boundaries handled as if the larger mtx
4 | % lies in a sea of zeros. Result will be of size of LARGER vector.
5 | %
6 | % The origin of the smaller matrix is assumed to be its center.
7 | % For even dimensions, the origin is determined by the CTR (optional)
8 | % argument:
9 | % CTR origin
10 | % 0 DIM/2 (default)
11 | % 1 (DIM/2)+1 (behaves like conv2(mtx1,mtx2,'same'))
12 |
13 | % Eero Simoncelli, 2/97.
14 |
15 | function c = zconv2(a,b,ctr)
16 |
17 | if (exist('ctr') ~= 1)
18 | ctr = 0;
19 | end
20 |
21 | if (( size(a,1) >= size(b,1) ) & ( size(a,2) >= size(b,2) ))
22 | large = a; small = b;
23 | elseif (( size(a,1) <= size(b,1) ) & ( size(a,2) <= size(b,2) ))
24 | large = b; small = a;
25 | else
26 | error('one arg must be larger than the other in both dimensions!');
27 | end
28 |
29 | ly = size(large,1);
30 | lx = size(large,2);
31 | sy = size(small,1);
32 | sx = size(small,2);
33 |
34 | %% These values are the index of the small mtx that falls on the
35 | %% border pixel of the large matrix when computing the first
36 | %% convolution response sample:
37 | sy2 = floor((sy+ctr+1)/2);
38 | sx2 = floor((sx+ctr+1)/2);
39 |
40 | clarge = conv2(large,small);
41 | c = clarge(sy2:ly+sy2-1, sx2:lx+sx2-1);
42 |
--------------------------------------------------------------------------------
/matlab/strred/run_strred.m:
--------------------------------------------------------------------------------
1 | function run_strred(ref_filename, dis_filename, width, height)
2 |
3 | path(path,'./strred');
4 | path(path,'./matlabPyrTools');
5 |
6 | calcStrredScore(ref_filename, dis_filename, height, width);
7 |
8 | % dmos_score = rred2dmos(strred_score)
9 |
10 | end
11 |
12 |
13 |
14 |
15 |
16 |
17 |
18 |
19 |
20 |
21 |
22 |
23 |
24 |
25 |
26 |
27 |
28 |
29 |
30 |
31 |
32 |
33 |
34 |
35 |
--------------------------------------------------------------------------------
/matlab/strred/run_strred_opt.m:
--------------------------------------------------------------------------------
1 | function run_strred_opt(ref_filename, dis_filename, width, height)
2 |
3 | path(path, './strred');
4 | path(path, './matlabPyrTools');
5 |
6 | calcStrredScore_opt(ref_filename, dis_filename, height, width);
7 |
8 | end
9 |
10 |
11 |
12 |
13 |
--------------------------------------------------------------------------------
/matlab/strred/strred/calcStrredScore.m:
--------------------------------------------------------------------------------
1 | function calcStrredScore(rname,dname,rows,colms)
2 |
3 | rfid = fopen(rname);
4 | dfid = fopen(dname);
5 |
6 | srred = [];
7 | trred = [];
8 |
9 | iframe = 0;
10 | while 1
11 |
12 | [yr, cbr, crr] = readframefromfid(rfid, rows, colms);
13 | [yd, cbr, crr] = readframefromfid(dfid, rows, colms);
14 |
15 | if feof(rfid) || feof(dfid)
16 | break;
17 | end
18 |
19 | % read successful, can then reshape
20 | yr = reshape(yr, rows, colms)';
21 | yd = reshape(yd, rows, colms)';
22 |
23 | if iframe > 0
24 | [spatial_ref temporal_ref] = extract_info(yr, yr_prev);
25 | [spatial_dis temporal_dis] = extract_info(yd, yd_prev);
26 | srred_now = mean2(abs(spatial_ref - spatial_dis));
27 | trred_now = mean2(abs(temporal_ref - temporal_dis));
28 | srred = [srred srred_now];
29 | trred = [trred trred_now];
30 | end
31 |
32 | yr_prev = yr;
33 | yd_prev = yd;
34 | iframe = iframe + 1;
35 |
36 | end
37 |
38 | fclose(rfid);
39 | fclose(dfid);
40 |
41 | srred = [srred(1) srred];
42 | trred = [trred(1) trred];
43 |
44 | for frame_ind = 0 : iframe - 1
45 |
46 | disp(sprintf('srred: %d %f', frame_ind, srred(frame_ind + 1)));
47 | disp(sprintf('trred: %d %f', frame_ind, trred(frame_ind + 1)));
48 |
49 | end;
50 |
51 | end
--------------------------------------------------------------------------------
/matlab/strred/strred/calcStrredScore_opt.m:
--------------------------------------------------------------------------------
1 | function calcStrredScore_opt(rname, dname, rows, colms)
2 |
3 | band = 4;
4 | Nscales = 5;
5 | Nor = 6;
6 | blk = 3;
7 | sigma_nsq = 0.1;
8 |
9 | srred = [];
10 | trred = [];
11 |
12 | rfid = fopen(rname);
13 | dfid = fopen(dname);
14 |
15 | iframe = 0;
16 | while 1
17 |
18 | [yr, ~, ~] = readframefromfid(rfid, rows, colms);
19 | [yd, ~, ~] = readframefromfid(dfid, rows, colms);
20 |
21 | if feof(rfid) || feof(dfid)
22 | break;
23 | end
24 |
25 | % read successful, can then reshape
26 | yr = reshape(yr, [colms rows])';
27 | yd = reshape(yd, [colms rows])';
28 |
29 | if iframe > 0
30 | [srred_now, ~, trred_now, ~] = extract_info_opt(yr, yr_prev, yd, ...
31 | yd_prev, band, Nscales, Nor, ...
32 | blk, sigma_nsq);
33 | srred = [srred srred_now];
34 | trred = [trred trred_now];
35 | end
36 |
37 | yr_prev = yr;
38 | yd_prev = yd;
39 | iframe = iframe + 1;
40 |
41 | end
42 |
43 | fclose(rfid);
44 | fclose(dfid);
45 |
46 | srred = [srred(1) srred];
47 | trred = [trred(1) trred];
48 |
49 | for frame_ind = 0 : iframe - 1
50 |
51 | disp(sprintf('srred: %d %f', frame_ind, srred(frame_ind + 1)));
52 | disp(sprintf('trred: %d %f', frame_ind, trred(frame_ind + 1)));
53 |
54 | end;
55 |
56 | end
--------------------------------------------------------------------------------
/matlab/strred/strred/ind2wtree.m:
--------------------------------------------------------------------------------
1 | function wtree = ind2wtree(pyr, ind)
2 |
3 | %this function is called by vifvec.m
4 | % converts the output of Eero Simoncelli's pyramid routines into subbands in a cell array
5 | C=pyr;
6 | S=ind;
7 |
8 | offset=0;
9 | numsubs=size(ind,1);
10 | for i=1:numsubs
11 | wtree{numsubs-i+1}=reshape(C(offset+1:offset+prod(S(i,:))), S(i,1),S(i,2));
12 | offset=offset+prod(S(i,:));
13 | end
14 |
--------------------------------------------------------------------------------
/matlab/strred/strred/readframefromfid.m:
--------------------------------------------------------------------------------
1 | function [y,cb,cr]=readframefromfid(fid,height,width)
2 |
3 | % for now, read yuv420p only
4 |
5 | y=fread(fid,width*height, 'uchar')';
6 | cb=fread(fid,width*height/4, 'uchar')';
7 | cr=fread(fid,width*height/4, 'uchar')';
8 |
9 | end
--------------------------------------------------------------------------------
/matlab/strred/strred/rred2dmos.m:
--------------------------------------------------------------------------------
1 | function dmos=rred2dmos(rred)
2 | dmos=16.4769+9.7111*log(1+rred/0.6444);
--------------------------------------------------------------------------------
/matlab/strred/workspace/.gitignore:
--------------------------------------------------------------------------------
1 | # Ignore everything in this directory
2 | *
3 | # Except this file
4 | !.gitignore
5 |
--------------------------------------------------------------------------------
/model/other_models/nflx_v1.pkl:
--------------------------------------------------------------------------------
1 | (dp0
2 | S'param_dict'
3 | p1
4 | (dp2
5 | S'C'
6 | p3
7 | F1.0
8 | sS'norm_type'
9 | p4
10 | S'clip_0to1'
11 | p5
12 | sS'score_clip'
13 | p6
14 | (lp7
15 | F0.0
16 | aF100.0
17 | asS'cache_size'
18 | p8
19 | I200
20 | sS'nu'
21 | p9
22 | F0.5
23 | sS'gamma'
24 | p10
25 | F0.85
26 | ssS'model_dict'
27 | p11
28 | (dp12
29 | g4
30 | S'linear_rescale'
31 | p13
32 | sg6
33 | g7
34 | sS'feature_names'
35 | p14
36 | (lp15
37 | S'VMAF_feature_adm_score'
38 | p16
39 | aS'VMAF_feature_ansnr_score'
40 | p17
41 | aS'VMAF_feature_motion_score'
42 | p18
43 | aS'VMAF_feature_vif_score'
44 | p19
45 | asS'intercepts'
46 | p20
47 | (lp21
48 | F-0.1909090909090909
49 | aF-1.635828565827225
50 | aF-0.5027725296167747
51 | aF-0.022214587359292954
52 | aF-0.12191917348723096
53 | asS'model_type'
54 | p22
55 | S'LIBSVMNUSVR'
56 | p23
57 | sS'slopes'
58 | p24
59 | (lp25
60 | F0.010909090909090908
61 | aF2.635828565827225
62 | aF0.030306790717580585
63 | aF0.06846153126171134
64 | aF1.121919173487231
65 | asS'model'
66 | p26
67 | Nss.
--------------------------------------------------------------------------------
/model/other_models/nflx_vmaff_rf_v2.pkl:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/Netflix/vmaf/b9ac69e6c4231fad0465021f9e31a841a18261db/model/other_models/nflx_vmaff_rf_v2.pkl
--------------------------------------------------------------------------------
/model/other_models/nflxall_libsvmnusvr_currentbest.pkl:
--------------------------------------------------------------------------------
1 | (dp0
2 | S'param_dict'
3 | p1
4 | (dp2
5 | S'norm_type'
6 | p3
7 | S'clip_0to1'
8 | p4
9 | sS'score_clip'
10 | p5
11 | (lp6
12 | F0.0
13 | aF100.0
14 | asS'C'
15 | p7
16 | F3.1
17 | sS'nu'
18 | p8
19 | F0.9
20 | sS'gamma'
21 | p9
22 | F0.1
23 | ssS'model_dict'
24 | p10
25 | (dp11
26 | S'feature_dict'
27 | p12
28 | (dp13
29 | S'VMAF_feature'
30 | p14
31 | (lp15
32 | S'vif'
33 | p16
34 | aS'adm'
35 | p17
36 | aS'motion'
37 | p18
38 | aS'ansnr'
39 | p19
40 | assg3
41 | S'linear_rescale'
42 | p20
43 | sg5
44 | g6
45 | sS'feature_names'
46 | p21
47 | (lp22
48 | S'VMAF_feature_adm_score'
49 | p23
50 | aS'VMAF_feature_ansnr_score'
51 | p24
52 | aS'VMAF_feature_motion_score'
53 | p25
54 | aS'VMAF_feature_vif_score'
55 | p26
56 | asS'intercepts'
57 | p27
58 | (lp28
59 | F-0.14912280701754385
60 | aF-1.635828565827225
61 | aF-0.5027725296167747
62 | aF-0.017141728475754268
63 | aF-0.12191917348723096
64 | asS'model_type'
65 | p29
66 | S'LIBSVMNUSVR'
67 | p30
68 | sS'model'
69 | p31
70 | NsS'slopes'
71 | p32
72 | (lp33
73 | F0.010526315789473684
74 | aF2.635828565827225
75 | aF0.030306790717580585
76 | aF0.05282785410063858
77 | aF1.121919173487231
78 | ass.
--------------------------------------------------------------------------------
/model/other_models/nflxall_vmafv1.pkl:
--------------------------------------------------------------------------------
1 | (dp0
2 | S'param_dict'
3 | p1
4 | (dp2
5 | S'norm_type'
6 | p3
7 | S'clip_0to1'
8 | p4
9 | sS'score_clip'
10 | p5
11 | (lp6
12 | F0.0
13 | aF100.0
14 | asS'C'
15 | p7
16 | F3.1
17 | sS'nu'
18 | p8
19 | F0.9
20 | sS'gamma'
21 | p9
22 | F0.1
23 | ssS'model_dict'
24 | p10
25 | (dp11
26 | S'feature_dict'
27 | p12
28 | (dp13
29 | S'VMAF_feature'
30 | p14
31 | (lp15
32 | S'vif'
33 | p16
34 | aS'adm'
35 | p17
36 | aS'motion'
37 | p18
38 | aS'ansnr'
39 | p19
40 | assg3
41 | S'linear_rescale'
42 | p20
43 | sg5
44 | g6
45 | sS'feature_names'
46 | p21
47 | (lp22
48 | S'VMAF_feature_adm_score'
49 | p23
50 | aS'VMAF_feature_ansnr_score'
51 | p24
52 | aS'VMAF_feature_motion_score'
53 | p25
54 | aS'VMAF_feature_vif_score'
55 | p26
56 | asS'intercepts'
57 | p27
58 | (lp28
59 | F-0.14912280701754385
60 | aF-1.635828565827225
61 | aF-0.5027725296167747
62 | aF-0.017141728475754268
63 | aF-0.12191917348723096
64 | asS'model_type'
65 | p29
66 | S'LIBSVMNUSVR'
67 | p30
68 | sS'model'
69 | p31
70 | NsS'slopes'
71 | p32
72 | (lp33
73 | F0.010526315789473684
74 | aF2.635828565827225
75 | aF0.030306790717580585
76 | aF0.05282785410063858
77 | aF1.121919173487231
78 | ass.
--------------------------------------------------------------------------------
/model/other_models/nflxtrain_libsvmnusvr_currentbest.pkl:
--------------------------------------------------------------------------------
1 | (dp0
2 | S'param_dict'
3 | p1
4 | (dp2
5 | S'norm_type'
6 | p3
7 | S'clip_0to1'
8 | p4
9 | sS'score_clip'
10 | p5
11 | (lp6
12 | F0.0
13 | aF100.0
14 | asS'C'
15 | p7
16 | F3.1
17 | sS'nu'
18 | p8
19 | F0.9
20 | sS'gamma'
21 | p9
22 | F0.1
23 | ssS'model_dict'
24 | p10
25 | (dp11
26 | S'feature_dict'
27 | p12
28 | (dp13
29 | S'VMAF_feature'
30 | p14
31 | (lp15
32 | S'vif'
33 | p16
34 | aS'adm'
35 | p17
36 | aS'motion'
37 | p18
38 | aS'ansnr'
39 | p19
40 | assg3
41 | S'linear_rescale'
42 | p20
43 | sg5
44 | g6
45 | sS'feature_names'
46 | p21
47 | (lp22
48 | S'VMAF_feature_adm_score'
49 | p23
50 | aS'VMAF_feature_ansnr_score'
51 | p24
52 | aS'VMAF_feature_motion_score'
53 | p25
54 | aS'VMAF_feature_vif_score'
55 | p26
56 | asS'intercepts'
57 | p27
58 | (lp28
59 | F-0.1909090909090909
60 | aF-1.635828565827225
61 | aF-0.5027725296167747
62 | aF-0.022214587359292954
63 | aF-0.12191917348723096
64 | asS'model_type'
65 | p29
66 | S'LIBSVMNUSVR'
67 | p30
68 | sS'model'
69 | p31
70 | NsS'slopes'
71 | p32
72 | (lp33
73 | F0.010909090909090908
74 | aF2.635828565827225
75 | aF0.030306790717580585
76 | aF0.06846153126171134
77 | aF1.121919173487231
78 | ass.
--------------------------------------------------------------------------------
/model/other_models/nflxtrain_norm_type_none.pkl:
--------------------------------------------------------------------------------
1 | (dp0
2 | S'param_dict'
3 | p1
4 | (dp2
5 | S'C'
6 | p3
7 | F4.0
8 | sS'norm_type'
9 | p4
10 | S'none'
11 | p5
12 | sS'score_clip'
13 | p6
14 | (lp7
15 | F0.0
16 | aF100.0
17 | asS'custom_clip_0to1_map'
18 | p8
19 | (dp9
20 | S'VMAF_feature_adm_scale0_score'
21 | p10
22 | (lp11
23 | F0.0
24 | aF0.5
25 | assS'nu'
26 | p12
27 | F0.9
28 | sS'gamma'
29 | p13
30 | F0.05
31 | ssS'model_dict'
32 | p14
33 | (dp15
34 | g4
35 | g5
36 | sg6
37 | g7
38 | sS'feature_names'
39 | p16
40 | (lp17
41 | S'VMAF_feature_adm2_score'
42 | p18
43 | aS'VMAF_feature_motion_score'
44 | p19
45 | aS'VMAF_feature_vif_scale0_score'
46 | p20
47 | aS'VMAF_feature_vif_scale1_score'
48 | p21
49 | aS'VMAF_feature_vif_scale2_score'
50 | p22
51 | aS'VMAF_feature_vif_scale3_score'
52 | p23
53 | asS'model_type'
54 | p24
55 | S'LIBSVMNUSVR'
56 | p25
57 | sS'model'
58 | p26
59 | NsS'feature_dict'
60 | p27
61 | (dp28
62 | S'VMAF_feature'
63 | p29
64 | (lp30
65 | S'vif_scale0'
66 | p31
67 | aS'vif_scale1'
68 | p32
69 | aS'vif_scale2'
70 | p33
71 | aS'vif_scale3'
72 | p34
73 | aS'adm2'
74 | p35
75 | aS'motion'
76 | p36
77 | asss.
--------------------------------------------------------------------------------
/model/other_models/nflxtrain_vmafv1.pkl:
--------------------------------------------------------------------------------
1 | (dp0
2 | S'param_dict'
3 | p1
4 | (dp2
5 | S'norm_type'
6 | p3
7 | S'clip_0to1'
8 | p4
9 | sS'score_clip'
10 | p5
11 | (lp6
12 | F0.0
13 | aF100.0
14 | asS'C'
15 | p7
16 | F3.1
17 | sS'nu'
18 | p8
19 | F0.9
20 | sS'gamma'
21 | p9
22 | F0.1
23 | ssS'model_dict'
24 | p10
25 | (dp11
26 | S'feature_dict'
27 | p12
28 | (dp13
29 | S'VMAF_feature'
30 | p14
31 | (lp15
32 | S'vif'
33 | p16
34 | aS'adm'
35 | p17
36 | aS'motion'
37 | p18
38 | aS'ansnr'
39 | p19
40 | assg3
41 | S'linear_rescale'
42 | p20
43 | sg5
44 | g6
45 | sS'feature_names'
46 | p21
47 | (lp22
48 | S'VMAF_feature_adm_score'
49 | p23
50 | aS'VMAF_feature_ansnr_score'
51 | p24
52 | aS'VMAF_feature_motion_score'
53 | p25
54 | aS'VMAF_feature_vif_score'
55 | p26
56 | asS'intercepts'
57 | p27
58 | (lp28
59 | F-0.1909090909090909
60 | aF-1.635828565827225
61 | aF-0.5027725296167747
62 | aF-0.022214587359292954
63 | aF-0.12191917348723096
64 | asS'model_type'
65 | p29
66 | S'LIBSVMNUSVR'
67 | p30
68 | sS'model'
69 | p31
70 | NsS'slopes'
71 | p32
72 | (lp33
73 | F0.010909090909090908
74 | aF2.635828565827225
75 | aF0.030306790717580585
76 | aF0.06846153126171134
77 | aF1.121919173487231
78 | ass.
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/model/other_models/niqe_v0.1.pkl:
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https://raw.githubusercontent.com/Netflix/vmaf/b9ac69e6c4231fad0465021f9e31a841a18261db/model/other_models/niqe_v0.1.pkl
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/model/vmaf_float_v0.6.1neg.pkl:
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https://raw.githubusercontent.com/Netflix/vmaf/b9ac69e6c4231fad0465021f9e31a841a18261db/model/vmaf_float_v0.6.1neg.pkl
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/python/.gitignore:
--------------------------------------------------------------------------------
1 | vmaf/externals.py
2 | test/resource/icpf
3 | test/resource/mp4
4 | test/resource/test_image_yuv
5 | test/resource/test_images
6 | test/resource/yuv
7 | test/resource/tiff
8 | test/resource/y4m
9 | adm_dwt2_cy.c*
10 |
--------------------------------------------------------------------------------
/python/DEVELOP.md:
--------------------------------------------------------------------------------
1 | # Development
2 |
3 | ## Testing
4 |
5 | A `tox.ini` was added to provide unit tests. Before running tests using tox, be sure to first run `make` under the root directory.
6 |
7 | Run:
8 |
9 | ```
10 | tox
11 | ```
12 |
13 | to run all tests.
14 |
15 | ## Test coverage
16 |
17 | If you run `tox`, a summary test coverage report will be shown in terminal,
18 | you can also see a full HTML report by looking at `.tox/coverage/index.html`.
19 |
20 | This report can be useful to spot any key part of the code that was not exercised (and thus possibly likely to fail under python3)
21 |
--------------------------------------------------------------------------------
/python/README.rst:
--------------------------------------------------------------------------------
1 | VMAF - Video Multimethod Assessment Fusion
2 | ==========================================
3 |
4 | .. image:: https://travis-ci.org/Netflix/vmaf.svg?branch=master
5 | :target: https://travis-ci.org/Netflix/vmaf
6 | :alt: Travis Build Status
7 |
8 | .. image:: https://ci.appveyor.com/api/projects/status/68i57b8ssasttngg?svg=true
9 | :target: https://ci.appveyor.com/project/li-zhi/vmaf
10 | :alt: AppVeyor Build Status
11 |
12 | VMAF is a perceptual video quality assessment algorithm developed by Netflix.
13 |
14 | VMAF Development Kit (VDK) is a software package that contains the VMAF algorithm implementation,
15 | as well as a set of tools that allows a user to train and test a custom VMAF model.
16 |
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/python/pyproject.toml:
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1 | [build-system]
2 | requires = ["setuptools", "wheel", "Cython", "numpy"]
3 |
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/python/requirements.txt:
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1 | numpy>=1.18.2,<2.0.0
2 | scipy>=1.4.1
3 | matplotlib>=3.2.1
4 | pandas>=1.0.3
5 | scikit-learn>=0.22.2
6 | scikit-image>=0.16.2
7 | h5py>=2.6.0
8 | sureal>=0.4.2
9 | dill>=0.3.1
10 | PyWavelets>=1.1.1
11 | python-slugify>=5.0.0
12 | libsvm-official>=3.30,<=3.32
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/python/test/__init__.py:
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https://raw.githubusercontent.com/Netflix/vmaf/b9ac69e6c4231fad0465021f9e31a841a18261db/python/test/__init__.py
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/python/test/conftest.py:
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1 | import pytest
2 |
3 |
4 | def pytest_collection_modifyitems(items):
5 | """
6 | Dynamically mark tests based on their file name:
7 | - *_test.py: main test (always exercise)
8 | - *_extratest.py: exercised only when testing with ffmpeg
9 | - *_libtest.py: exercised only to test testlib
10 | """
11 | for item in items:
12 | item.add_marker(pytest.mark.main)
13 |
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/python/test/doctest_test.py:
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1 | __copyright__ = "Copyright 2016-2020, Netflix, Inc."
2 | __license__ = "BSD+Patent"
3 |
4 | """
5 | Run embedded doctests
6 | """
7 |
8 | import doctest
9 |
10 | from vmaf.tools import misc
11 | # from vmaf.tools import stats
12 | from vmaf.core import quality_runner
13 | from vmaf.core import train_test_model
14 |
15 | def load_tests(loader, tests, ignore):
16 | tests.addTests(doctest.DocTestSuite(misc))
17 | # tests.addTests(doctest.DocTestSuite(stats)) # commented out because not numerically exact
18 | tests.addTests(doctest.DocTestSuite(quality_runner))
19 | tests.addTests(doctest.DocTestSuite(train_test_model))
20 | return tests
21 |
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/python/test/requirements.txt:
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1 | pytest-cov
2 |
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/python/test/resource/data_Toyama.mat:
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https://raw.githubusercontent.com/Netflix/vmaf/b9ac69e6c4231fad0465021f9e31a841a18261db/python/test/resource/data_Toyama.mat
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/python/test/resource/dataset_sample.py:
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1 | dataset_name = 'example'
2 |
3 | yuv_fmt = 'yuv420p'
4 | width = 1920
5 | height = 1080
6 |
7 | from vmaf.config import VmafConfig
8 |
9 | ref_videos = [
10 | {'content_id': 0, 'path': VmafConfig.test_resource_path('yuv', 'checkerboard_1920_1080_10_3_0_0.yuv')},
11 |
12 | {'content_id': 1, 'path': VmafConfig.test_resource_path('yuv', 'flat_1920_1080_0.yuv')},
13 | ]
14 |
15 | dis_videos = [
16 | {'content_id': 0, 'asset_id': 0, 'dmos': 100, 'path': VmafConfig.test_resource_path('yuv', 'checkerboard_1920_1080_10_3_0_0.yuv')}, # ref
17 | {'content_id': 0, 'asset_id': 1, 'dmos': 50, 'path': VmafConfig.test_resource_path('yuv', 'checkerboard_1920_1080_10_3_1_0.yuv')},
18 |
19 | {'content_id': 1, 'asset_id': 2, 'dmos': 100, 'path': VmafConfig.test_resource_path('yuv', 'flat_1920_1080_0.yuv')}, # ref
20 | {'content_id': 1, 'asset_id': 3, 'dmos': 80, 'path': VmafConfig.test_resource_path('yuv', 'flat_1920_1080_10.yuv')},
21 | ]
22 |
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/python/test/resource/example_batch_input:
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1 | # yuv_fmt width height ref_path src_path
2 | yuv420p 576 324 python/test/resource/yuv/src01_hrc00_576x324.yuv python/test/resource/yuv/src01_hrc01_576x324.yuv
3 | yuv420p 576 324 python/test/resource/yuv/src01_hrc00_576x324.yuv python/test/resource/yuv/src01_hrc00_576x324.yuv
4 |
5 | # repeat
6 | yuv420p 576 324 python/test/resource/yuv/src01_hrc00_576x324.yuv python/test/resource/yuv/src01_hrc01_576x324.yuv
7 | yuv420p 576 324 python/test/resource/yuv/src01_hrc00_576x324.yuv python/test/resource/yuv/src01_hrc00_576x324.yuv
8 |
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/python/test/resource/example_dataset.py:
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1 | dataset_name = 'example'
2 |
3 | yuv_fmt = 'yuv420p'
4 | width = 1920
5 | height = 1080
6 |
7 | from vmaf.config import VmafConfig
8 |
9 | ref_videos = [
10 | {'content_id': 0, 'path': VmafConfig.test_resource_path('yuv', 'checkerboard_1920_1080_10_3_0_0.yuv')},
11 |
12 | {'content_id': 1, 'path': VmafConfig.test_resource_path('yuv', 'flat_1920_1080_0.yuv')},
13 | ]
14 |
15 | dis_videos = [
16 | {'content_id': 0, 'asset_id': 0, 'dmos': 100, 'path': VmafConfig.test_resource_path('yuv', 'checkerboard_1920_1080_10_3_0_0.yuv')}, # ref
17 | {'content_id': 0, 'asset_id': 1, 'dmos': 50, 'path': VmafConfig.test_resource_path('yuv', 'checkerboard_1920_1080_10_3_1_0.yuv')},
18 |
19 | {'content_id': 1, 'asset_id': 2, 'dmos': 100, 'path': VmafConfig.test_resource_path('yuv', 'flat_1920_1080_0.yuv')}, # ref
20 | {'content_id': 1, 'asset_id': 3, 'dmos': 80, 'path': VmafConfig.test_resource_path('yuv', 'flat_1920_1080_10.yuv')},
21 | ]
22 |
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/python/test/resource/example_dataset_crop_pad.py:
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1 | dataset_name = 'example'
2 |
3 | yuv_fmt = 'yuv420p'
4 | width = 576
5 | height = 324
6 | quality_width = 576
7 | quality_height = 324
8 |
9 | from vmaf.config import VmafConfig
10 |
11 | ref_videos = [
12 | {'content_id': 0, 'path': VmafConfig.resource_path('yuv', 'src01_hrc00_576x324.yuv')},
13 | ]
14 |
15 | dis_videos = [
16 | {'content_id': 0, 'asset_id': 1, 'dmos': 50, 'path': VmafConfig.resource_path('yuv', 'src01_hrc01_576x324.yuv'), 'crop_cmd': '288:162:144:81'},
17 | {'content_id': 0, 'asset_id': 2, 'dmos': 49, 'path': VmafConfig.resource_path('yuv', 'src01_hrc01_576x324.yuv'), 'pad_cmd': 'iw+100:ih+100:50:50'},
18 | {'content_id': 0, 'asset_id': 3, 'dmos': 48, 'path': VmafConfig.resource_path('yuv', 'src01_hrc01_576x324.yuv'), 'crop_cmd': '288:162:144:81', 'pad_cmd': 'iw+288:ih+162:144:81',},
19 | ]
20 |
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/python/test/resource/example_dataset_crop_pad_duration_sec.py:
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1 | dataset_name = 'example'
2 |
3 | yuv_fmt = 'yuv420p'
4 | width = 576
5 | height = 324
6 | quality_width = 576
7 | quality_height = 324
8 | duration_sec = 5.0
9 |
10 | from vmaf.config import VmafConfig
11 |
12 | ref_videos = [
13 | {'content_id': 0, 'path': VmafConfig.test_resource_path('yuv', 'src01_hrc00_576x324.yuv')},
14 | ]
15 |
16 | dis_videos = [
17 | {'content_id': 0, 'asset_id': 1, 'dmos': 50, 'path': VmafConfig.test_resource_path('yuv', 'src01_hrc01_576x324.yuv'), 'crop_cmd': '288:162:144:81'},
18 | {'content_id': 0, 'asset_id': 2, 'dmos': 49, 'path': VmafConfig.test_resource_path('yuv', 'src01_hrc01_576x324.yuv'), 'pad_cmd': 'iw+100:ih+100:50:50'},
19 | {'content_id': 0, 'asset_id': 3, 'dmos': 48, 'path': VmafConfig.test_resource_path('yuv', 'src01_hrc01_576x324.yuv'), 'crop_cmd': '288:162:144:81', 'pad_cmd': 'iw+288:ih+162:144:81',},
20 | ]
21 |
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/python/test/resource/example_raw_dataset.py:
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1 | dataset_name = 'example'
2 |
3 | yuv_fmt = 'yuv420p'
4 | width = 1920
5 | height = 1080
6 | ref_score = 100.0
7 |
8 | from vmaf.config import VmafConfig
9 |
10 | ref_videos = [
11 | {'content_id': 0, 'path': VmafConfig.test_resource_path('yuv', 'checkerboard_1920_1080_10_3_0_0.yuv')},
12 |
13 | {'content_id': 1, 'path': VmafConfig.test_resource_path('yuv', 'flat_1920_1080_0.yuv')},
14 | ]
15 |
16 | dis_videos = [
17 | {'content_id': 0, 'asset_id': 0, 'os': [100, 100, 100, 100, 100], 'path': VmafConfig.test_resource_path('yuv', 'checkerboard_1920_1080_10_3_0_0.yuv')}, # ref
18 | {'content_id': 0, 'asset_id': 1, 'os': [40, 45, 50, 55, 60], 'path': VmafConfig.test_resource_path('yuv', 'checkerboard_1920_1080_10_3_1_0.yuv')},
19 |
20 | {'content_id': 1, 'asset_id': 2, 'os': [90, 90, 90, 90, 90], 'path': VmafConfig.test_resource_path('yuv', 'flat_1920_1080_0.yuv')}, # ref
21 | {'content_id': 1, 'asset_id': 3, 'os': [70, 75, 80, 85, 90], 'path': VmafConfig.test_resource_path('yuv', 'flat_1920_1080_10.yuv')},
22 | ]
23 |
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/python/test/resource/example_raw_dataset2.py:
--------------------------------------------------------------------------------
1 | import os
2 |
3 | dataset_name = 'example'
4 |
5 | yuv_fmt = 'yuv420p'
6 | width = 1920
7 | height = 1080
8 | ref_score = 100.0
9 |
10 | dir = '/dir'
11 |
12 | ref_videos = [
13 | {'content_id': 0, 'path': os.path.join(dir, 'yuv', 'checkerboard_1920_1080_10_3_0_0.yuv')},
14 | {'content_id': 1, 'path': os.path.join(dir, 'yuv', 'flat_1920_1080_0.yuv')},
15 | ]
16 |
17 | dis_videos = [
18 | {'content_id': 0, 'asset_id': 0, 'os': [100, 100, 100, 100, 100], 'path': os.path.join(dir, 'yuv', 'checkerboard_1920_1080_10_3_0_0.yuv')}, # ref
19 | {'content_id': 0, 'asset_id': 1, 'os': [40, 45, 50, 55, 60], 'path': os.path.join(dir, 'yuv', 'checkerboard_1920_1080_10_3_1_0.yuv')},
20 |
21 | {'content_id': 1, 'asset_id': 2, 'os': [90, 90, 90, 90, 90], 'path': os.path.join(dir, 'yuv', 'flat_1920_1080_0.yuv')}, # ref
22 | {'content_id': 1, 'asset_id': 3, 'os': [70, 75, 80, 85, 90], 'path': os.path.join(dir, 'yuv', 'flat_1920_1080_10.yuv')},
23 | ]
24 |
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/python/test/resource/example_raw_dataset3.py:
--------------------------------------------------------------------------------
1 | import os
2 |
3 | dataset_name = 'example'
4 |
5 | yuv_fmt = 'yuv420p'
6 | width = 1920
7 | height = 1080
8 | ref_score = 100.0
9 |
10 | quality_width = 1920
11 |
12 | dir = '/dir'
13 |
14 | ref_videos = [
15 | {'content_id': 0, 'path': os.path.join(dir, 'yuv', 'checkerboard_1920_1080_10_3_0_0.yuv')},
16 | {'content_id': 1, 'path': os.path.join(dir, 'yuv', 'flat_1920_1080_0.yuv')},
17 | ]
18 |
19 | dis_videos = [
20 | {'content_id': 0, 'asset_id': 0, 'os': [100, 100, 100, 100, 100], 'path': os.path.join(dir, 'yuv', 'checkerboard_1920_1080_10_3_0_0.yuv')}, # ref
21 | {'content_id': 0, 'asset_id': 1, 'os': [40, 45, 50, 55, 60], 'path': os.path.join(dir, 'yuv', 'checkerboard_1920_1080_10_3_1_0.yuv')},
22 |
23 | {'content_id': 1, 'asset_id': 2, 'os': [90, 90, 90, 90, 90], 'path': os.path.join(dir, 'yuv', 'flat_1920_1080_0.yuv')}, # ref
24 | {'content_id': 1, 'asset_id': 3, 'os': [70, 75, 80, 85, 90], 'path': os.path.join(dir, 'yuv', 'flat_1920_1080_10.yuv')},
25 | ]
26 |
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/python/test/resource/example_raw_dataset4.py:
--------------------------------------------------------------------------------
1 | import os
2 |
3 | dataset_name = 'example'
4 |
5 | yuv_fmt = 'yuv420p'
6 | width = 1920
7 | height = 1080
8 | ref_score = 100.0
9 |
10 | quality_width, quality_height = 1920, 1080
11 |
12 | dir = '/dir'
13 |
14 | ref_videos = [
15 | {'content_id': 0, 'path': os.path.join(dir, 'yuv', 'checkerboard_1920_1080_10_3_0_0.yuv')},
16 | {'content_id': 1, 'path': os.path.join(dir, 'yuv', 'flat_1920_1080_0.yuv')},
17 | ]
18 |
19 | dis_videos = [
20 | {'content_id': 0, 'asset_id': 0, 'os': [100, 100, 100, 100, 100], 'path': os.path.join(dir, 'yuv', 'checkerboard_1920_1080_10_3_0_0.yuv')}, # ref
21 | {'content_id': 0, 'asset_id': 1, 'os': [40, 45, 50, 55, 60], 'path': os.path.join(dir, 'yuv', 'checkerboard_1920_1080_10_3_1_0.yuv')},
22 |
23 | {'content_id': 1, 'asset_id': 2, 'os': [90, 90, 90, 90, 90], 'path': os.path.join(dir, 'yuv', 'flat_1920_1080_0.yuv')}, # ref
24 | {'content_id': 1, 'asset_id': 3, 'os': [70, 75, 80, 85, 90], 'path': os.path.join(dir, 'yuv', 'flat_1920_1080_10.yuv')},
25 | ]
26 |
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/python/test/resource/feature_param_sample.py:
--------------------------------------------------------------------------------
1 | feature_dict = {
2 |
3 | # use selected features from VmafFeatureExtractor
4 | 'VMAF_feature': ['vif', 'adm', 'motion', 'ansnr'],
5 |
6 | 'Moment_feature':['dis1st'], # use distorted video's 1st moment
7 | }
8 |
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/python/test/resource/feature_param_sample_with_optional_dict.py:
--------------------------------------------------------------------------------
1 | feature_dict = {
2 |
3 | # use selected features from VmafFeatureExtractor
4 | 'VMAF_feature': ['vif', 'adm', 'motion', 'ansnr'],
5 |
6 | 'Moment_feature':['dis1st'], # use distorted video's 1st moment
7 | }
8 |
9 | feature_optional_dict = {
10 | 'VMAF_feature': {'adm_ref_display_height': 108000},
11 | }
12 |
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/python/test/resource/feature_param_sample_with_optional_dict_good.py:
--------------------------------------------------------------------------------
1 | feature_dict = {
2 |
3 | # use selected features from VmafFeatureExtractor
4 | 'VMAF_feature': ['vif', 'adm', 'motion', 'ansnr'],
5 |
6 | 'Moment_feature':['dis1st'], # use distorted video's 1st moment
7 | }
8 |
9 | feature_optional_dict = {
10 | 'VMAF_feature': {'adm_ref_display_height': 540},
11 | }
12 |
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/python/test/resource/model_param_sample.py:
--------------------------------------------------------------------------------
1 | model_type = "LIBSVMNUSVR"
2 | model_param_dict = {
3 |
4 | # ==== preprocess: normalize each feature ==== #
5 | 'norm_type':'clip_0to1', # rescale to within [0, 1]
6 |
7 | # ==== postprocess: clip final quality score ==== #
8 |
9 | 'score_clip':[0.0, 100.0], # clip to within [0, 100]
10 |
11 | }
12 |
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/python/test/resource/raw_dataset_sample.py:
--------------------------------------------------------------------------------
1 | dataset_name = 'example'
2 |
3 | yuv_fmt = 'yuv420p'
4 | width = 1920
5 | height = 1080
6 | ref_score = 100.0
7 |
8 | from vmaf.config import VmafConfig
9 |
10 | ref_videos = [
11 | {'content_id': 0, 'path': VmafConfig.test_resource_path('yuv', 'checkerboard_1920_1080_10_3_0_0.yuv')},
12 |
13 | {'content_id': 1, 'path': VmafConfig.test_resource_path('yuv', 'flat_1920_1080_0.yuv')},
14 | ]
15 |
16 | dis_videos = [
17 | {'content_id': 0, 'asset_id': 0, 'os': [100, 100, 100, 100, 100], 'path': VmafConfig.test_resource_path('yuv', 'checkerboard_1920_1080_10_3_0_0.yuv')}, # ref
18 | {'content_id': 0, 'asset_id': 1, 'os': [40, 45, 50, 55, 60], 'path': VmafConfig.test_resource_path('yuv', 'checkerboard_1920_1080_10_3_1_0.yuv')},
19 |
20 | {'content_id': 1, 'asset_id': 2, 'os': [90, 90, 90, 90, 90], 'path': VmafConfig.test_resource_path('yuv', 'flat_1920_1080_0.yuv')}, # ref
21 | {'content_id': 1, 'asset_id': 3, 'os': [70, 75, 80, 85, 90], 'path': VmafConfig.test_resource_path('yuv', 'flat_1920_1080_10.yuv')},
22 | ]
23 |
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/python/test/resource/result_with_none.txt:
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1 | {'asset_id': {0: 0, 1: 0}, 'executor_id': {0: 'STRRED_feature_V1.0', 1: 'STRRED_feature_V1.0'}, 'scores_key': {0: 'STRRED_feature_srred_scores', 1: 'STRRED_feature_trred_scores'}, 'dataset': {0: 'test', 1: 'test'}, 'asset': {0: '{"asset_dict": {"height": 324, "use_path_as_workpath": 1, "width": 576}, "asset_id": 0, "content_id": 0, "dataset": "test", "dis_path": "flat_1920_1080_10.yuv", "ref_path": "flat_1920_1080_0.yuv", "workdir": ""}', 1: '{"asset_dict": {"height": 324, "use_path_as_workpath": 1, "width": 576}, "asset_id": 0, "content_id": 0, "dataset": "test", "dis_path": "flat_1920_1080_10.yuv", "ref_path": "flat_1920_1080_0.yuv", "workdir": ""}'}, 'dis_name': {0: 'flat_1920_1080_10.yuv', 1: 'flat_1920_1080_10.yuv'}, 'scores': {0: [None, None, None, None, None, None, None, 11302.90547, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, 355.623424, None, None, None], 1: [None, None, None, None, None, None, None, 10514.716612, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, 15659.008856, None, None, None]}, 'content_id': {0: 0, 1: 0}, 'ref_name': {0: 'flat_1920_1080_0.yuv', 1: 'flat_1920_1080_0.yuv'}}
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/python/test/resource/test_dataset.py:
--------------------------------------------------------------------------------
1 | dataset_name = 'example'
2 |
3 | yuv_fmt = 'yuv420p'
4 | width = 1920
5 | height = 1080
6 |
7 | from vmaf.config import VmafConfig
8 |
9 | ref_videos = [
10 | {'content_id': 0, 'path': VmafConfig.resource_path('yuv', 'checkerboard_1920_1080_10_3_0_0.yuv')},
11 |
12 | {'content_id': 1, 'path': VmafConfig.resource_path('yuv', 'flat_1920_1080_0.yuv')},
13 | ]
14 |
15 | dis_videos = [
16 | {'content_id': 0, 'asset_id': 0, 'dmos': 100, 'path': VmafConfig.resource_path('yuv', 'checkerboard_1920_1080_10_3_0_0.yuv')}, # ref
17 | {'content_id': 0, 'asset_id': 1, 'dmos': 50, 'path': VmafConfig.resource_path('yuv', 'checkerboard_1920_1080_10_3_1_0.yuv')},
18 |
19 | {'content_id': 1, 'asset_id': 2, 'dmos': 100, 'path': VmafConfig.resource_path('yuv', 'flat_1920_1080_0.yuv')}, # ref
20 | {'content_id': 1, 'asset_id': 3, 'dmos': 80, 'path': VmafConfig.resource_path('yuv', 'flat_1920_1080_10.yuv')},
21 | ]
22 |
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/python/test/resource/test_dataset_bad_fps_rebufinds.py:
--------------------------------------------------------------------------------
1 | dataset_name = 'example'
2 |
3 | quality_width = 1920
4 | quality_height = 1080
5 |
6 | from vmaf.config import VmafConfig
7 |
8 | ref_videos = [
9 | {'content_id': 0, 'path': VmafConfig.resource_path('yuv', 'checkerboard_1920_1080_10_3_0_0.yuv'), 'yuv_fmt': 'yuv420p'},
10 | ]
11 |
12 | dis_videos = [
13 | {'content_id': 0, 'asset_id': 0, 'dmos': 100, 'path': VmafConfig.resource_path('yuv', 'checkerboard_1920_1080_10_3_0_0.yuv'), 'fps': -10, 'rebuf_indices': [0, 4, 15]}, # ref, make up fps and rebuf indices
14 | ]
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/python/test/resource/test_dataset_diffyuv.py:
--------------------------------------------------------------------------------
1 | dataset_name = 'example'
2 |
3 | from vmaf.config import VmafConfig
4 |
5 | ref_videos = [
6 | {'content_id': 0, 'path': VmafConfig.resource_path('yuv', 'checkerboard_1920_1080_10_3_0_0.yuv'), 'width': 1920, 'height': 1080, 'yuv_fmt': 'yuv420p'},
7 |
8 | {'content_id': 1, 'path': VmafConfig.resource_path('yuv', 'flat_1280_720_0.yuv'), 'width': 1280, 'height': 720, 'yuv_fmt': 'yuv420p10le'},
9 | ]
10 |
11 | dis_videos = [
12 | {'content_id': 0, 'asset_id': 0, 'groundtruth': 100, 'path': VmafConfig.resource_path('yuv', 'checkerboard_1920_1080_10_3_0_0.yuv')}, # ref
13 | {'content_id': 0, 'asset_id': 1, 'groundtruth': 50, 'path': VmafConfig.resource_path('yuv', 'checkerboard_1920_1080_10_3_1_0.yuv')},
14 |
15 | {'content_id': 1, 'asset_id': 2, 'groundtruth': 100, 'path': VmafConfig.resource_path('yuv', 'flat_1280_720_0.yuv')}, # ref
16 | {'content_id': 1, 'asset_id': 3, 'groundtruth': 80, 'path': VmafConfig.resource_path('yuv', 'flat_1280_720_10.yuv')},
17 | ]
18 |
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/python/test/resource/test_dataset_fps_bad_rebufinds.py:
--------------------------------------------------------------------------------
1 | dataset_name = 'example'
2 |
3 | quality_width = 1920
4 | quality_height = 1080
5 |
6 | from vmaf.config import VmafConfig
7 |
8 | ref_videos = [
9 | {'content_id': 0, 'path': VmafConfig.resource_path('yuv', 'checkerboard_1920_1080_10_3_0_0.yuv'), 'yuv_fmt': 'yuv420p'},
10 | ]
11 |
12 | dis_videos = [
13 | {'content_id': 0, 'asset_id': 0, 'dmos': 100, 'path': VmafConfig.resource_path('yuv', 'checkerboard_1920_1080_10_3_0_0.yuv'), 'fps': 30, 'rebuf_indices': [0, -4, 15]}, # ref, make up fps and rebuf indices
14 | ]
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/python/test/resource/test_dataset_fps_rebufinds.py:
--------------------------------------------------------------------------------
1 | dataset_name = 'example'
2 |
3 | quality_width = 1920
4 | quality_height = 1080
5 |
6 | from vmaf.config import VmafConfig
7 |
8 | ref_videos = [
9 | {'content_id': 0, 'path': VmafConfig.resource_path('yuv', 'checkerboard_1920_1080_10_3_0_0.yuv'), 'yuv_fmt': 'yuv420p'},
10 | ]
11 |
12 | dis_videos = [
13 | {'content_id': 0, 'asset_id': 0, 'dmos': 100, 'path': VmafConfig.resource_path('yuv', 'checkerboard_1920_1080_10_3_0_0.yuv'), 'fps': 30, 'rebuf_indices': [0, 4, 15]}, # ref, make up fps and rebuf indices
14 | ]
--------------------------------------------------------------------------------
/python/test/resource/test_dataset_mixed.py:
--------------------------------------------------------------------------------
1 | dataset_name = 'example'
2 |
3 | quality_width = 1920
4 | quality_height = 1080
5 |
6 | from vmaf.config import VmafConfig
7 |
8 | ref_videos = [
9 | {'content_id': 0, 'path': VmafConfig.resource_path('yuv', 'checkerboard_1920_1080_10_3_0_0.yuv'), 'yuv_fmt': 'yuv420p', 'width': 1920, 'height': 1080},
10 |
11 | {'content_id': 1, 'path': VmafConfig.resource_path('yuv', 'flat_1920_1080_0.yuv'), 'yuv_fmt': 'yuv420p', 'width': 720, 'height': 480},
12 | ]
13 |
14 | dis_videos = [
15 | {'content_id': 0, 'asset_id': 0, 'dmos': 100, 'path': VmafConfig.resource_path('yuv', 'checkerboard_1920_1080_10_3_0_0.yuv'), 'yuv_fmt': 'yuv420p', 'width': 1920, 'height': 1080}, # ref
16 | {'content_id': 0, 'asset_id': 1, 'dmos': 50, 'path': VmafConfig.resource_path('yuv', 'checkerboard_1920_1080_10_3_1_0.264'), 'yuv_fmt': 'notyuv',},
17 |
18 | {'content_id': 1, 'asset_id': 2, 'dmos': 100, 'path': VmafConfig.resource_path('yuv', 'flat_1920_1080_0.yuv'), 'yuv_fmt': 'yuv420p', 'width': 720, 'height': 480}, # ref
19 | {'content_id': 1, 'asset_id': 3, 'dmos': 80, 'path': VmafConfig.resource_path('yuv', 'flat_1920_1080_10.264'), 'yuv_fmt': 'notyuv',},
20 | ]
21 |
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/python/test/resource/test_image_dataset_notyuv.py:
--------------------------------------------------------------------------------
1 | dataset_name = 'example_image'
2 |
3 | yuv_fmt = 'notyuv'
4 | quality_width = 1920
5 | quality_height = 1080
6 |
7 | from vmaf.config import VmafConfig
8 |
9 | ref_videos = [
10 | {'content_id': 0, 'path': VmafConfig.resource_path('icpf', 'frame00000001.icpf')},
11 |
12 | {'content_id': 1, 'path': VmafConfig.resource_path('icpf', 'frame00000002.icpf')},
13 | ]
14 |
15 | dis_videos = [
16 | {'content_id': 0, 'asset_id': 0, 'dmos': 100, 'path': VmafConfig.resource_path('icpf', 'frame00000000.icpf')}, # ref
17 | {'content_id': 0, 'asset_id': 1, 'dmos': 50, 'path': VmafConfig.resource_path('icpf', 'frame00000001.icpf')},
18 |
19 | {'content_id': 1, 'asset_id': 2, 'dmos': 100, 'path': VmafConfig.resource_path('icpf', 'frame00000002.icpf')}, # ref
20 | {'content_id': 1, 'asset_id': 3, 'dmos': 80, 'path': VmafConfig.resource_path('icpf', 'frame00000003.icpf')},
21 | ]
22 |
23 |
24 |
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/python/test/resource/test_image_dataset_notyuv_workfile_yuv_type.py:
--------------------------------------------------------------------------------
1 | dataset_name = 'example_image'
2 |
3 | yuv_fmt = 'notyuv'
4 | quality_width = 1920
5 | quality_height = 1080
6 | workfile_yuv_type = 'yuv444p'
7 |
8 | from vmaf.config import VmafConfig
9 |
10 | ref_videos = [
11 | {'content_id': 0, 'path': VmafConfig.resource_path('icpf', 'frame00000001.icpf')},
12 |
13 | {'content_id': 1, 'path': VmafConfig.resource_path('icpf', 'frame00000002.icpf')},
14 | ]
15 |
16 | dis_videos = [
17 | {'content_id': 0, 'asset_id': 0, 'dmos': 100, 'path': VmafConfig.resource_path('icpf', 'frame00000000.icpf')}, # ref
18 | {'content_id': 0, 'asset_id': 1, 'dmos': 50, 'path': VmafConfig.resource_path('icpf', 'frame00000001.icpf')},
19 |
20 | {'content_id': 1, 'asset_id': 2, 'dmos': 100, 'path': VmafConfig.resource_path('icpf', 'frame00000002.icpf')}, # ref
21 | {'content_id': 1, 'asset_id': 3, 'dmos': 80, 'path': VmafConfig.resource_path('icpf', 'frame00000003.icpf')},
22 | ]
23 |
24 |
25 |
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/python/test/resource/test_read_dataset_dataset.py:
--------------------------------------------------------------------------------
1 | import os
2 |
3 | dataset_name = 'DBName'
4 | quality_width = 1280
5 | quality_height = 1920
6 | start_frame = 200
7 | end_frame = 210
8 |
9 | root_dir = ""
10 |
11 | ref_videos = [
12 | {'content_id': 0, 'content_name': 'XXX360', 'path': os.path.join(root_dir, 'XXX360Ref.mkv'),
13 | 'yuv_fmt': 'notyuv'}
14 | ]
15 |
16 | dis_videos = [
17 |
18 | {'asset_id': 3, 'content_id': 0, 'path': os.path.join(root_dir, 'XXX360Ref.mkv'), 'yuv_fmt': 'notyuv',
19 | 'groundtruth': None, 'crop_cmd': '1280:1920:0:0'},
20 | {'asset_id': 4, 'content_id': 0, 'path': os.path.join(root_dir, 'XXX360DisScaling.mp4'), 'yuv_fmt': 'notyuv',
21 | 'groundtruth': None, 'crop_cmd': '1280:1920:0:0', 'start_frame': 100, 'end_frame': 110},
22 | {'asset_id': 5, 'content_id': 0, 'path': os.path.join(root_dir, 'XXX360DisTiling.mp4'), 'yuv_fmt': 'notyuv',
23 | 'groundtruth': None, 'crop_cmd': '1280:1920:0:0'},
24 |
25 | ]
26 |
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/python/test/resource/test_read_dataset_dataset2.py:
--------------------------------------------------------------------------------
1 | import os
2 |
3 | dataset_name = 'DBName'
4 | quality_width = 1280
5 | quality_height = 1920
6 | fps = 1
7 | duration_sec = 10
8 |
9 | root_dir = ""
10 |
11 | ref_videos = [
12 | {'content_id': 0, 'content_name': 'XXX360', 'path': os.path.join(root_dir, 'XXX360Ref.mkv'),
13 | 'yuv_fmt': 'notyuv'}
14 | ]
15 |
16 | dis_videos = [
17 |
18 | {'asset_id': 3, 'content_id': 0, 'path': os.path.join(root_dir, 'XXX360Ref.mkv'), 'yuv_fmt': 'notyuv',
19 | 'groundtruth': None, 'crop_cmd': '1280:1920:0:0'},
20 |
21 | {'asset_id': 4, 'content_id': 0, 'path': os.path.join(root_dir, 'XXX360DisScaling.mp4'), 'yuv_fmt': 'notyuv',
22 | 'groundtruth': None, 'crop_cmd': '1280:1920:0:0', 'start_frame': 100, 'end_frame': 110},
23 |
24 | {'asset_id': 5, 'content_id': 0, 'path': os.path.join(root_dir, 'XXX360DisTiling.mp4'), 'yuv_fmt': 'notyuv',
25 | 'groundtruth': None, 'crop_cmd': '1280:1920:0:0'},
26 |
27 | ]
28 |
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/python/test/resource/test_read_dataset_dataset3.py:
--------------------------------------------------------------------------------
1 | import os
2 |
3 | dataset_name = 'DBName'
4 | quality_width = 1280
5 | quality_height = 1920
6 | start_frame = 200
7 | end_frame = 210
8 |
9 | root_dir = ""
10 |
11 | ref_videos = [
12 | {'content_id': 0, 'content_name': 'XXX360', 'path': os.path.join(root_dir, 'XXX360Ref.mkv'),
13 | 'yuv_fmt': 'notyuv', 'ref_start_frame': 250, 'ref_end_frame': 250}
14 | ]
15 |
16 | dis_videos = [
17 |
18 | {'asset_id': 3, 'content_id': 0, 'path': os.path.join(root_dir, 'XXX360Ref.mkv'), 'yuv_fmt': 'notyuv',
19 | 'groundtruth': None, 'crop_cmd': '1280:1920:0:0', 'dis_start_frame': 250, 'dis_end_frame': 250},
20 | {'asset_id': 4, 'content_id': 0, 'path': os.path.join(root_dir, 'XXX360DisScaling.mp4'), 'yuv_fmt': 'notyuv',
21 | 'groundtruth': None, 'crop_cmd': '1280:1920:0:0', 'start_frame': 100, 'end_frame': 110},
22 | {'asset_id': 5, 'content_id': 0, 'path': os.path.join(root_dir, 'XXX360DisTiling.mp4'), 'yuv_fmt': 'notyuv',
23 | 'groundtruth': None, 'crop_cmd': '1280:1920:0:0', 'dis_start_frame': 250, 'dis_end_frame': 251},
24 |
25 | ]
26 |
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/python/test/resource/vmaf_float_v0.6.1neg.inconsist.pkl:
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https://raw.githubusercontent.com/Netflix/vmaf/b9ac69e6c4231fad0465021f9e31a841a18261db/python/test/resource/vmaf_float_v0.6.1neg.inconsist.pkl
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/python/test/resource/vmaf_v4.py:
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1 | feature_dict = {
2 |
3 | 'VMAF_feature': ['vif_scale0', 'vif_scale1', 'vif_scale2', 'vif_scale3', 'adm2', 'motion',],
4 |
5 | }
6 |
7 | model_type = "LIBSVMNUSVR"
8 | model_param_dict = {
9 |
10 | # ==== preprocess: normalize each feature ==== #
11 | # 'norm_type': 'none', # default: do nothing
12 | 'norm_type': 'clip_0to1', # rescale to within [0, 1]
13 | # 'norm_type': 'clip_minus1to1', # rescale to within [-1, 1]
14 | # 'norm_type': 'normalize', # rescale to mean zero and std one
15 |
16 | # ==== postprocess: clip final quality score ==== #
17 | # 'score_clip': None, # default: do nothing
18 | 'score_clip': [0.0, 100.0], # clip to within [0, 100]
19 |
20 | # ==== libsvmnusvr parameters ==== #
21 |
22 | # 'gamma': 0.0, # default
23 | 'gamma': 0.05, # vmaf_v3, vmaf_v4
24 |
25 | # 'C': 1.0, # default
26 | 'C': 4.0, # vmaf_v4
27 |
28 | # 'nu': 0.5, # default
29 | 'nu': 0.9, # vmafv4
30 | }
31 |
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/python/test/resource/vmafplus_v6_bootstrap_test.py:
--------------------------------------------------------------------------------
1 | feature_dict = {
2 |
3 | 'VMAF_feature': ['vif_scale0', 'vif_scale1', 'vif_scale2', 'vif_scale3',
4 | 'adm2', 'motion2',],
5 |
6 | }
7 |
8 | model_type = "BOOTSTRAP_LIBSVMNUSVR"
9 | model_param_dict = {
10 |
11 | # ==== preprocess: normalize each feature ==== #
12 | 'norm_type': 'clip_0to1', # rescale to within [0, 1]
13 |
14 | # ==== postprocess: clip final quality score ==== #
15 | # 'score_clip': None, # default: do nothing
16 | 'score_clip': [0.0, 100.0], # clip to within [0, 100]
17 |
18 | # ==== postprocess: transform final quality score ==== #
19 | 'score_transform': {'p0':1.70674692, 'p1':1.72643844, 'p2':-0.00705305,}, # laptop vs. mobile transform
20 |
21 | # ==== libsvmnusvr parameters ==== #
22 |
23 | 'gamma': 0.04,
24 | 'C': 4.0,
25 | 'nu': 0.9,
26 |
27 | # ==== bootstrap parameters ==== #
28 |
29 | 'num_models': 5,
30 | }
31 |
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/python/test/resource/vmafplus_v6_bootstrap_test2.py:
--------------------------------------------------------------------------------
1 | feature_dict = {
2 |
3 | 'VMAF_feature': ['vif_scale0', 'vif_scale1', 'vif_scale2', 'vif_scale3',
4 | 'adm2', 'motion2',],
5 |
6 | }
7 |
8 | model_type = "BOOTSTRAP_LIBSVMNUSVR"
9 | model_param_dict = {
10 |
11 | # ==== preprocess: normalize each feature ==== #
12 | 'norm_type': 'clip_0to1', # rescale to within [0, 1]
13 |
14 | # ==== postprocess: clip final quality score ==== #
15 | # 'score_clip': None, # default: do nothing
16 | 'score_clip': [0.0, 100.0], # clip to within [0, 100]
17 |
18 | # ==== postprocess: transform final quality score ==== #
19 | 'score_transform': {'p0':1.70674692, 'p1':1.72643844, 'p2':-0.00705305,}, # laptop vs. mobile transform
20 |
21 | # ==== libsvmnusvr parameters ==== #
22 |
23 | 'gamma': 0.04,
24 | 'C': 4.0,
25 | 'nu': 0.9,
26 |
27 | # ==== bootstrap parameters ==== #
28 |
29 | 'num_models': 10,
30 | }
31 |
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/python/vmaf/core/__init__.py:
--------------------------------------------------------------------------------
1 | __copyright__ = "Copyright 2016-2020, Netflix, Inc."
2 | __license__ = "BSD+Patent"
3 |
--------------------------------------------------------------------------------
/python/vmaf/core/adm_dwt2_py.py:
--------------------------------------------------------------------------------
1 | import pywt
2 |
3 |
4 | def adm_dwt2_py(a):
5 | a, ds = pywt.dwt2(a, 'db2', 'periodization')
6 | h, v, d = ds
7 | return a, v, h, d
8 |
9 |
10 | def adm_idwt2_py(a_v_h_d):
11 | a, v, h, d = a_v_h_d
12 | ds = (h, v, d)
13 | a = pywt.idwt2((a, ds), 'db2', 'periodization')
14 | return a
15 |
--------------------------------------------------------------------------------
/python/vmaf/core/adm_dwt2_tools.py:
--------------------------------------------------------------------------------
1 | MAX_ALIGN = 32
2 |
3 |
4 | def ALIGN_CEIL(x):
5 | """
6 | # ((x) + ((x) % MAX_ALIGN ? MAX_ALIGN - (x) % MAX_ALIGN : 0))
7 |
8 | >>> ALIGN_CEIL(3)
9 | 32
10 | >>> ALIGN_CEIL(32)
11 | 32
12 | >>> ALIGN_CEIL(33)
13 | 64
14 |
15 | """
16 | if x % MAX_ALIGN != 0:
17 | y = MAX_ALIGN - x % MAX_ALIGN
18 | else:
19 | y = 0
20 | return x + y
21 |
22 |
23 | if __name__ == '__main__':
24 | import doctest
25 | doctest.testmod()
26 |
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/python/vmaf/core/cambi_quality_runner.py:
--------------------------------------------------------------------------------
1 | from abc import ABC
2 |
3 | from vmaf.core.cambi_feature_extractor import CambiFeatureExtractor, CambiFullReferenceFeatureExtractor
4 | from vmaf.core.quality_runner import QualityRunnerFromFeatureExtractor
5 | from vmaf.tools.decorator import override
6 |
7 |
8 | class CambiQualityRunner(QualityRunnerFromFeatureExtractor, ABC):
9 |
10 | TYPE = 'Cambi'
11 | VERSION = 'F' + CambiFeatureExtractor.VERSION
12 |
13 | @override(QualityRunnerFromFeatureExtractor)
14 | def _get_feature_extractor_class(self):
15 | return CambiFeatureExtractor
16 |
17 | @override(QualityRunnerFromFeatureExtractor)
18 | def _get_feature_key_for_score(self):
19 | return 'cambi'
20 |
21 |
22 | class CambiFullReferenceQualityRunner(QualityRunnerFromFeatureExtractor, ABC):
23 |
24 | TYPE = 'Cambi_FR'
25 | VERSION = 'F' + CambiFeatureExtractor.VERSION
26 |
27 | @override(QualityRunnerFromFeatureExtractor)
28 | def _get_feature_extractor_class(self):
29 | return CambiFullReferenceFeatureExtractor
30 |
31 | @override(QualityRunnerFromFeatureExtractor)
32 | def _get_feature_key_for_score(self):
33 | return 'cambi_full_reference'
34 |
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/python/vmaf/core/h5py_mixin.py:
--------------------------------------------------------------------------------
1 | import h5py
2 |
3 | __copyright__ = "Copyright 2016-2020, Netflix, Inc."
4 | __license__ = "BSD+Patent"
5 |
6 |
7 | class H5pyMixin(object):
8 | """
9 | Use a h5py file to store raw video channel or similar as features.
10 | Implementation class must have attribute optional_dict2.
11 | """
12 | @staticmethod
13 | def open_h5py_file(h5py_filepath, mode='w'):
14 | f = h5py.File(h5py_filepath, mode)
15 | return f
16 |
17 | @staticmethod
18 | def close_h5py_file(f, mode='w'):
19 | if mode == 'w':
20 | f.flush()
21 | f.close()
22 | elif mode == 'r':
23 | f.close()
24 | else:
25 | assert False
26 |
27 | def assert_h5py_file(self):
28 | assert self.optional_dict2 is not None and 'h5py_file' in self.optional_dict2
29 |
30 | @property
31 | def h5py_file(self):
32 | return self.optional_dict2['h5py_file']
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/python/vmaf/core/proc_func.py:
--------------------------------------------------------------------------------
1 | __copyright__ = "Copyright 2016-2020, Netflix, Inc."
2 | __license__ = "BSD+Patent"
3 |
4 | proc_func_dict = {
5 | 'identity': lambda x: x,
6 | 'multiply': lambda x: x * 1.1,
7 | }
8 |
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/python/vmaf/script/__init__.py:
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https://raw.githubusercontent.com/Netflix/vmaf/b9ac69e6c4231fad0465021f9e31a841a18261db/python/vmaf/script/__init__.py
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/python/vmaf/third_party/__init__.py:
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https://raw.githubusercontent.com/Netflix/vmaf/b9ac69e6c4231fad0465021f9e31a841a18261db/python/vmaf/third_party/__init__.py
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/python/vmaf/third_party/xiph/__init__.py:
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https://raw.githubusercontent.com/Netflix/vmaf/b9ac69e6c4231fad0465021f9e31a841a18261db/python/vmaf/third_party/xiph/__init__.py
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/python/vmaf/tools/__init__.py:
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1 | __copyright__ = "Copyright 2016-2020, Netflix, Inc."
2 | __license__ = "BSD+Patent"
3 |
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/python/vmaf/tools/exceptions.py:
--------------------------------------------------------------------------------
1 | class BdRateException(Exception):
2 | pass
3 |
4 |
5 | class BdRateNotEnoughPointsException(BdRateException):
6 | """Exception raised when there are not enough points in the BD-rate calculation."""
7 |
8 | def __init__(self, message: str = "Not enough points for BD-rate calculation; at least 4 points required"):
9 | super().__init__(message)
10 |
11 |
12 | class BdRateNoOverlapException(BdRateException):
13 | """Exception raised when there is no overlap in the BD-rate calculation."""
14 |
15 | def __init__(self, message: str = "No overlap in BD-rate calculation"):
16 | super().__init__(message)
17 |
18 |
19 | class BdRateNonMonotonicException(BdRateException):
20 | """Exception raised for non-monotonic data in the BD-rate calculation."""
21 |
22 | def __init__(self, message: str = "Non-monotonic data found in BD-rate calculation"):
23 | super().__init__(message)
24 |
25 |
26 | class BdRateZeroRateException(BdRateException):
27 | """Exception raised for data with zero rate in the BD-rate calculation."""
28 |
29 | def __init__(self, message: str = "Points with zero rate found in BD-rate calculation"):
30 | super().__init__(message)
31 |
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/python/vmaf/tools/kimchi.py:
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1 | # kimchi.py
2 | # For converting Python 2 pickles to Python 3
3 | # taken from https://rebeccabilbro.github.io/convert-py2-pickles-to-py3/
4 |
5 | import os
6 | import dill
7 | import pickle
8 | import argparse
9 |
10 |
11 | def convert(old_pkl):
12 | """
13 | Convert a Python 2 pickle to Python 3
14 | """
15 | # Make a name for the new pickle
16 | new_pkl = os.path.splitext(os.path.basename(old_pkl))[0]+"_p3.pkl"
17 |
18 | # Convert Python 2 "ObjectType" to Python 3 object
19 | dill._dill._reverse_typemap["ObjectType"] = object
20 |
21 | # Open the pickle using latin1 encoding
22 | with open(old_pkl, "rb") as f:
23 | loaded = pickle.load(f, encoding="latin1")
24 |
25 | # Re-save as Python 3 pickle
26 | with open(new_pkl, "wb") as outfile:
27 | pickle.dump(loaded, outfile)
28 |
29 |
30 | if __name__ == "__main__":
31 | parser = argparse.ArgumentParser(
32 | description="Convert a Python 2 pickle to Python 3"
33 | )
34 |
35 | parser.add_argument("infile", help="Python 2 pickle filename")
36 |
37 | args = parser.parse_args()
38 |
39 | convert(args.infile)
40 |
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/python/vmaf/tools/resource/Hanley_McNeil.mat:
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https://raw.githubusercontent.com/Netflix/vmaf/b9ac69e6c4231fad0465021f9e31a841a18261db/python/vmaf/tools/resource/Hanley_McNeil.mat
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/python/vmaf/tools/typing_utils.py:
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1 | from __future__ import annotations
2 |
3 | from dataclasses import dataclass
4 |
5 |
6 | @dataclass
7 | class RdPoint:
8 | rate: float
9 | metric: float
10 |
11 | def __hash__(self) -> int:
12 | return hash((self.rate, self.metric))
13 |
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/resource/doc/bad_cases.md:
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1 | # Reporting Bad Cases
2 |
3 | Over time, we have received feedbacks on when VMAF's prediction does not reflect the expected perceptual quality of videos, either they are corner cases where VMAF fails to cover, or new application scenarios which VMAF was not initially intended for. In response to that, we have created a Google form to allow users to upload their video samples and describe their cases. The bad cases are valuable for improving future versions of VMAF. Users can opt in or out for sharing their sample videos publicly.
4 |
5 | Please submit the bad cases through [this link](https://docs.google.com/forms/d/e/1FAIpQLSdJntNoBuucMSiYoK3SDWoY1QN0yiFAi5LyEXuOyXEWJbQBtQ/viewform?usp=sf_link).
6 |
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/resource/doc/nflx_ctc.md:
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1 | # NFLX CTC
2 |
3 | ## Metrics
4 | Using the versioned `--nflx_ctc` preset, the following metrics will be computed and logged. These metrics are specified according to the NFLX CTC.
5 |
6 | * PSNR
7 | * APSNR
8 | * SSIM
9 | * VMAF
10 | * VMAF NEG
11 | * CAMBI
12 |
13 | ## Usage
14 | Basic usage of the tool is described in the [`vmaf` README](../../libvmaf/tools/README.md). Use the versioned `--nflx_ctc` presets to register and configure all metrics according to the NFLX CTC. Basic usage is as follows:
15 |
16 | ```
17 | ./build/tools/vmaf \
18 | --reference reference.y4m \
19 | --distorted distorted.y4m \
20 | --nflx_ctc v1.0 \
21 | --json \
22 | --output output.json
23 | ```
24 |
25 | There are also a few optional command-line settings you may find useful.
26 | * Use `--threads` to set the thread count to be used for multi-threaded computation. This will decrease the overall latency.
27 |
28 | ## Output
29 | `JSON` logging formats provide per-frame metrics, pooled metrics, and aggregate metrics.
30 |
31 | ## NFLX CTC Version History
32 | * v1.0: `--nflx_ctc v1.0`
33 | * 2023-01-01
34 | * Initial CTC release
35 |
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/resource/doc/papers/CAMBI_PCS2021.pdf:
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/resource/doc/presentations/VMAF_ICIP17.pdf:
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/resource/doc/release.md:
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1 | Instructions for Publishing a New Release
2 | ========================
3 | - Manually search the repo for the current version number (for example: 1.5.1) and replace it with the next version (for example: 1.5.2).
4 | - Update [CHANGELOG.md](https://github.com/Netflix/vmaf/blob/master/CHANGELOG.md) with new features and bugfixes since the last release (check against the [commit history](https://github.com/Netflix/vmaf/commits/master) between the dates and take in any significant / non-trivial changes into the "New features" and "Fixed bugs" lists).
5 | - Merge the changes above into master. At the [release](https://github.com/Netflix/vmaf/releases) page, click on `Draft a new release`, and follow the instructions.
6 |
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/resource/doc/windows.md:
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1 | # Building vmaf on Windows
2 |
3 | We are going to build vmaf in Windows. These steps are in accordance with the corresponding github action for building on Windows and have been tested successfully using a Windows10 machine. They work with either `cmd` or `PowerShell`.
4 |
5 | **Note:** This guide is just to build libvmaf on Windows and not involves the python part of project as it is the same across all platforms (settings up virtual environment, ...).
6 |
7 | ## Steps
8 | 1. Install [msys2](https://www.msys2.org/)
9 |
10 | 2. Install required msys2 packages using its shell:
11 |
12 | pacman -S --noconfirm --needed mingw-w64-x86_64-nasm mingw-w64-x86_64-gcc mingw-w64-x86_64-meson mingw-w64-x86_64-ninja
13 |
14 | 3. It is assumed the final results will be in `C:/vmaf-install` (You can change it to any directory if you want). Finally setup the meson and build:
15 |
16 |
17 | cd <Vmaf project root directory>
18 | mkdir C:/vmaf-install
19 | meson setup libvmaf libvmaf/build --buildtype release --default-library static --prefix C:/vmaf-install
20 | meson install -C libvmaf/build
21 |
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/resource/example/example_batch_input:
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1 | # yuv_fmt width height ref_path src_path
2 | yuv420p 576 324 python/test/resource/yuv/src01_hrc00_576x324.yuv python/test/resource/yuv/src01_hrc01_576x324.yuv
3 | yuv420p 576 324 python/test/resource/yuv/src01_hrc00_576x324.yuv python/test/resource/yuv/src01_hrc00_576x324.yuv
4 |
5 | # repeat
6 | yuv420p 576 324 python/test/resource/yuv/src01_hrc00_576x324.yuv python/test/resource/yuv/src01_hrc01_576x324.yuv
7 | yuv420p 576 324 python/test/resource/yuv/src01_hrc00_576x324.yuv python/test/resource/yuv/src01_hrc00_576x324.yuv
8 |
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/resource/example/example_dataset.py:
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1 | dataset_name = 'example'
2 |
3 | yuv_fmt = 'yuv420p'
4 | width = 1920
5 | height = 1080
6 |
7 | from vmaf.config import VmafConfig
8 |
9 | ref_videos = [
10 | {'content_id': 0, 'path': VmafConfig.test_resource_path('yuv', 'checkerboard_1920_1080_10_3_0_0.yuv')},
11 |
12 | {'content_id': 1, 'path': VmafConfig.test_resource_path('yuv', 'flat_1920_1080_0.yuv')},
13 | ]
14 |
15 | dis_videos = [
16 | {'content_id': 0, 'asset_id': 0, 'dmos': 100, 'path': VmafConfig.test_resource_path('yuv', 'checkerboard_1920_1080_10_3_0_0.yuv')}, # ref
17 | {'content_id': 0, 'asset_id': 1, 'dmos': 50, 'path': VmafConfig.test_resource_path('yuv', 'checkerboard_1920_1080_10_3_1_0.yuv')},
18 |
19 | {'content_id': 1, 'asset_id': 2, 'dmos': 100, 'path': VmafConfig.test_resource_path('yuv', 'flat_1920_1080_0.yuv')}, # ref
20 | {'content_id': 1, 'asset_id': 3, 'dmos': 80, 'path': VmafConfig.test_resource_path('yuv', 'flat_1920_1080_10.yuv')},
21 | ]
22 |
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/resource/example/example_raw_dataset.py:
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1 | dataset_name = 'example'
2 |
3 | yuv_fmt = 'yuv420p'
4 | width = 1920
5 | height = 1080
6 | ref_score = 100.0
7 |
8 | from vmaf.config import VmafConfig
9 |
10 | ref_videos = [
11 | {'content_id': 0, 'content_name': 'checkerboard', 'path': VmafConfig.test_resource_path('yuv', 'checkerboard_1920_1080_10_3_0_0.yuv')},
12 |
13 | {'content_id': 1, 'content_name': 'flat', 'path': VmafConfig.test_resource_path('yuv', 'flat_1920_1080_0.yuv')},
14 | ]
15 |
16 | dis_videos = [
17 | {'content_id': 0, 'asset_id': 0, 'os': [100, 100, 100, 100, 100], 'path': VmafConfig.test_resource_path('yuv', 'checkerboard_1920_1080_10_3_0_0.yuv')}, # ref
18 | {'content_id': 0, 'asset_id': 1, 'os': [40, 45, 50, 55, 60], 'path': VmafConfig.test_resource_path('yuv', 'checkerboard_1920_1080_10_3_1_0.yuv')},
19 |
20 | {'content_id': 1, 'asset_id': 2, 'os': [90, 90, 90, 90, 90], 'path': VmafConfig.test_resource_path('yuv', 'flat_1920_1080_0.yuv')}, # ref
21 | {'content_id': 1, 'asset_id': 3, 'os': [70, 75, 80, 85, 90], 'path': VmafConfig.test_resource_path('yuv', 'flat_1920_1080_10.yuv')},
22 | ]
23 |
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/resource/example/externals.py:
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1 | FFMPEG_PATH = '/home/zli/Projects/stash/MCE/transcoder/builds/bin/ffmpeg'
2 | MATLAB_PATH = '/usr/local/MATLAB/R2014b/bin/matlab'
3 |
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/resource/feature_param/ssim.py:
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1 | feature_dict = {
2 | 'SSIM_feature': ['ssim'],
3 | }
4 |
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/resource/feature_param/vmaf_feature_v1.py:
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1 | feature_dict = {
2 |
3 | # use selected features from VmafFeatureExtractor
4 | 'VMAF_feature': ['vif', 'adm', 'motion', 'ansnr'],
5 |
6 | }
7 |
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/resource/feature_param/vmaf_feature_v2.py:
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1 | feature_dict = {
2 |
3 | 'VMAF_feature': ['vif_scale0', 'vif_scale1', 'vif_scale2', 'vif_scale3', 'adm2', 'motion', 'ansnr', ],
4 |
5 | }
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/resource/feature_param/vmaf_feature_v3.py:
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1 | feature_dict = {
2 |
3 | 'VMAF_feature': ['vif_scale0', 'vif_scale1', 'vif_scale2', 'vif_scale3', 'adm2', 'motion', ],
4 |
5 | }
6 |
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/resource/feature_param/vmaf_feature_v6.py:
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1 | feature_dict = {
2 |
3 | 'VMAF_feature': ['vif_scale0', 'vif_scale1', 'vif_scale2', 'vif_scale3', 'adm2', 'motion2', ],
4 |
5 | }
6 |
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/resource/model_param/5PL_v1.py:
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1 | model_type = "5PL"
2 | model_param_dict = {
3 | # ==== preprocess: normalize each feature ==== #
4 | # 'norm_type':'none',
5 | 'norm_type': 'clip_0to1', # rescale to within [0, 1]
6 |
7 | # ==== postprocess: clip final quality score ==== #
8 | 'score_clip':[0.0, 100.0], # clip to within [0, 100]
9 | }
10 |
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/resource/model_param/libsvmnusvr_v1.py:
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1 | model_type = "LIBSVMNUSVR"
2 | model_param_dict = {
3 |
4 | # ==== preprocess: normalize each feature ==== #
5 | # 'norm_type': 'none', # default: do nothing
6 | 'norm_type': 'clip_0to1', # rescale to within [0, 1]
7 | # 'norm_type': 'clip_minus1to1', # rescale to within [-1, 1]
8 | # 'norm_type': 'normalize', # rescale to mean zero and std one
9 |
10 | # ==== postprocess: clip final quality score ==== #
11 | # 'score_clip': None, # default: do nothing
12 | 'score_clip': [0.0, 100.0], # clip to within [0, 100]
13 |
14 | # ==== libsvmnusvr parameters ==== #
15 |
16 | # 'gamma': 0.0, # default
17 | 'gamma': 0.1, # vmafv1
18 |
19 | # 'C': 1.0, # default
20 | 'C': 3.1, # vmafv1
21 |
22 | # 'nu': 0.5, # default
23 | 'nu': 0.9, # vmafv1
24 | }
25 |
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/resource/model_param/libsvmnusvr_v2.py:
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1 | model_type = "LIBSVMNUSVR"
2 | model_param_dict = {
3 |
4 | # ==== preprocess: normalize each feature ==== #
5 | # 'norm_type': 'none', # default: do nothing
6 | 'norm_type': 'clip_0to1', # rescale to within [0, 1]
7 | # 'norm_type': 'clip_minus1to1', # rescale to within [-1, 1]
8 | # 'norm_type': 'normalize', # rescale to mean zero and std one
9 |
10 | # ==== postprocess: clip final quality score ==== #
11 | # 'score_clip': None, # default: do nothing
12 | 'score_clip': [0.0, 100.0], # clip to within [0, 100]
13 |
14 | # ==== libsvmnusvr parameters ==== #
15 |
16 | # 'gamma': 0.0, # default
17 | 'gamma': 0.05, # vmafv2
18 |
19 | # 'C': 1.0, # default
20 | 'C': 4.0, # vmafv2
21 |
22 | # 'nu': 0.5, # default
23 | 'nu': 0.9, # vmafv2
24 | }
25 |
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/resource/model_param/libsvmnusvr_v3.py:
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1 | model_type = "LIBSVMNUSVR"
2 | model_param_dict = {
3 |
4 | # ==== preprocess: normalize each feature ==== #
5 | # 'norm_type': 'none', # default: do nothing
6 | 'norm_type': 'clip_0to1', # rescale to within [0, 1]
7 | # 'norm_type': 'clip_minus1to1', # rescale to within [-1, 1]
8 | # 'norm_type': 'normalize', # rescale to mean zero and std one
9 |
10 | # ==== postprocess: clip final quality score ==== #
11 | # 'score_clip': None, # default: do nothing
12 | 'score_clip': [0.0, 100.0], # clip to within [0, 100]
13 |
14 | # ==== libsvmnusvr parameters ==== #
15 |
16 | # 'gamma': 0.0, # default
17 | 'gamma': 0.05, # vmafv2
18 |
19 | # 'C': 1.0, # default
20 | 'C': 4.0, # vmafv2
21 |
22 | # 'nu': 0.5, # default
23 | 'nu': 0.9, # vmafv2
24 | }
25 |
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/resource/model_param/randomforest_v1.py:
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1 | model_type = "RANDOMFOREST"
2 | model_param_dict = {
3 |
4 | # ==== preprocess: normalize each feature ==== #
5 | 'norm_type':'none', # default: do nothing - won't matter to random forest
6 |
7 | # ==== postprocess: clip final quality score
8 | # 'score_clip':None, # default: do nothing
9 | 'score_clip':[0.0, 100.0], # clip to within [0, 100]
10 |
11 | # ==== randomforest parameters ==== #
12 |
13 | 'n_estimators':10, # default
14 |
15 | 'criterion':'mse', # default
16 |
17 | 'max_depth':None, # default
18 |
19 | # 'random_state':None, # default: random
20 | 'random_state':0, # make result deterministic
21 |
22 | }
23 |
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/resource/param/vmaf_v1.py:
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1 | feature_dict = {
2 |
3 | 'VMAF_feature': ['vif', 'adm', 'motion', 'ansnr'],
4 |
5 | }
6 |
7 | model_type = "LIBSVMNUSVR"
8 | model_param_dict = {
9 |
10 | # ==== preprocess: normalize each feature ==== #
11 | # 'norm_type': 'none', # default: do nothing
12 | 'norm_type': 'clip_0to1', # rescale to within [0, 1]
13 | # 'norm_type': 'clip_minus1to1', # rescale to within [-1, 1]
14 | # 'norm_type': 'normalize', # rescale to mean zero and std one
15 |
16 | # ==== postprocess: clip final quality score ==== #
17 | # 'score_clip': None, # default: do nothing
18 | 'score_clip': [0.0, 100.0], # clip to within [0, 100]
19 |
20 | # ==== libsvmnusvr parameters ==== #
21 |
22 | # 'gamma': 0.0, # default
23 | 'gamma': 0.1, # vmafv1
24 |
25 | # 'C': 1.0, # default
26 | 'C': 3.1, # vmafv1
27 |
28 | # 'nu': 0.5, # default
29 | 'nu': 0.9, # vmafv1
30 | }
31 |
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/resource/param/vmaf_v2.py:
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1 | feature_dict = {
2 |
3 | 'VMAF_feature': ['vif_scale0', 'vif_scale1', 'vif_scale2', 'vif_scale3', 'adm2', 'motion', 'ansnr', ],
4 |
5 | }
6 |
7 | model_type = "LIBSVMNUSVR"
8 | model_param_dict = {
9 |
10 | # ==== preprocess: normalize each feature ==== #
11 | # 'norm_type': 'none', # default: do nothing
12 | 'norm_type': 'clip_0to1', # rescale to within [0, 1]
13 | # 'norm_type': 'clip_minus1to1', # rescale to within [-1, 1]
14 | # 'norm_type': 'normalize', # rescale to mean zero and std one
15 |
16 | # ==== postprocess: clip final quality score ==== #
17 | # 'score_clip': None, # default: do nothing
18 | 'score_clip': [0.0, 100.0], # clip to within [0, 100]
19 |
20 | # ==== libsvmnusvr parameters ==== #
21 |
22 | # 'gamma': 0.0, # default
23 | 'gamma': 0.05, # vmafv2
24 |
25 | # 'C': 1.0, # default
26 | 'C': 4.0, # vmafv2
27 |
28 | # 'nu': 0.5, # default
29 | 'nu': 0.9, # vmafv2
30 | }
31 |
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/resource/param/vmaf_v3.py:
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1 | feature_dict = {
2 |
3 | 'VMAF_feature': ['vif_scale0', 'vif_scale1', 'vif_scale2', 'vif_scale3', 'adm2', 'motion', ],
4 |
5 | }
6 |
7 | model_type = "LIBSVMNUSVR"
8 | model_param_dict = {
9 |
10 | # ==== preprocess: normalize each feature ==== #
11 | # 'norm_type': 'none', # default: do nothing
12 | 'norm_type': 'clip_0to1', # rescale to within [0, 1]
13 | # 'norm_type': 'clip_minus1to1', # rescale to within [-1, 1]
14 | # 'norm_type': 'normalize', # rescale to mean zero and std one
15 |
16 | # ==== postprocess: clip final quality score ==== #
17 | # 'score_clip': None, # default: do nothing
18 | 'score_clip': [0.0, 100.0], # clip to within [0, 100]
19 |
20 | # ==== libsvmnusvr parameters ==== #
21 |
22 | # 'gamma': 0.0, # default
23 | 'gamma': 0.05, # vmafv3
24 |
25 | # 'C': 1.0, # default
26 | 'C': 4.0, # vmafv3
27 |
28 | # 'nu': 0.5, # default
29 | 'nu': 0.9, # vmafv3
30 | }
31 |
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/resource/param/vmaf_v4.py:
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1 | feature_dict = {
2 |
3 | 'VMAF_feature': ['vif_scale0', 'vif_scale1', 'vif_scale2', 'vif_scale3', 'adm2', 'motion',],
4 |
5 | }
6 |
7 | model_type = "LIBSVMNUSVR"
8 | model_param_dict = {
9 |
10 | # ==== preprocess: normalize each feature ==== #
11 | # 'norm_type': 'none', # default: do nothing
12 | 'norm_type': 'clip_0to1', # rescale to within [0, 1]
13 | # 'norm_type': 'clip_minus1to1', # rescale to within [-1, 1]
14 | # 'norm_type': 'normalize', # rescale to mean zero and std one
15 |
16 | # ==== postprocess: clip final quality score ==== #
17 | # 'score_clip': None, # default: do nothing
18 | 'score_clip': [0.0, 100.0], # clip to within [0, 100]
19 |
20 | # ==== libsvmnusvr parameters ==== #
21 |
22 | # 'gamma': 0.0, # default
23 | 'gamma': 0.05, # vmaf_v3, vmaf_v4
24 |
25 | # 'C': 1.0, # default
26 | 'C': 4.0, # vmaf_v4
27 |
28 | # 'nu': 0.5, # default
29 | 'nu': 0.9, # vmafv4
30 | }
31 |
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/resource/param/vmaf_v6.py:
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1 | feature_dict = {
2 |
3 | 'VMAF_feature': ['vif_scale0', 'vif_scale1', 'vif_scale2', 'vif_scale3',
4 | 'adm2', 'motion2',],
5 |
6 | }
7 |
8 | model_type = "LIBSVMNUSVR"
9 | model_param_dict = {
10 |
11 | # ==== preprocess: normalize each feature ==== #
12 | # 'norm_type': 'none', # default: do nothing
13 | 'norm_type': 'clip_0to1', # rescale to within [0, 1]
14 | # 'norm_type': 'clip_minus1to1', # rescale to within [-1, 1]
15 | # 'norm_type': 'normalize', # rescale to mean zero and std one
16 |
17 | # ==== postprocess: clip final quality score ==== #
18 | # 'score_clip': None, # default: do nothing
19 | 'score_clip': [0.0, 100.0], # clip to within [0, 100]
20 |
21 | # ==== postprocess: transform final quality score ==== #
22 | 'score_transform': {'p0':1.70674692, 'p1':1.72643844, 'p2':-0.00705305, 'out_gte_in':'true'}, # laptop vs. mobile transform
23 |
24 | # ==== libsvmnusvr parameters ==== #
25 |
26 | 'gamma': 0.04,
27 | 'C': 4.0,
28 | 'nu': 0.9,
29 | }
30 |
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/resource/param/vmaf_v6_bootstrap.py:
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1 | feature_dict = {
2 |
3 | 'VMAF_feature': ['vif_scale0', 'vif_scale1', 'vif_scale2', 'vif_scale3',
4 | 'adm2', 'motion2',],
5 |
6 | }
7 |
8 | model_type = "BOOTSTRAP_LIBSVMNUSVR"
9 | model_param_dict = {
10 |
11 | # ==== preprocess: normalize each feature ==== #
12 | # 'norm_type': 'none', # default: do nothing
13 | 'norm_type': 'clip_0to1', # rescale to within [0, 1]
14 | # 'norm_type': 'clip_minus1to1', # rescale to within [-1, 1]
15 | # 'norm_type': 'normalize', # rescale to mean zero and std one
16 |
17 | # ==== postprocess: clip final quality score ==== #
18 | # 'score_clip': None, # default: do nothing
19 | 'score_clip': [0.0, 100.0], # clip to within [0, 100]
20 |
21 | # ==== postprocess: transform final quality score ==== #
22 | 'score_transform': {'p0':1.70674692, 'p1':1.72643844, 'p2':-0.00705305, 'out_gte_in':'true'}, # laptop vs. mobile transform
23 |
24 | # ==== libsvmnusvr parameters ==== #
25 |
26 | 'gamma': 0.04,
27 | 'C': 4.0,
28 | 'nu': 0.9,
29 |
30 | # ==== bootstrap parameters ==== #
31 |
32 | 'num_models': 21, # this leads to 20 bootstrapped models being trained
33 | }
34 |
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/resource/param/vmaf_v6_residue_bootstrap.py:
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1 | feature_dict = {
2 |
3 | 'VMAF_feature': ['vif_scale0', 'vif_scale1', 'vif_scale2', 'vif_scale3',
4 | 'adm2', 'motion2',],
5 |
6 | }
7 |
8 | model_type = "RESIDUEBOOTSTRAP_LIBSVMNUSVR"
9 | model_param_dict = {
10 |
11 | # ==== preprocess: normalize each feature ==== #
12 | # 'norm_type': 'none', # default: do nothing
13 | 'norm_type': 'clip_0to1', # rescale to within [0, 1]
14 | # 'norm_type': 'clip_minus1to1', # rescale to within [-1, 1]
15 | # 'norm_type': 'normalize', # rescale to mean zero and std one
16 |
17 | # ==== postprocess: clip final quality score ==== #
18 | # 'score_clip': None, # default: do nothing
19 | 'score_clip': [0.0, 100.0], # clip to within [0, 100]
20 |
21 | # ==== postprocess: transform final quality score ==== #
22 | 'score_transform': {'p0':1.70674692, 'p1':1.72643844, 'p2':-0.00705305, 'out_gte_in':'true'}, # laptop vs. mobile transform
23 |
24 | # ==== libsvmnusvr parameters ==== #
25 |
26 | 'gamma': 0.04,
27 | 'C': 4.0,
28 | 'nu': 0.9,
29 |
30 | # ==== bootstrap parameters ==== #
31 |
32 | 'num_models': 21, # this leads to 20 bootstrapped models being trained
33 | }
34 |
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/resource/param/vmaf_v7_bootstrap.py:
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1 | feature_dict = {
2 |
3 | 'VMAF_feature': ['vif_scale0', 'vif_scale1', 'vif_scale2', 'vif_scale3',
4 | 'adm2', 'motion2',],
5 |
6 | }
7 |
8 | model_type = "BOOTSTRAP_LIBSVMNUSVR"
9 | model_param_dict = {
10 |
11 | # ==== preprocess: normalize each feature ==== #
12 | # 'norm_type': 'none', # default: do nothing
13 | 'norm_type': 'clip_0to1', # rescale to within [0, 1]
14 | # 'norm_type': 'clip_minus1to1', # rescale to within [-1, 1]
15 | # 'norm_type': 'normalize', # rescale to mean zero and std one
16 |
17 | # ==== postprocess: clip final quality score ==== #
18 | # 'score_clip': None, # default: do nothing
19 | 'score_clip': [0.0, 100.0], # clip to within [0, 100]
20 |
21 | # ==== postprocess: transform final quality score ==== #
22 | 'score_transform': {'p0':1.70674692, 'p1':1.72643844, 'p2':-0.00705305, 'out_gte_in':'true'}, # laptop vs. mobile transform
23 |
24 | # ==== libsvmnusvr parameters ==== #
25 |
26 | 'gamma': 0.04,
27 | 'C': 4.0,
28 | 'nu': 0.9,
29 |
30 | # ==== bootstrap parameters ==== #
31 |
32 | 'num_models': 101, # this leads to 100 bootstrapped models being trained
33 | }
34 |
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/resource/param/vmaf_v8.py:
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1 | feature_dict = {
2 |
3 | 'VMAF_integer_feature': ['vif_scale0', 'vif_scale1', 'vif_scale2', 'vif_scale3',
4 | 'adm2', 'motion2',],
5 |
6 | }
7 |
8 | model_type = "LIBSVMNUSVR"
9 | model_param_dict = {
10 |
11 | # ==== preprocess: normalize each feature ==== #
12 | # 'norm_type': 'none', # default: do nothing
13 | 'norm_type': 'clip_0to1', # rescale to within [0, 1]
14 | # 'norm_type': 'clip_minus1to1', # rescale to within [-1, 1]
15 | # 'norm_type': 'normalize', # rescale to mean zero and std one
16 |
17 | # ==== postprocess: clip final quality score ==== #
18 | # 'score_clip': None, # default: do nothing
19 | 'score_clip': [0.0, 100.0], # clip to within [0, 100]
20 |
21 | # ==== postprocess: transform final quality score ==== #
22 | 'score_transform': {'p0':1.70674692, 'p1':1.72643844, 'p2':-0.00705305, 'out_gte_in':'true'}, # laptop vs. mobile transform
23 |
24 | # ==== libsvmnusvr parameters ==== #
25 |
26 | 'gamma': 0.04,
27 | 'C': 4.0,
28 | 'nu': 0.9,
29 | }
30 |
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/resource/param/vmaf_v8_bootstrap.py:
--------------------------------------------------------------------------------
1 | feature_dict = {
2 |
3 | 'VMAF_integer_feature': ['vif_scale0', 'vif_scale1', 'vif_scale2', 'vif_scale3',
4 | 'adm2', 'motion2',],
5 |
6 | }
7 |
8 | model_type = "BOOTSTRAP_LIBSVMNUSVR"
9 | model_param_dict = {
10 |
11 | # ==== preprocess: normalize each feature ==== #
12 | # 'norm_type': 'none', # default: do nothing
13 | 'norm_type': 'clip_0to1', # rescale to within [0, 1]
14 | # 'norm_type': 'clip_minus1to1', # rescale to within [-1, 1]
15 | # 'norm_type': 'normalize', # rescale to mean zero and std one
16 |
17 | # ==== postprocess: clip final quality score ==== #
18 | # 'score_clip': None, # default: do nothing
19 | 'score_clip': [0.0, 100.0], # clip to within [0, 100]
20 |
21 | # ==== postprocess: transform final quality score ==== #
22 | 'score_transform': {'p0':1.70674692, 'p1':1.72643844, 'p2':-0.00705305, 'out_gte_in':'true'}, # laptop vs. mobile transform
23 |
24 | # ==== libsvmnusvr parameters ==== #
25 |
26 | 'gamma': 0.04,
27 | 'C': 4.0,
28 | 'nu': 0.9,
29 |
30 | # ==== bootstrap parameters ==== #
31 |
32 | 'num_models': 101, # this leads to 100 bootstrapped models being trained
33 | }
34 |
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/unittest:
--------------------------------------------------------------------------------
1 | #!/usr/bin/env sh
2 |
3 | if [ -z "$1" ]; then
4 | pattern='*_test.py'
5 | else
6 | pattern="$1"
7 | fi
8 |
9 | PYTHONPATH=python python3 -m unittest discover -v -s python/test/ -p $pattern
10 |
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/workspace/checkpoints_dir/.gitignore:
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1 | # Ignore everything in this directory
2 | *
3 | # Except this file
4 | !.gitignore
5 |
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/workspace/dataset/.gitignore:
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1 | # Ignore everything in this directory
2 | *
3 | # Except this file
4 | !.gitignore
5 |
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/workspace/encode/.gitignore:
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1 | # Ignore everything in this directory
2 | *
3 | # Except this file
4 | !.gitignore
5 |
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/workspace/model/.gitignore:
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1 | # Ignore everything in this directory
2 | *
3 | # Except this file
4 | !.gitignore
5 |
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/workspace/model_param/.gitignore:
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1 | # Ignore everything in this directory
2 | *
3 | # Except this file
4 | !.gitignore
5 |
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/workspace/output/.gitignore:
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1 | # Ignore everything in this directory
2 | *
3 | # Except this file
4 | !.gitignore
5 |
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/workspace/result_store_dir/.gitignore:
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1 | # Ignore everything in this directory
2 | *
3 | # Except this file
4 | !.gitignore
5 |
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/workspace/workdir/.gitignore:
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1 | # Ignore everything in this directory
2 | *
3 | # Except this file
4 | !.gitignore
5 |
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