Perceptual video quality assessment based on multi-method fusion.
compute_vmaf()
, header file compute_vmaf.h
.vmaf_cuda_*
APIs, header file vmaf_cuda.h
.Release candidate for upcoming libvmaf v3.0.0.
This is a minor release with some CAMBI extensions and speed-ups and adding it to AOM CTC v3, as well as a few minor fixes/cleanups.
This is a minor release to address a few last minute items for the initial AOM CTC.
--aom_ctc v1.0
has been updated to use these clipping options according to the AOM CTC. (https://github.com/Netflix/vmaf/pull/802).This is a minor release for the initial AOM CTC. Support has been added for templated feature names. While this is a general purpose software feature, templated feature names are immediately useful for simultaneous computation of VMAF and VMAF NEG since the two metrics rely on slightly different VIF/ADM variations. Global feature overrides via the --feature
flag are no longer supported, instead individual models can have their features overloaded individually, the syntax for which is as follows:
--model version=vmaf_v0.6.1:vif.vif_enhn_gain_limit=1.0:adm.adm_enhn_gain_limit=1.0
New features:
vmaf_model_feature_overload()
.--aom_ctc v1.0
preset, encompassing all metrics specified by the AOM CTC.This is a major release with an updated and overhauled libvmaf
API. The vmafossexec
command line tool has been deprecated and replaced with the more flexible and powerful vmaf
tool. For an introduction to the libvmaf v2.0.0
API as well as an explanation of the new vmaf
tool, please see the following README
files: libvmaf
, vmaf
. Also part of this release is a new fixed-point and x86 SIMD-optimized (AVX2, AVX-512) implementation that achieves ~2x speed up compared to the previous floating-point version.
New features:
Fixed bugs:
(Updates since 1.5.1)
Fixed bugs:
New features: