A dependency-free (pure standard-library) Python tool that connects an objective PICTURE metric (VMAF) to a session QoE score. Given a session described segment by segment (the played rendition mapped to its measured VMAF) plus the rebuffering and switching that happened, it computes: (1) the DELIVERED-vs-ENCODED gap — top-rung VMAF vs time-weighted PLAYED VMAF; (2) the ABR QoE OBJECTIVE (a real published objective, MPC/Pensieve) QoE = Σq − μ·Σstall − Σ|Δq| in linear and log variants, mapping VM
Download free PDF
The handbook · 7 volumes
Fora Soft Video Engineering Handbook
This picture-quality-to-QoE calculator links per-segment VMAF to a session QoE score, showing the gap between encoded and delivered picture quality alongside stalls and switches. Our seven-volume handbook covers the video stack end to end; Volume 3 is the place to start for ABR rung selection, rebuffering and QoE monitoring, with Volume 1 on quality metrics and encoding and Volume 6 on AI models. Written by Nikolay Sapunov, CEO at Fora Soft.
Need to prove whether viewers actually see the quality your encoder produces?
Share a sample of session logs and your ladder, and we will measure the delivered-versus-encoded gap and show which ABR changes close it. 250+ video products shipped since 2005.
You get a realistic estimate, technical recommendations and next steps. Free, no obligations.
