r/AV1

I don't actually know how to code, but I got fed up with current video editing options:

• NLEs (Premiere/Resolve): Too slow just to cut and stitch videos.
• Standard Lossless Trimming (ffmpeg -c copy): Imprecise (cuts only on keyframes).
• Existing Smart-Cutters: Re-encode boundary frames using static CRF, which kept making my 30-second cuts larger (46mb) in file size than my 1-minute originals (30mb). Why would someone code it in this way?

So I said to myself, why not just alter what smartcut does? So, I spent the last few days using AI (Claude free version) to build a custom PyAV/Python smart-cutting engine to fix this for my own workflow. We ended up hitting a few major breakthroughs. I fed my changes into gemini and talked with it for a long while trying to find out if what I did was actually game changing. It thought so, but I have no idea if it is:

• Player-First Workflow (Movist Pro): I mark cut points (IN and OUT) using Movist Pro's bookmark feature. The script reads the timestamps in the bookmark file and cuts everything headlessly in the background. I'm using this in place of a standard video editing tool (like capcut). It makes timestamp extraction much easier and I can easily add/remove bookmarks.
• Localized Bitrate Matching: Ditched static CRF completely. The engine measures the exact source bitrate of the head and tail keyframes independently and forces x265 / libsvtav1 to match them. No file bloat, no visual seams. File sizes stay small.
• Frame-Accurate AV1 Smart-Cutting: Solved the PyAV level override and timestamp bugs that normally crash AV1 boundary re-encodes. The only issue is self testing. I am currently doing all this on a 2019 Intel MacBook Pro, so it has been annoying to test the final output. I have access to a M3 MacBook Air, but not often. The final cut video works perfectly fine on the M3 Macbook Air, but i get slight lag on the last couple seconds on my Intel MacBook Pro. I am still fixing this slight issue, the AI suggests it will be a simple fix, but it never is.
• Parallel C Extension: Wrote a C module to handle H.265 NAL unit scanning (CRA Type 21 → BLA Type 16), jumping CPU usage on my Intel Mac from 100% (GIL capped) to 600% and eliminating repeated frames at cut points.

I built this purely for my own personal use, but I'm curious: Is there actual demand for a lightweight, frame-accurate AV1/H.265 smart-cutter like this, or is this too niche to bother releasing? I've also built additional functionality for the Movist Pro Media Player. I use this to run the smartcut features.

I am not the most technical when it comes to all of this. The AI did a lot of the heavy lifting, I just pushing it in the correct direction.

EDIT:
I created a github and with the ai's help, i created the zip folder that houses all the relevant files and scripts. As well as a readme that will with most questions you have.

https://github.com/AbdulazizMorad/Smartcut-proof-of-concept

EDIT2:
Github updated and no longer shows a zip file

Body:
Hey everyone,

I wanted to share an open-source batch video encoder and quality assessment tool I’ve been developing called QualiSVT. It's primarily optimized for SVT-AV1 and x265, using FFmpeg or HandBrakeCLI as the backend.

One of my favorite tools is ab-av1, so I implemented a similar Auto-CRF search algorithm inside this GUI. It takes samples from your video and uses binary search/interpolation to find the highest CRF that meets your target quality score, while letting you set a maximum file size limit.

However, instead of relying only on VMAF or XPSNR for quality estimation, I integrated support for newer perceptual metrics: SSIMULACRA2, Butteraugli, and CVVDP. (This is hardware-accelerated using FFVship so it runs relatively fast on the GPU).

Some other useful features included:

• Pre-encode estimations (predicts file size, time, and quality before doing a full encode).
• Post-encode visual validation (automatically extracts the worst, mid, and best frames as WebP images so you can compare them side-by-side).
• Power and energy tracking (hooks into Open Hardware Monitor to log your CPU's W and Wh usage during the encode).
• A solid auto-resume feature if your PC crashes or loses power.

If anyone is interested in testing it out or looking at the code, you can find it on GitHub here: [Insert your GitHub link here]

Feedback and bug reports are welcome.

https://github.com/Cimorq/QualiSVT

I've starting using AV1 recently since learning about the SVT-AV1-HDR fork (I was very unimpressed with mainline SVT). I've generally been getting better results than HEVC with this fork. I'm currently trying to encode a high quality 4K HDR video to 1080p to save space. For grainy videos, I generally aim for 10-15Mbps with HEVC. I haven't done that many encodes with AV1 yet, but I've seen similar or better quality at 8-12Mbps with the few that I've done. On this one that I'm working on right now, It looks really good at 10Mbps except that I'm seeing artifacts on some of the edges. Particularly edges that move slowly across a grainy background. In the attached picture, it's kinda hard to see the artifacts, but it's more obvious when the video is going because there's no grain moving in that area and it follows the character as they move like it's attached. Normally I would just increase the bitrate until I can't see it anymore, but in this case even doubling the bitrate to 20Mbps doesn't fix it which is a pretty high bitrate for 1080p AV1/HEVC.

I'm using SVT-AV1-HDR 10bit, tune:grain, preset 4-2, ABR. I'm not interested in using grain synthesis or anything that's going to remove the original grain. If anyone knows any relevant settings that can help with this, please let me know.

Человеки, здорова. Разберем этот ваш AV2 по понятиям и науке.

С точки зрения фундаментальной компрессии данных, перед нами — абсолютный триумф инженерной мысли. А если по-простому: кодек получился фартовый, упаковывает информацию наглухо, комар носа не подточит.

Ниже представлены ключевые детерминанты его превосходства.

1. Беспрецедентная плотность архивации (Экономия битрейта)

Фёдор: Математическая оптимизация энтропийного кодирования позволила снизить избыточность сигнала на 30% относительно AV1.

Васян: Век воли не видать, эта залупа умудряется ужать тяжелый видос в такую крохотную щель, что провайдеры связи просто плачут от счастья. Объемы тают, как сахар в кипятке.

2. Макроструктурная эволюция типа блоки 256×256

Фёдор: Экстраполяция размеров суперблоков до дискретизации 256×256 минимизирует накладные расходы на кодирование однородных поверхностей.

Васян: Раньше картинку резали мелкой соломкой, а теперь делят конкретными, авторитетными кусками. На больших экранах теперь никакой дерибасовской размытости — всё четко, без шума и пыли.

3. Глубокий ретроспективный анализ типа предсказание по 7 кадрам

Фёдор: Мультиреференсный интерполяционный алгоритм верифицирует аж семь временных слоев для идеального интеркадрового предсказания.

Васян: Кодек у нас с феноменальной памятью. Он помнит всё, что было семь шагов назад, и наперед знает, куда пиксель дернется. Короче, фуфло и мыло мимо кассы не пропустит.

4. Мультистриминг и синергия типа разделение экрана

Фёдор: Нативная поддержка интеграции гетерогенных видеопотоков в рамках единой транспортной сессии.

Васян: Можно в одну камеру загнать сразу несколько картинок, и они не будут грызться за пайку битрейта. Каждому свое, всё по справедливости и в одном флаконе.

Сводный вердикт научного консилиума

Резюмируя: вещь получилась авторитетная, профессура одобряет. Да, сейчас этот софт жрет ресурсы процессора так, будто у него сто лет голодовки было. Но когда подгонят аппаратное железо — кодек пойдет в массы как хозяин жизни.

Консилиум окончен, чифир остывает.