Self-hosted Opus Clip alternative — reels.biba.live

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Sebastjan Artič 0513768466 Live preview in Edit modal — fast low-q clip render User feedback: 'dejstvo je da trajna ker more najprej zrenderirat? to traja? za to bi rabili hudo mašino al?' Solution before GPU upgrade: live preview that renders just the selected range as low-quality 480p clip. ~2-3s instead of ~70s full reel render. NEW endpoint: GET /api/preview-clip/{job_id}?start=X&end=Y - ffmpeg fast extract (no reframe, no subtitles, no face tracking) - 480p ultrafast x264 preset, CRF 30 - Cached per job+range (re-clicks are instant) - ~2-3s on CPU Frontend: - '▶ Predvajaj odsek' button now triggers preview-clip render - Shows status: '🎬 Renderiram odsek... (~3s)' - After render: video element switches to preview src - User sees EXACTLY what reel will contain (just without face track) - Subsequent clicks on same range are instant (cached) Workflow: - Drag handles → click '▶ Predvajaj odsek' → 3s wait → see + hear it - Iterate fast: drag → preview → drag → preview - Final '✅ Shrani in re-render' only when satisfied (~70s full render)		2026-04-30 11:56:54 +00:00
app	Live preview in Edit modal — fast low-q clip render	2026-04-30 11:56:54 +00:00
scripts	Edit feature: slider + napis edit + recut endpoint	2026-04-30 10:26:25 +00:00
templates	Live preview in Edit modal — fast low-q clip render	2026-04-30 11:56:54 +00:00
.env.example	Initial: reels clipper app	2026-04-28 15:28:22 +00:00
.gitignore	Initial: reels clipper app	2026-04-28 15:28:22 +00:00
docker-compose.yml	Initial: reels clipper app	2026-04-28 15:28:22 +00:00
Dockerfile	Add Deno runtime for yt-dlp YouTube nsig challenge solving	2026-04-28 16:05:09 +00:00
README.md	Initial: reels clipper app	2026-04-28 15:28:22 +00:00
requirements.txt	ACRCloud auto-recognition: never block uploads, fall back to fingerprinting	2026-04-29 14:24:53 +00:00

README.md

Reels Clipper · biba.live

Self-hosted Opus Clip alternativa za FOLX TV / PTC. Pretvori 16:9 video v 9:16 reels/shorts/tiktok format z auto face tracking, podnapisi (sl/de/en) in avto-detekcijo refrena v glasbenih pesmih.

Features

📤 Drag & drop upload (do 2 GB)
📺 YouTube URL paste (yt-dlp)
🎯 Smart reframe: track (face follow), center, blur (za glasbo)
🎵 Auto-chorus detection (Whisper + energy hibrid)
📝 Burned-in podnapisi (faster-whisper, multi-jezik)
🎨 3 stili podnapisov: reels, yellow (MrBeast), minimal
🔐 HTTP Basic Auth
📊 Real-time progress (Server-Sent Events)
📦 Docker / Coolify ready

Quick start (lokalno)

docker compose up --build
# odpri http://localhost:8000

Default login: sebastjan / nastavi AUTH_PASS v .env.

Coolify deploy

V Coolify ustvari nov projekt → Docker Compose iz tega repoja
Domena: reels.biba.live

Env vars:

AUTH_USER=sebastjan
AUTH_PASS=<močno geslo>
MAX_UPLOAD_MB=2000

Volume reels_data se ustvari avtomatsko
Deploy → Coolify postavi Traefik reverse proxy + SSL via Let's Encrypt

Pipeline

Upload / YouTube
       ↓
[ yt_download.py ]    ← samo če YouTube
       ↓
[ find_chorus.py ]    ← samo če auto_chorus=true (Whisper + RMS analiza)
       ↓
[ reframe.py ]        ← 16:9 → 9:16 (track / center / blur)
       ↓
[ subtitle.py ]       ← Whisper transkripcija + burn-in
       ↓
   reel.mp4

API

POST /api/upload — multipart file upload, vrne job_id
POST /api/youtube — JSON {url, mode, lang, ...}
POST /api/process — start processing za uploaded job
GET /api/jobs — list vseh
GET /api/jobs/{id} — status
GET /api/stream/{id} — SSE stream progress
GET /api/download/{id} — final reel
DELETE /api/jobs/{id} — pobriši

Dependencies

FFmpeg (system)
faster-whisper (transkripcija)
OpenCV (face detection)
yt-dlp (YouTube)
FastAPI + uvicorn (server)