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

Go to file

Sebastjan Artič 7d00730051 Auto-detect language from filename for Scribe (no manual UI selection needed) Problem: Scribe was failing on Slovenian narodno-zabavna songs (Avseniki, Modrijani) because: - User doesn't manually pick language (everything is auto) - Scribe auto-detect had low confidence (0.58) on harmonika-heavy polka - Result: only 37s transcribed instead of full 186s song Solution: detect_language_from_filename() function: - Recognizes 60+ Slovenian artists (Avseniki, Modrijani, Veseli Dolenjci, ...) - Recognizes 30+ German artists (Ben Zucker, Helene Fischer, ...) - Recognizes 20+ Croatian/Serbian artists (Thompson, Severina, Lepa Brena, ...) - Falls back to keyword matching (volim, liebe, srce, herz, ...) - Detects character set (č/ž/š → SL, ä/ö/ü/ß → DE, đ → HR) - Score-based: 5pts for artist match, 1-2pts for keywords/chars When detected, sends language_code to Scribe explicitly: - Avseniki → 'slv' lock → no more half-transcribed songs - Ben Zucker → 'deu' lock → consistent German transcription - User still doesn't need to manually pick anything filename_hint flows: main.py → analyze.py CLI → transcribe_full → Scribe		2026-04-29 12:57:19 +00:00
app	Integrate ElevenLabs Scribe (best multilingual STT 2026)	2026-04-29 12:03:40 +00:00
scripts	Auto-detect language from filename for Scribe (no manual UI selection needed)	2026-04-29 12:57:19 +00:00
templates	Fix preview cutoff + sticky left panel	2026-04-29 10:24:32 +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	Upgrade yt-dlp to nightly for new YouTube nsig algorithm support	2026-04-28 15:48:39 +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)