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

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Sebastjan Artič a5097c5acc Fix first word being cut at clip start ('Žena' problem) Real-world failure: 'Ansambel Saša Avsenika - ŽENA ME TEPE' - Refren starts with 'Žena me tepe' at 78.0s - Scribe's segment boundary: word 'Žena' was end of previous segment (73.9-78.2s) while new segment 'tepe, mi prazni žepe' started at 78.3s - Claude picked clip start = 78.3s (segment boundary) - Fade-in 0.4s on vocal start = inaudible 'Že-' - User hears: '...na me tepe' (cut) Three-part fix: 1. PROMPT: instruct Claude to start clip ~0.3s BEFORE first chorus word (not exactly at it). Concrete example with timing math. 2. POST-LLM EXTENSION: scan corrected_segments for boundary cases: - If clip start falls MID-segment → extend back to segment start - 0.2s - If a previous segment ended within 0.5s of clip start → check if its last word might actually be the first chorus word, extend back to it - Uses word-level timestamps when available (Scribe provides these) 3. FADE-IN: was 0.4s when starting on vocal — too long, audibly cuts first word. Reduced to 0.05s (just click prevention, not audible). Still 0.2s for instrumental intros where fade is musically appropriate. Now 'Žena' will be heard fully — clip starts at ~77.5-77.7s, word starts at 78.0s, plenty of buffer.		2026-04-29 14:47:07 +00:00
app	ACRCloud auto-recognition: never block uploads, fall back to fingerprinting	2026-04-29 14:24:53 +00:00
scripts	Fix first word being cut at clip start ('Žena' problem)	2026-04-29 14:47:07 +00:00
templates	MXF/MPG broadcast format support: handle multichannel audio properly	2026-04-29 14:38:48 +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)