111 lines
2.5 KiB
Markdown
111 lines
2.5 KiB
Markdown

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# Auto Clip 🎧✂️
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Local, offline-friendly **DJ-style album teaser builder** using Python + FFmpeg.
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This repository contains multiple versions of the Auto Clip workflow, each adding more intelligence and DJ-oriented features.
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---
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## 🚦 Roadmap
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See the planned future development here:
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- [V4 Roadmap](V4_ROADMAP.md)
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---
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## 📁 Repository structure
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```
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Auto Clip/
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├── V_1/
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├── V_2/
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├── V_3/
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├── README.md ← this file
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├── README_EN.md
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└── README_DA.md
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```
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- **V_1** — Minimal MVP / proof-of-concept
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- **V_2** — Track selection, best-of mode, DJ ordering
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- **V_3** — Harmonic mixing (Camelot), downbeat-ish snap, 2-pass loudness
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---
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## 📖 Documentation
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Choose your preferred language:
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- 🇬🇧 **English documentation** → [README_EN.md](README_EN.md)
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- 🇩🇰 **Dansk dokumentation** → [README_DA.md](README_DA.md)
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Each language README contains:
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- Full explanation of V_1 / V_2 / V_3
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- Install instructions
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- Usage examples
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- DJ / trance tuning tips
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- Limitations and troubleshooting
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---
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## 🎶 What is Auto Clip?
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Auto Clip scans a folder of audio tracks and automatically creates a **short DJ-style teaser** by:
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- Finding musical highlights
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- Snapping cuts to bar/phrase boundaries
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- Optionally applying harmonic (Camelot) ordering
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- Rendering a smooth teaser with crossfades
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- Exporting WAV + MP3 plus a detailed JSON report
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It is designed for:
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- DJs
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- Producers
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- Album / EP promo teasers
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- Old school trance & electronic music
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Everything runs **locally** — no cloud, no uploads.
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---
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## 🤖 Optional: Ollama integration
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If you run Ollama locally, Auto Clip can optionally generate:
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- README content
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- Promo text (SoMe / YouTube)
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- Tracklists with timestamps
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Recommended model:
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- `llama3.1:8b-instruct-q4_0`
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Ollama is **optional** and not required for audio processing.
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---
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## 🚀 Quick start (example)
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```bash
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cd V_3
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python dj_teaser_v3.py --tracks-dir ./tracks --select all --teaser 60 --bars 2 --preroll-bars 1 --avoid-intro 30 --harmonic
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```
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---
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## 📜 License
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Choose the license that fits your project (MIT is commonly used).
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---
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## ❤️ Credits
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- FFmpeg
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- librosa
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- numpy
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Built for DJs who like automation, control, and clean signal paths.
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