https://github.com/lucianodato/makeitdrumless
A Python script to automate downloading a YouTube song, removing drums, and generating a backing track for practice or performance.
https://github.com/lucianodato/makeitdrumless
drumless drums music-separation
Last synced: 10 months ago
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A Python script to automate downloading a YouTube song, removing drums, and generating a backing track for practice or performance.
- Host: GitHub
- URL: https://github.com/lucianodato/makeitdrumless
- Owner: lucianodato
- Created: 2025-07-30T20:25:28.000Z (11 months ago)
- Default Branch: main
- Last Pushed: 2025-07-31T19:38:40.000Z (11 months ago)
- Last Synced: 2025-07-31T22:41:37.733Z (11 months ago)
- Topics: drumless, drums, music-separation
- Language: Python
- Homepage:
- Size: 11.7 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# MakeItDrumless
This project allows you to generate drumless tracks from YouTube videos using the SCNet model.
## Project Structure
```
MakeItDrumless/
├── .git/
├── .gitignore
├── README.md
├── requirements.txt
├── checkpoints/ (SCNet model checkpoints)
├── ffmpeg/ (Portable FFmpeg binaries)
├── SCNet/ (SCNet repository - external, for inference)
├── src/
│ ├── __init__.py
│ ├── audio/
│ │ ├── __init__.py
│ │ ├── downloader.py (Handles YouTube audio download)
│ │ └── processing.py (Handles audio mixing and metadata)
│ ├── ffmpeg/
│ │ ├── __init__.py
│ │ └── manager.py (Manages FFmpeg installation)
│ ├── scnet_integration/
│ │ ├── __init__.py
│ │ ├── inference.py (Integrates SCNet inference logic)
│ │ └── repo_manager.py (Manages SCNet repository and checkpoints)
│ └── utils/
│ ├── __init__.py
│ └── spinner.py (Utility for console spinner)
└── temp/ (Temporary files)
└── output/ (Generated drumless tracks)
```
## Setup
1. **Clone the repository:**
```bash
git clone https://github.com/your_username/MakeItDrumless.git
cd MakeItDrumless
```
2. **Create and activate a virtual environment:**
```bash
python -m venv .venv
# On Windows
.venv\Scripts\activate
# On macOS/Linux
source .venv/bin/activate
```
3. **Install dependencies:**
```bash
pip install -r requirements.txt
```
4. **Initial Setup (FFmpeg and SCNet Model):**
The first time you run `main.py`, it will automatically:
* Download and set up a portable FFmpeg (Windows only, otherwise requires manual installation).
* Clone the SCNet repository into the `SCNet/` directory.
* Check for the SCNet model checkpoint (`SCNet-large.th`) and configuration file (`config.yaml`) in the `checkpoints/` directory. You will be prompted to manually download the checkpoint if it's missing.
## Usage
To generate a drumless track from a YouTube video, run the `main.py` script with the YouTube URL as an argument:
```bash
.venv\Scripts\python.exe src/main.py ""
```
**Example:**
```bash
.venv\Scripts\python.exe src/main.py "https://www.youtube.com/watch?v=dQw4w9WgXcQ"
```
## Output
The generated drumless track (MP3 format) will be saved in the `output/` directory. Separated stems (vocals, bass, other) will be saved in `separated_scnet//`.
## Troubleshooting
* **FFmpeg not found:** If you are not on Windows, ensure FFmpeg is installed and added to your system's PATH.
* **SCNet Checkpoint Missing:** Follow the instructions in the console to manually download the `SCNet-large.th` file.
* **Dependency Issues:** Ensure all packages in `requirements.txt` are installed.