SSbump Generator: Quick Guide to Setup and Use
What it is
SSbump Generator is a tool that produces SSbump-compatible outputs (assumed: signal-shaping or sample-processing artifacts) for integrating into audio/data pipelines. It converts input data into bump-patterned outputs usable in downstream systems.
Quick prerequisites
- OS: Windows 10+ or recent Linux distro
- Dependencies: Python 3.10+, pip, NumPy, soundfile (if audio), or relevant SDK for your format
- Hardware: CPU with SSE support; optional GPU for acceleration
- Files: Input files in WAV, FLAC, or supported data format
Installation (Python example)
- Install Python and pip.
- Create and activate a virtual environment:
Code
python -m venv ssbump-env source ssbump-env/bin/activate# macOS/Linux ssbump-env\Scripts\activate.bat # Windows
- Install package and deps:
Code
pip install ssbump-generator numpy soundfile
Basic usage (CLI)
- Generate from input file:
Code
ssbump-generate –input input.wav –output output.wav –strength 0.8 –pattern default
- Common flags:
- –input / -i: source file
- –output / -o: destination file
- –strength / -s: 0.0–1.0 intensity
- –pattern / -p: pattern name (default, smooth, sharp)
- –rate / -r: sample rate override
Basic usage (Python API)
python
from ssbump import Generator g = Generator(strength=0.8, pattern=‘default’) g.load(‘input.wav’) g.process() g.save(‘output.wav’)
Recommended workflow
- Start with strength 0.3–0.5 and pattern ‘default’.
- Listen and increment strength in 0.1 steps.
- Use A/B comparisons on short segments.
- Batch-process with consistent parameters for a release.
Troubleshooting
- No output: check input path and file format.
- Artifacts/clipping: lower strength or use ‘smooth’ pattern.
- Slow processing: enable GPU or reduce sample rate.
Tips
- Preserve original files; use non-destructive workflow.
- Automate with shell scripts for large batches.
- Test patterns on multiple segments to avoid surprises.
If you want, I can produce a step-by-step beginner walkthrough tailored to your OS and file type.
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