mirror of
https://github.com/unclshura/ABStemPlayer.git
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195 lines
4.0 KiB
Markdown
195 lines
4.0 KiB
Markdown
# ABStemPlayer
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ABStemPlayer is a Avalonia 12 audio player application built with .NET, designed for
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real‑time media processing, modern UI rendering, and cross‑platform deployment.
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The project focuses on predictable performance, clean architecture, and production‑grade
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engineering practices.
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## Features
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- Stem splitting and mixing
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- Drums
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- Bass
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- Other
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- Vocals
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- Guitar
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- Piano
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- Turn each stem on and off independently
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- Pan stems left or right
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- Audio player with A/B looping and speed control
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**Techy stuff:**
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- .NET 10
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- Cross‑platform UI built with Avalonia 12
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- ONNX Runtime integration for ML inference
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- htdemucs_6s.onnx for stem splitting
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> YOU HAVE TO DOWNLOAD htdemucs_6s.onnx YOURSELF DUE TO GITHUB SIZE LIMITATIONS
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> https://huggingface.co/StemSplitio/htdemucs-6s-onnx/blob/main/htdemucs_6s.onnx
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## Requirements
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- .NET 10 or later
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- Avalonia 12
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- ONNX Runtime (CPU or GPU)
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- FFmpeg
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# HTDemucs 6‑Stem ONNX Model Guide
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## Overview
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**HTDemucs‑6s** is a state‑of‑the‑art music source separation model capable of splitting a stereo mix into **six distinct stems**:
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- Drums
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- Bass
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- Vocals
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- Guitar
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- Piano
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- Other
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The model is designed for **high‑fidelity separation**, **low artifacts**, and **robust performance** on modern CPU inference engines.
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---
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## Required Model File
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```
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File Name: htdemucs_6s.onnx
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Placement: Place the model inside your application's data directory: /Data/htdemucs_6s.onnx
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```
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### Why this model
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This ONNX export is specifically built for:
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- **CPU inference**
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- **float32 audio processing**
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- **6‑stem output**
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- **44.1 kHz stereo input**
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Using any other Demucs variant (4‑stem, hybrid, GPU‑optimized, etc.) will result in incompatible tensor shapes.
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---
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## Model Input Specification
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### Input Tensor Name
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```
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mix
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```
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### Input Shape
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```
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[1, 2, N]
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```
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Where:
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- `1` = batch size
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- `2` = stereo channels
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- `N` = number of audio samples in the segment
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### Audio Requirements
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- **Sample rate:** 44,100 Hz
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- **Channels:** Stereo
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- **Format:** float32 PCM
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- **Normalization:** Standard waveform scaling
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---
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## Model Output Specification
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### Output Tensor Name
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```
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stems
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```
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### Output Shape
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```
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[1, 6, 2, N]
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```
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Where:
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- `1` = batch
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- `6` = stems
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- `2` = stereo
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- `N` = same segment length as input
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Each stem is returned as a stereo float32 waveform.
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---
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## Technical Details
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HTDemucs‑6s is based on the **Hybrid Demucs architecture**, combining:
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- Convolutional encoder/decoder
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- Multi‑band processing
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- Transformer blocks for long‑range context
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- Overlap‑add reconstruction
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- Six‑head output layer
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This design allows the model to preserve transients, maintain stereo imaging, and reduce musical bleed between stems.
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### Supported ONNX Operations
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The model uses only standard ONNX ops, including:
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- Conv / ConvTranspose
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- LayerNorm / GroupNorm
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- Multi‑Head Attention
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- GELU / ReLU
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- Reshape / Transpose
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- Basic arithmetic ops
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This ensures full compatibility with CPU execution providers.
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---
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## Downloading the Correct Model
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Make sure you download the **HTDemucs 6‑stem ONNX export**, not:
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- 4‑stem Demucs
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- Hybrid Demucs v3/v4 PyTorch checkpoints
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- GPU‑optimized ONNX models
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- Models with different sample rates
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If you need a verified download link, choose:
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- **https://huggingface.co/StemSplitio/htdemucs-6s-onnx/blob/main/htdemucs_6s.onnx**
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---
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## Verification
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To ensure you have the correct model, check:
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| Property | Expected |
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|---------|----------|
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| File name | `htdemucs_6s.onnx` |
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| Input tensor | `mix` |
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| Input shape | `[1, 2, N]` |
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| Output tensor | `stems` |
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| Output shape | `[1, 6, 2, N]` |
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| Sample rate | 44.1 kHz |
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| Channels | Stereo |
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| Stems | 6 |
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| Execution | CPU |
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SHA256: `48F8E84945579F8AB340E083339E9221E03785DBE733A52C388200B6D3CA779A`
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---
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# Copyright notices
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## Icons
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```
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COLLECTION: Gentlecons Interface Icons
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LICENSE: CC Attribution License
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AUTHOR: Konstantin Filatov
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``` |