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AudioEditingCode_Demo.ipynb
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# AudioEditingCode Colab Demo
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This notebook demonstrates how to use the `AudioEditingCode` repository in Google Colab.
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## 1. Clone the repository
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```bash
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!git clone https://github.com/HilaManor/AudioEditingCode.git
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%cd AudioEditingCode
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```
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## 2. Install dependencies
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```bash
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!pip install -r requirements.txt
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```
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## 3. Demo Usage
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Here you can add examples of how to use the code. You might need to download some audio files for demonstration.
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### Download example audio
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```bash
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!wget https://www.soundhelix.com/examples/mp3/SoundHelix-Song-1.mp3 -O input_audio.mp3
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```
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### Text-Based Editing Example
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This example uses `main_run.py` for text-based audio editing. You will need a Hugging Face token to use models like Stable Audio Open. Please visit [Hugging Face](https://huggingface.co/settings/tokens) to get your token and replace `<YOUR_HF_TOKEN>` below.
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```python
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import os
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# Replace with your actual Hugging Face token
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os.environ["HF_TOKEN"] = "<YOUR_HF_TOKEN>"
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!python code/main_run.py \
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--cfg_tar 1.5 \
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--cfg_src 0.5 \
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--init_aud input_audio.mp3 \
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--target_prompt "a dog barking" \
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--tstart 100 \
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--model_id audioldm \
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--results_path results_text_based
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```
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### Unsupervised Editing Example
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First, extract the principal components:
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```bash
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!python code/main_pc_extract_inv.py \
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--init_aud input_audio.mp3 \
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--model_id audioldm \
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--results_path results_unsupervised_extract \
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--drift_start 0 \
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--drift_end 200 \
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--n_evs 5
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```
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Then, apply the principal components:
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```bash
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!python code/main_pc_apply_drift.py \
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--extraction_path results_unsupervised_extract/input_audio_audioldm_inversion_data.pt \
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--drift_start 0 \
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--drift_end 200 \
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--amount 1.0 \
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--evs 0
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```
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