NeoPy commited on
Commit
386a259
·
verified ·
1 Parent(s): d6e21f3

Upload AudioEditingCode_Demo.ipynb

Browse files
Files changed (1) hide show
  1. AudioEditingCode_Demo.ipynb +81 -0
AudioEditingCode_Demo.ipynb ADDED
@@ -0,0 +1,81 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # AudioEditingCode Colab Demo
2
+
3
+ This notebook demonstrates how to use the `AudioEditingCode` repository in Google Colab.
4
+
5
+ ## 1. Clone the repository
6
+
7
+
8
+
9
+ ```bash
10
+ !git clone https://github.com/HilaManor/AudioEditingCode.git
11
+ %cd AudioEditingCode
12
+ ```
13
+
14
+ ## 2. Install dependencies
15
+
16
+
17
+
18
+ ```bash
19
+ !pip install -r requirements.txt
20
+ ```
21
+
22
+ ## 3. Demo Usage
23
+
24
+ Here you can add examples of how to use the code. You might need to download some audio files for demonstration.
25
+
26
+
27
+
28
+ ### Download example audio
29
+
30
+ ```bash
31
+ !wget https://www.soundhelix.com/examples/mp3/SoundHelix-Song-1.mp3 -O input_audio.mp3
32
+ ```
33
+
34
+ ### Text-Based Editing Example
35
+
36
+ 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.
37
+
38
+ ```python
39
+ import os
40
+
41
+ # Replace with your actual Hugging Face token
42
+ os.environ["HF_TOKEN"] = "<YOUR_HF_TOKEN>"
43
+
44
+ !python code/main_run.py \
45
+ --cfg_tar 1.5 \
46
+ --cfg_src 0.5 \
47
+ --init_aud input_audio.mp3 \
48
+ --target_prompt "a dog barking" \
49
+ --tstart 100 \
50
+ --model_id audioldm \
51
+ --results_path results_text_based
52
+ ```
53
+
54
+
55
+
56
+ ### Unsupervised Editing Example
57
+
58
+ First, extract the principal components:
59
+
60
+ ```bash
61
+ !python code/main_pc_extract_inv.py \
62
+ --init_aud input_audio.mp3 \
63
+ --model_id audioldm \
64
+ --results_path results_unsupervised_extract \
65
+ --drift_start 0 \
66
+ --drift_end 200 \
67
+ --n_evs 5
68
+ ```
69
+
70
+ Then, apply the principal components:
71
+
72
+ ```bash
73
+ !python code/main_pc_apply_drift.py \
74
+ --extraction_path results_unsupervised_extract/input_audio_audioldm_inversion_data.pt \
75
+ --drift_start 0 \
76
+ --drift_end 200 \
77
+ --amount 1.0 \
78
+ --evs 0
79
+ ```
80
+
81
+