Zuletzt geändert von René Schmidt am 2025/03/26 14:55

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1 conda create -n openvoice python=3.9
2 conda activate openvoice
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4
5 git clone [[https:~~/~~/github.com/myshell-ai/openVoice.git>>https://github.com/myshell-ai/openVoice.git]]
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7 cd openVoice
8 pip install -e .
9 mkdir checkpoints_v2
10 cd checkpoints_v2
11 wget [[https:~~/~~/myshell-public-repo-host.s3.amazonaws.com/openvoice/checkpoints_v2_0417.zip>>https://myshell-public-repo-host.s3.amazonaws.com/openvoice/checkpoints_v2_0417.zip]]
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13 unzip checkpoints_v2_0417.zip
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16 mv checkpoints_v2 ~~/OpenVoice
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18 cd ..
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25 pip install git+https:~/~/github.com/cocktailpeanut/ov2.git
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29 cd ..
30 pip install git+https:~/~/github.com/myshell-ai/MeloTTS.git
31 python -m unidic download
32 cd resources
33 python3
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36
37 import os
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39 import torch
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41 from openvoice import se_extractor
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43 from openvoice.api import ToneColorConverter
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45 ckpt_converter = 'checkpoints_v2/converter'
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47 device = "cuda:0" if torch.cuda.is_available() else "cpu"
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49 output_dir = 'outputs_v2'
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51 tone_color_converter = ToneColorConverter(f' {ckpt_converter} /config.json', device=device)
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53 tone_color_converter.load_ckpt(f' {ckpt_converter} /checkpoint.pth')
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55 os.makedirs (output_dir, exist_ok=True)
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57 reference_speaker = 'resources/example_reference.mp3'
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59 target_se, audio_name = se_extractor.get_se(reference_speaker, tone_color_converter, vad=False)
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61 from melo.api import TTS
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63 src_path = f' {output_dir} /tmp.wav'
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65 speed = 1.0
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