PublicMirrors/voice-changer
1
0
Fork 0
mirror of https://github.com/w-okada/voice-changer.git synced 2025-01-23 05:25:01 +03:00
Code Issues Actions Packages Projects Releases Wiki Activity

test model

Browse Source
This commit is contained in:
wataru 2023-05-31 02:26:16 +09:00
parent 96458c2bba
commit c2efe5cba1
20 changed files with 209 additions and 542 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

1
.gitignore vendored
View File

@ -42,6 +42,7 @@ docker/cudnn/
server/pretrain/ server/pretrain/
server/weights/ server/weights/
server/model_dir/
server/weights_/ server/weights_/
server/weights__/ server/weights__/
server/models/ server/models/

8
server/const.py
View File

@ -103,8 +103,10 @@ class ServerAudioDeviceTypes(Enum):
SAMPLES_JSONS = [ SAMPLES_JSONS = [
# "https://huggingface.co/wok000/vcclient_model/raw/main/samples_0001.json", # "https://huggingface.co/wok000/vcclient_model/raw/main/samples_0001.json",
# "https://huggingface.co/wok000/vcclient_model/raw/main/samples_0002.json", # "https://huggingface.co/wok000/vcclient_model/raw/main/samples_0002.json",
"https://huggingface.co/wok000/vcclient_model/raw/main/samples_0003_t.json", # "https://huggingface.co/wok000/vcclient_model/raw/main/samples_0003_t.json",
"https://huggingface.co/wok000/vcclient_model/raw/main/samples_0003_o.json", # "https://huggingface.co/wok000/vcclient_model/raw/main/samples_0003_o.json",
"https://huggingface.co/wok000/vcclient_model/raw/main/test/test_official_v1_v2.jsona",
"https://huggingface.co/wok000/vcclient_model/raw/main/test/test_ddpn_v1_v2.jsona",
] ]
RVC_MODEL_DIRNAME = "rvc" RVC_MODEL_DIRNAME = "rvc"
RVC_MAX_SLOT_NUM = 5 RVC_MAX_SLOT_NUM = 10

2
server/initialize.sh
View File

@ -1,2 +1,2 @@
rm -r models rm -r model_dir
rm -r pretrain rm -r pretrain

139
server/samples_0001.json
View File

@ -1,139 +0,0 @@
{
"RVC": [
{
"id": "KikotoKurage",
"lang": "ja-JP",
"tag": ["torch", "test"],
"name": "黄琴海月",
"modelUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc/kikoto_kurage_48k_256/kikoto_kurage.pth",
"indexUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc/kikoto_kurage_48k_256/added_IVF2997_Flat_nprobe_11.index.bin",
"featureUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc/kikoto_kurage_48k_256/total_fea.npy",
"termsOfUseUrl": "https://huggingface.co/wok000/vcclient_model/raw/main/rvc/kikoto_kurage_48k_256/term_of_use.txt",
"credit": "黄琴海月",
"description": "",
"sampleRate": 48000,
"modelType": "webui_v1",
"f0": true
},
{
"id": "KikotoMahiro",
"lang": "ja-JP",
"tag": ["torch", "test"],
"name": "黄琴まひろ",
"modelUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc/kikoto_mahiro_48k_256/kikoto_mahiro.pth",
"indexUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc/kikoto_mahiro_48k_256/added_IVF4833_Flat_nprobe_12.index.bin",
"featureUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc/kikoto_mahiro_48k_256/total_fea.npy",
"termsOfUseUrl": "https://huggingface.co/wok000/vcclient_model/raw/main/rvc/kikoto_mahiro_48k_256/term_of_use.txt",
"credit": "黄琴まひろ",
"description": "",
"sampleRate": 48000,
"modelType": "webui_v1",
"f0": true
},
{
"id": "TokinaShigure",
"lang": "ja-JP",
"tag": ["torch", "test"],
"name": "刻鳴時雨",
"modelUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc/tokina_sigure/Shigure.pth",
"indexUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc/tokina_sigure/added_IVF1572_Flat_nprobe_9.index.bin",
"featureUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc/tokina_sigure/total_fea.npy",
"termsOfUseUrl": "https://huggingface.co/wok000/vcclient_model/raw/main/rvc/tokina_sigure/term_of_use.txt",
"credit": "刻鳴時雨",
"description": "https://huggingface.co/yasyune/Shigure_Tokina_RVC",
"sampleRate": 40000,
"modelType": "webui_v1",
"f0": true
},
{
"id": "Amitaro",
"lang": "ja-JP",
"tag": ["torch", "test"],
"name": "あみたろ",
"modelUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc/amitaro_contentvec_256/amitaro48k-100.pth",
"indexUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc/amitaro_contentvec_256/amitaro48k.0.index.bin",
"featureUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc/amitaro_contentvec_256/amitaro48k.0.big.npy",
"termsOfUseUrl": "https://huggingface.co/wok000/vcclient_model/raw/main/rvc/amitaro_contentvec_256/term_of_use.txt",
"credit": "あみたろ",
"description": "",
"sampleRate": 48000,
"modelType": "webui_v1",
"f0": true
},
{
"id": "Amitaro_768d",
"lang": "ja-JP",
"tag": ["torch", "test"],
"name": "あみたろ(768d)",
"modelUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc/amitaro_hubertjp_768_default/amitaro_hubertjp_768_def-100.pth",
"indexUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc/amitaro_hubertjp_768_default/amitaro_hubertjp_768_def.0.index.bin",
"featureUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc/amitaro_hubertjp_768_default/amitaro_hubertjp_768_def.0.big.npy",
"termsOfUseUrl": "https://huggingface.co/wok000/vcclient_model/raw/main/rvc/amitaro_hubertjp_768_default/term_of_use.txt",
"credit": "あみたろ",
"description": "rinna hubertjpを使用した768次元埋め込み版。デフォルトの事前学習モデルを使用",
"sampleRate": 48000,
"modelType": "webui_v1",
"f0": true
},
{
"id": "Amitaro_768n",
"lang": "ja-JP",
"tag": ["torch", "test"],
"name": "あみたろ(768n)",
"modelUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc/amitaro_hubertjp_768_nadare/amitaro_hubert_jp-100.pth",
"indexUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc/amitaro_hubertjp_768_nadare/amitaro_hubert_jp.0.index.bin",
"featureUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc/amitaro_hubertjp_768_nadare/amitaro_hubert_jp.0.big.npy",
"termsOfUseUrl": "https://huggingface.co/wok000/vcclient_model/raw/main/rvc/amitaro_hubertjp_768_nadare/term_of_use.txt",
"credit": "あみたろ",
"description": "rinna hubertjpを使用した768次元埋め込み版。nadare様作成の事前学習モデルを使用",
"sampleRate": 48000,
"modelType": "webui_v1",
"f0": true
},
{
"id": "Amitaro_768t",
"lang": "ja-JP",
"tag": ["torch", "test"],
"name": "あみたろ(768t)",
"modelUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc/amitaro_hubertjp_768_tylor/amitaro_hubertjp_768_tylor-100.pth",
"indexUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc/amitaro_hubertjp_768_tylor/amitaro_hubertjp_768_tylor.0.index.bin",
"featureUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc/amitaro_hubertjp_768_tylor/amitaro_hubertjp_768_tylor.0.big.npy",
"termsOfUseUrl": "https://huggingface.co/wok000/vcclient_model/raw/main/rvc/amitaro_hubertjp_768_tylor/term_of_use.txt",
"credit": "あみたろ",
"description": "rinna hubertjpを使用した768次元埋め込み版。tylor様作成の事前学習モデルを使用",
"sampleRate": 48000,
"modelType": "webui_v1",
"f0": true
},
{
"id": "Tsukuyomi-chan_768d",
"lang": "ja-JP",
"tag": ["torch", "test"],
"name": "つくよみちゃん(768d)",
"modelUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc/tsukuyomi-chan_hubertjp_768_default/tsukuyomi_hubertjp_768_def-100.pth",
"indexUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc/tsukuyomi-chan_hubertjp_768_default/tsukuyomi_hubertjp_768_def.0.index.bin",
"featureUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc/tsukuyomi-chan_hubertjp_768_default/tsukuyomi_hubertjp_768_def.0.big.npy",
"termsOfUseUrl": "https://huggingface.co/wok000/vcclient_model/raw/main/rvc/tsukuyomi-chan_hubertjp_768_default/term_of_use.txt",
"credit": "つくよみちゃん",
"description": "rinna hubertjpを使用した768次元埋め込み版。デフォルトの事前学習モデルを使用",
"sampleRate": 48000,
"modelType": "webui_v1",
"f0": true
},
{
"id": "Tsukuyomi-chan",
"lang": "ja-JP",
"tag": ["torch", "test"],
"name": "つくよみちゃん",
"modelUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc/tsukuyomi_contentvec_256/tsukuyomi48k-100.pth",
"indexUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc/tsukuyomi_contentvec_256/tsukuyomi48k.0.index.bin",
"featureUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc/tsukuyomi_contentvec_256/tsukuyomi48k.0.big.npy",
"termsOfUseUrl": "https://huggingface.co/wok000/vcclient_model/raw/main/rvc/tsukuyomi_contentvec_256/term_of_use.txt",
"credit": "つくよみちゃん",
"description": "",
"sampleRate": 48000,
"modelType": "webui_v1",
"f0": true
}
]
}

79
server/samples_0002.json
View File

@ -1,79 +0,0 @@
{
"RVC": [
{
"id": "KikotoKurage_v2",
"lang": "ja-JP",
"tag": ["torch", "test"],
"name": "黄琴海月_v2",
"modelUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc_v2_alpha/kikoto_kurage/kikoto_kurage_v2_40k_e100.pth",
"indexUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc_v2_alpha/kikoto_kurage/added_IVF5181_Flat_nprobe_1_v2.index.bin",
"featureUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc_v2_alpha/kikoto_kurage/total_fea.npy",
"termsOfUseUrl": "https://huggingface.co/wok000/vcclient_model/raw/main/rvc_v2_alpha/kikoto_kurage/terms_of_use.txt",
"credit": "黄琴海月",
"description": "",
"sampleRate": 40000,
"modelType": "rvc_v2",
"f0": true
},
{
"id": "KikotoMahiro_v2",
"lang": "ja-JP",
"tag": ["torch", "test"],
"name": "黄琴まひろ_v2",
"modelUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc_v2_alpha/kikoto_mahiro/kikoto_mahiro_v2_40k.pth",
"indexUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc_v2_alpha/kikoto_mahiro/added_IVF6881_Flat_nprobe_1_v2.index.bin",
"featureUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc_v2_alpha/kikoto_mahiro/total_fea.npy",
"termsOfUseUrl": "",
"credit": "黄琴まひろ",
"description": "",
"sampleRate": 40000,
"modelType": "rvc_v2",
"f0": true
},
{
"id": "TokinaShigure_v2",
"lang": "ja-JP",
"tag": ["torch", "test"],
"name": "刻鳴時雨_v2",
"modelUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc_v2_alpha/tokina_shigure/tokina_shigure_v2_40k_e100.pth",
"indexUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc_v2_alpha/tokina_shigure/added_IVF2736_Flat_nprobe_1_v2.index.bin",
"featureUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc_v2_alpha/tokina_shigure/total_fea.npy",
"termsOfUseUrl": "https://huggingface.co/wok000/vcclient_model/raw/main/rvc_v2_alpha/tokina_shigure/terms_of_use.txt",
"credit": "刻鳴時雨",
"description": "",
"sampleRate": 40000,
"modelType": "rvc_v2",
"f0": true
},
{
"id": "Amitaro_v2",
"lang": "ja-JP",
"tag": ["torch", "test"],
"name": "あみたろ_v2",
"modelUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc_v2_alpha/amitaro/amitaro_v2_40k_e100.pth",
"indexUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc_v2_alpha/amitaro/added_IVF3139_Flat_nprobe_1_v2.index.bin",
"featureUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc_v2_alpha/amitaro/total_fea.npy",
"termsOfUseUrl": "https://huggingface.co/wok000/vcclient_model/raw/main/rvc_v2_alpha/amitaro/terms_of_use.txt",
"credit": "あみたろ",
"description": "",
"sampleRate": 40000,
"modelType": "rvc_v2",
"f0": true
},
{
"id": "Tsukuyomi-chan_v2",
"lang": "ja-JP",
"tag": ["torch", "test"],
"name": "つくよみちゃん_v2",
"modelUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc_v2_alpha/tsukuyomi-chan/tsukuyomi_v2_40k_e100.pth",
"indexUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc_v2_alpha/tsukuyomi-chan/added_IVF7852_Flat_nprobe_1_v2.index.bin",
"featureUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc_v2_alpha/tsukuyomi-chan/total_fea.npy",
"termsOfUseUrl": "https://huggingface.co/wok000/vcclient_model/blob/main/rvc_v2_alpha/tsukuyomi-chan/terms_of_use.txt",
"credit": "つくよみちゃん",
"description": "",
"sampleRate": 40000,
"modelType": "rvc_v2",
"f0": true
}
]
}

74
server/samples_0003_o.json
View File

@ -1,74 +0,0 @@
{
"RVC": [
{
"id": "KikotoKurage_o",
"lang": "ja-JP",
"tag": ["v2", "onnx"],
"name": "黄琴海月",
"modelUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc_v2_alpha/kikoto_kurage/kikoto_kurage_v2_40k_e100_simple.onnx",
"indexUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc_v2_alpha/kikoto_kurage/added_IVF5181_Flat_nprobe_1_v2.index.bin",
"termsOfUseUrl": "https://huggingface.co/wok000/vcclient_model/raw/main/rvc_v2_alpha/kikoto_kurage/terms_of_use.txt",
"credit": "黄琴海月",
"description": "",
"sampleRate": 40000,
"modelType": "rvc_v2",
"f0": true
},
{
"id": "KikotoMahiro_o",
"lang": "ja-JP",
"tag": ["v2", "onnx"],
"name": "黄琴まひろ",
"modelUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc_v2_alpha/kikoto_mahiro/kikoto_mahiro_v2_40k_simple.onnx",
"indexUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc_v2_alpha/kikoto_mahiro/added_IVF6881_Flat_nprobe_1_v2.index.bin",
"termsOfUseUrl": "",
"credit": "黄琴まひろ",
"description": "",
"sampleRate": 40000,
"modelType": "rvc_v2",
"f0": true
},
{
"id": "TokinaShigure_o",
"lang": "ja-JP",
"tag": ["v2", "onnx"],
"name": "刻鳴時雨",
"modelUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc_v2_alpha/tokina_shigure/tokina_shigure_v2_40k_e100_simple.onnx",
"indexUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc_v2_alpha/tokina_shigure/added_IVF2736_Flat_nprobe_1_v2.index.bin",
"termsOfUseUrl": "https://huggingface.co/wok000/vcclient_model/raw/main/rvc_v2_alpha/tokina_shigure/terms_of_use.txt",
"credit": "刻鳴時雨",
"description": "",
"sampleRate": 40000,
"modelType": "rvc_v2",
"f0": true
},
{
"id": "Amitaro_o",
"lang": "ja-JP",
"tag": ["v2", "onnx"],
"name": "あみたろ",
"modelUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc_v2_alpha/amitaro/amitaro_v2_40k_e100_simple.onnx",
"indexUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc_v2_alpha/amitaro/added_IVF3139_Flat_nprobe_1_v2.index.bin",
"termsOfUseUrl": "https://huggingface.co/wok000/vcclient_model/raw/main/rvc_v2_alpha/amitaro/terms_of_use.txt",
"credit": "あみたろ",
"description": "",
"sampleRate": 40000,
"modelType": "rvc_v2",
"f0": true
},
{
"id": "Tsukuyomi-chan_o",
"lang": "ja-JP",
"tag": ["v2", "onnx"],
"name": "つくよみちゃん",
"modelUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc_v2_alpha/tsukuyomi-chan/tsukuyomi_v2_40k_e100_simple.onnx",
"indexUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc_v2_alpha/tsukuyomi-chan/added_IVF7852_Flat_nprobe_1_v2.index.bin",
"termsOfUseUrl": "https://huggingface.co/wok000/vcclient_model/blob/main/rvc_v2_alpha/tsukuyomi-chan/terms_of_use.txt",
"credit": "つくよみちゃん",
"description": "",
"sampleRate": 40000,
"modelType": "rvc_v2",
"f0": true
}
]
}

74
server/samples_0003_t.json
View File

@ -1,74 +0,0 @@
{
"RVC": [
{
"id": "KikotoKurage_t",
"lang": "ja-JP",
"tag": ["v2", "torch"],
"name": "黄琴海月",
"modelUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc_v2_alpha/kikoto_kurage/kikoto_kurage_v2_40k_e100.pth",
"indexUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc_v2_alpha/kikoto_kurage/added_IVF5181_Flat_nprobe_1_v2.index.bin",
"termsOfUseUrl": "https://huggingface.co/wok000/vcclient_model/raw/main/rvc_v2_alpha/kikoto_kurage/terms_of_use.txt",
"credit": "黄琴海月",
"description": "",
"sampleRate": 40000,
"modelType": "rvc_v2",
"f0": true
},
{
"id": "KikotoMahiro_t",
"lang": "ja-JP",
"tag": ["v2", "torch"],
"name": "黄琴まひろ",
"modelUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc_v2_alpha/kikoto_mahiro/kikoto_mahiro_v2_40k.pth",
"indexUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc_v2_alpha/kikoto_mahiro/added_IVF6881_Flat_nprobe_1_v2.index.bin",
"termsOfUseUrl": "",
"credit": "黄琴まひろ",
"description": "",
"sampleRate": 40000,
"modelType": "rvc_v2",
"f0": true
},
{
"id": "TokinaShigure_t",
"lang": "ja-JP",
"tag": ["v2", "torch"],
"name": "刻鳴時雨",
"modelUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc_v2_alpha/tokina_shigure/tokina_shigure_v2_40k_e100.pth",
"indexUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc_v2_alpha/tokina_shigure/added_IVF2736_Flat_nprobe_1_v2.index.bin",
"termsOfUseUrl": "https://huggingface.co/wok000/vcclient_model/raw/main/rvc_v2_alpha/tokina_shigure/terms_of_use.txt",
"credit": "刻鳴時雨",
"description": "",
"sampleRate": 40000,
"modelType": "rvc_v2",
"f0": true
},
{
"id": "Amitaro_t",
"lang": "ja-JP",
"tag": ["v2", "torch"],
"name": "あみたろ",
"modelUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc_v2_alpha/amitaro/amitaro_v2_40k_e100.pth",
"indexUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc_v2_alpha/amitaro/added_IVF3139_Flat_nprobe_1_v2.index.bin",
"termsOfUseUrl": "https://huggingface.co/wok000/vcclient_model/raw/main/rvc_v2_alpha/amitaro/terms_of_use.txt",
"credit": "あみたろ",
"description": "",
"sampleRate": 40000,
"modelType": "rvc_v2",
"f0": true
},
{
"id": "Tsukuyomi-chan_t",
"lang": "ja-JP",
"tag": ["v2", "torch"],
"name": "つくよみちゃん",
"modelUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc_v2_alpha/tsukuyomi-chan/tsukuyomi_v2_40k_e100.pth",
"indexUrl": "https://huggingface.co/wok000/vcclient_model/resolve/main/rvc_v2_alpha/tsukuyomi-chan/added_IVF7852_Flat_nprobe_1_v2.index.bin",
"termsOfUseUrl": "https://huggingface.co/wok000/vcclient_model/blob/main/rvc_v2_alpha/tsukuyomi-chan/terms_of_use.txt",
"credit": "つくよみちゃん",
"description": "",
"sampleRate": 40000,
"modelType": "rvc_v2",
"f0": true
}
]
}

2
server/voice_changer/DDSP_SVC/DDSP_SVC.py
View File

@ -226,7 +226,7 @@ class DDSP_SVC:
try: try:
file_path = val.__file__ file_path = val.__file__
if file_path.find("DDSP-SVC" + os.path.sep) >= 0: if file_path.find("DDSP-SVC" + os.path.sep) >= 0:
print("remove", key, file_path) # print("remove", key, file_path)
sys.modules.pop(key) sys.modules.pop(key)
except: # type:ignore except: # type:ignore
pass pass

2
server/voice_changer/MMVCv13/MMVCv13.py
View File

@ -289,7 +289,7 @@ class MMVCv13:
try: try:
file_path = val.__file__ file_path = val.__file__
if file_path.find(remove_path + os.path.sep) >= 0: if file_path.find(remove_path + os.path.sep) >= 0:
print("remove", key, file_path) # print("remove", key, file_path)
sys.modules.pop(key) sys.modules.pop(key)
except: # type:ignore except: # type:ignore
pass pass

2
server/voice_changer/MMVCv15/MMVCv15.py
View File

@ -348,7 +348,7 @@ class MMVCv15:
try: try:
file_path = val.__file__ file_path = val.__file__
if file_path.find(remove_path + os.path.sep) >= 0: if file_path.find(remove_path + os.path.sep) >= 0:
print("remove", key, file_path) # print("remove", key, file_path)
sys.modules.pop(key) sys.modules.pop(key)
except: # type:ignore except: # type:ignore
pass pass

8
server/voice_changer/RVC/ModelSlot.py
View File

@ -5,24 +5,22 @@ from dataclasses import dataclass
@dataclass @dataclass
class ModelSlot: class ModelSlot:
# pyTorchModelFile: str = ""
# onnxModelFile: str = ""
modelFile: str = "" modelFile: str = ""
featureFile: str = ""
indexFile: str = "" indexFile: str = ""
defaultTune: int = 0 defaultTune: int = 0
defaultIndexRatio: int = 1 defaultIndexRatio: int = 1
isONNX: bool = False isONNX: bool = False
modelType: EnumInferenceTypes = EnumInferenceTypes.pyTorchRVC modelType: str = EnumInferenceTypes.pyTorchRVC.value
samplingRate: int = -1 samplingRate: int = -1
f0: bool = True f0: bool = True
embChannels: int = 256 embChannels: int = 256
embOutputLayer: int = 9 embOutputLayer: int = 9
useFinalProj: bool = True useFinalProj: bool = True
deprecated: bool = False deprecated: bool = False
embedder: EnumEmbedderTypes = EnumEmbedderTypes.hubert embedder: str = EnumEmbedderTypes.hubert.value
name: str = "" name: str = ""
description: str = "" description: str = ""
credit: str = "" credit: str = ""
termsOfUseUrl: str = "" termsOfUseUrl: str = ""
sampleId: str = ""

119
server/voice_changer/RVC/ModelSlotGenerator.py
View File

@ -4,55 +4,6 @@ from voice_changer.RVC.ModelSlot import ModelSlot
import torch import torch
import onnxruntime import onnxruntime
import json import json
import os
def generateModelSlot(slotDir: str):
try:
modelSlot = ModelSlot()
if os.path.exists(slotDir) is False:
return modelSlot
paramFile = os.path.join(slotDir, "params.json")
with open(paramFile, "r") as f:
params = json.load(f)
modelSlot.modelFile = os.path.join(
slotDir, os.path.basename(params["files"]["rvcModel"])
)
if "rvcFeature" in params["files"]:
modelSlot.featureFile = os.path.join(
slotDir, os.path.basename(params["files"]["rvcFeature"])
)
else:
modelSlot.featureFile = None
if "rvcIndex" in params["files"]:
modelSlot.indexFile = os.path.join(
slotDir, os.path.basename(params["files"]["rvcIndex"])
)
else:
modelSlot.indexFile = None
modelSlot.defaultTune = params["defaultTune"] if "defaultTune" in params else 0
modelSlot.defaultIndexRatio = (
params["defaultIndexRatio"] if "defaultIndexRatio" in params else 0
)
modelSlot.name = params["name"] if "name" in params else None
modelSlot.description = params["description"] if "description" in params else None
modelSlot.credit = params["credit"] if "credit" in params else None
modelSlot.termsOfUseUrl = (
params["termsOfUseUrl"] if "termsOfUseUrl" in params else None
)
modelSlot.isONNX = modelSlot.modelFile.endswith(".onnx")
if modelSlot.isONNX:
_setInfoByONNX(modelSlot)
else:
_setInfoByPytorch(modelSlot)
return modelSlot
except Exception as e:
print(f"[Voice Changer] faild to generate slot: {e}")
return ModelSlot()
def _setInfoByPytorch(slot: ModelSlot): def _setInfoByPytorch(slot: ModelSlot):
@ -65,32 +16,34 @@ def _setInfoByPytorch(slot: ModelSlot):
version = cpt.get("version", "v1") version = cpt.get("version", "v1")
if version is None or version == "v1": if version is None or version == "v1":
slot.modelType = ( slot.modelType = (
EnumInferenceTypes.pyTorchRVC EnumInferenceTypes.pyTorchRVC.value
if slot.f0 if slot.f0
else EnumInferenceTypes.pyTorchRVCNono else EnumInferenceTypes.pyTorchRVCNono.value
) )
slot.embChannels = 256 slot.embChannels = 256
slot.embOutputLayer = 9 slot.embOutputLayer = 9
slot.useFinalProj = True slot.useFinalProj = True
slot.embedder = EnumEmbedderTypes.hubert slot.embedder = EnumEmbedderTypes.hubert.value
print("[Voice Changer] Official Model(pyTorch) : v1")
else: else:
slot.modelType = ( slot.modelType = (
EnumInferenceTypes.pyTorchRVCv2 EnumInferenceTypes.pyTorchRVCv2.value
if slot.f0 if slot.f0
else EnumInferenceTypes.pyTorchRVCv2Nono else EnumInferenceTypes.pyTorchRVCv2Nono.value
) )
slot.embChannels = 768 slot.embChannels = 768
slot.embOutputLayer = 12 slot.embOutputLayer = 12
slot.useFinalProj = False slot.useFinalProj = False
slot.embedder = EnumEmbedderTypes.hubert slot.embedder = EnumEmbedderTypes.hubert.value
print("[Voice Changer] Official Model(pyTorch) : v2")
else: else:
# DDPN RVC # DDPN RVC
slot.f0 = True if cpt["f0"] == 1 else False slot.f0 = True if cpt["f0"] == 1 else False
slot.modelType = ( slot.modelType = (
EnumInferenceTypes.pyTorchWebUI EnumInferenceTypes.pyTorchWebUI.value
if slot.f0 if slot.f0
else EnumInferenceTypes.pyTorchWebUINono else EnumInferenceTypes.pyTorchWebUINono.value
) )
slot.embChannels = cpt["config"][17] slot.embChannels = cpt["config"][17]
slot.embOutputLayer = ( slot.embOutputLayer = (
@ -107,30 +60,30 @@ def _setInfoByPytorch(slot: ModelSlot):
and slot.embOutputLayer == 9 and slot.embOutputLayer == 9
and slot.useFinalProj is True and slot.useFinalProj is True
): ):
print("[Voice Changer] DDPN Model: Original v1 like") print("[Voice Changer] DDPN Model(pyTorch) : Official v1 like")
elif ( elif (
slot.embChannels == 768 slot.embChannels == 768
and slot.embOutputLayer == 12 and slot.embOutputLayer == 12
and slot.useFinalProj is False and slot.useFinalProj is False
): ):
print("[Voice Changer] DDPN Model: Original v2 like") print("[Voice Changer] DDPN Model(pyTorch): Official v2 like")
else: else:
print( print(
f"[Voice Changer] DDPN Model: ch:{slot.embChannels}, L:{slot.embOutputLayer}, FP:{slot.useFinalProj}" f"[Voice Changer] DDPN Model(pyTorch): ch:{slot.embChannels}, L:{slot.embOutputLayer}, FP:{slot.useFinalProj}"
) )
slot.embedder = cpt["embedder_name"] slot.embedder = cpt["embedder_name"]
if slot.embedder.endswith("768"): if slot.embedder.endswith("768"):
slot.embedder = slot.embedder[:-3] slot.embedder = slot.embedder[:-3]
if slot.embedder == EnumEmbedderTypes.hubert.value: # if slot.embedder == EnumEmbedderTypes.hubert.value:
slot.embedder = EnumEmbedderTypes.hubert # slot.embedder = EnumEmbedderTypes.hubert
elif slot.embedder == EnumEmbedderTypes.contentvec.value: # elif slot.embedder == EnumEmbedderTypes.contentvec.value:
slot.embedder = EnumEmbedderTypes.contentvec # slot.embedder = EnumEmbedderTypes.contentvec
elif slot.embedder == EnumEmbedderTypes.hubert_jp.value: # elif slot.embedder == EnumEmbedderTypes.hubert_jp.value:
slot.embedder = EnumEmbedderTypes.hubert_jp # slot.embedder = EnumEmbedderTypes.hubert_jp
else: # else:
raise RuntimeError("[Voice Changer][setInfoByONNX] unknown embedder") # raise RuntimeError("[Voice Changer][setInfoByONNX] unknown embedder")
slot.samplingRate = cpt["config"][-1] slot.samplingRate = cpt["config"][-1]
@ -170,40 +123,44 @@ def _setInfoByONNX(slot: ModelSlot):
and slot.embOutputLayer == 9 and slot.embOutputLayer == 9
and slot.useFinalProj is True and slot.useFinalProj is True
): ):
print("[Voice Changer] ONNX Model: Original v1 like") print("[Voice Changer] ONNX Model: Official v1 like")
elif ( elif (
slot.embChannels == 768 slot.embChannels == 768
and slot.embOutputLayer == 12 and slot.embOutputLayer == 12
and slot.useFinalProj is False and slot.useFinalProj is False
): ):
print("[Voice Changer] ONNX Model: Original v2 like") print("[Voice Changer] ONNX Model: Official v2 like")
else: else:
print( print(
f"[Voice Changer] ONNX Model: ch:{slot.embChannels}, L:{slot.embOutputLayer}, FP:{slot.useFinalProj}" f"[Voice Changer] ONNX Model: ch:{slot.embChannels}, L:{slot.embOutputLayer}, FP:{slot.useFinalProj}"
) )
if "embedder" not in metadata: if "embedder" not in metadata:
slot.embedder = EnumEmbedderTypes.hubert slot.embedder = EnumEmbedderTypes.hubert.value
elif metadata["embedder"] == EnumEmbedderTypes.hubert.value:
slot.embedder = EnumEmbedderTypes.hubert
elif metadata["embedder"] == EnumEmbedderTypes.contentvec.value:
slot.embedder = EnumEmbedderTypes.contentvec
elif metadata["embedder"] == EnumEmbedderTypes.hubert_jp.value:
slot.embedder = EnumEmbedderTypes.hubert_jp
else: else:
raise RuntimeError("[Voice Changer][setInfoByONNX] unknown embedder") slot.embedder = metadata["embedder"]
# elif metadata["embedder"] == EnumEmbedderTypes.hubert.value:
# slot.embedder = EnumEmbedderTypes.hubert
# elif metadata["embedder"] == EnumEmbedderTypes.contentvec.value:
# slot.embedder = EnumEmbedderTypes.contentvec
# elif metadata["embedder"] == EnumEmbedderTypes.hubert_jp.value:
# slot.embedder = EnumEmbedderTypes.hubert_jp
# else:
# raise RuntimeError("[Voice Changer][setInfoByONNX] unknown embedder")
slot.f0 = metadata["f0"] slot.f0 = metadata["f0"]
slot.modelType = ( slot.modelType = (
EnumInferenceTypes.onnxRVC if slot.f0 else EnumInferenceTypes.onnxRVCNono EnumInferenceTypes.onnxRVC.value
if slot.f0
else EnumInferenceTypes.onnxRVCNono.value
) )
slot.samplingRate = metadata["samplingRate"] slot.samplingRate = metadata["samplingRate"]
slot.deprecated = False slot.deprecated = False
except Exception as e: except Exception as e:
slot.modelType = EnumInferenceTypes.onnxRVC slot.modelType = EnumInferenceTypes.onnxRVC.value
slot.embChannels = 256 slot.embChannels = 256
slot.embedder = EnumEmbedderTypes.hubert slot.embedder = EnumEmbedderTypes.hubert.value
slot.f0 = True slot.f0 = True
slot.samplingRate = 48000 slot.samplingRate = 48000
slot.deprecated = True slot.deprecated = True

97
server/voice_changer/RVC/RVC.py
View File

@ -6,6 +6,7 @@ import numpy as np
import torch import torch
import torchaudio import torchaudio
from ModelSample import getModelSamples from ModelSample import getModelSamples
from voice_changer.RVC.ModelSlot import ModelSlot
from voice_changer.RVC.SampleDownloader import downloadModelFiles from voice_changer.RVC.SampleDownloader import downloadModelFiles
@ -24,7 +25,10 @@ else:
from voice_changer.RVC.modelMerger.MergeModel import merge_model from voice_changer.RVC.modelMerger.MergeModel import merge_model
from voice_changer.RVC.modelMerger.MergeModelRequest import MergeModelRequest from voice_changer.RVC.modelMerger.MergeModelRequest import MergeModelRequest
from voice_changer.RVC.ModelSlotGenerator import generateModelSlot from voice_changer.RVC.ModelSlotGenerator import (
_setInfoByONNX,
_setInfoByPytorch,
)
from voice_changer.RVC.RVCSettings import RVCSettings from voice_changer.RVC.RVCSettings import RVCSettings
from voice_changer.RVC.embedder.EmbedderManager import EmbedderManager from voice_changer.RVC.embedder.EmbedderManager import EmbedderManager
from voice_changer.utils.LoadModelParams import LoadModelParams from voice_changer.utils.LoadModelParams import LoadModelParams
@ -37,7 +41,7 @@ from voice_changer.RVC.deviceManager.DeviceManager import DeviceManager
from voice_changer.RVC.pipeline.Pipeline import Pipeline from voice_changer.RVC.pipeline.Pipeline import Pipeline
from Exceptions import NoModeLoadedException from Exceptions import NoModeLoadedException
from const import RVC_MAX_SLOT_NUM, RVC_MODEL_DIRNAME, SAMPLES_JSONS, UPLOAD_DIR from const import RVC_MODEL_DIRNAME, SAMPLES_JSONS, UPLOAD_DIR
import shutil import shutil
import json import json
@ -65,6 +69,7 @@ class RVC:
self.loadSlots() self.loadSlots()
print("RVC initialization: ", params) print("RVC initialization: ", params)
# サンプルカタログ作成
sampleJsons: list[str] = [] sampleJsons: list[str] = []
for url in SAMPLES_JSONS: for url in SAMPLES_JSONS:
filename = os.path.basename(url) filename = os.path.basename(url)
@ -82,7 +87,7 @@ class RVC:
self.switchModel(self.settings.modelSlotIndex) self.switchModel(self.settings.modelSlotIndex)
self.initialLoad = False self.initialLoad = False
break break
self.prevVol = 0. self.prevVol = 0.0
def getSampleInfo(self, id: str): def getSampleInfo(self, id: str):
sampleInfos = list(filter(lambda x: x.id == id, self.settings.sampleModels)) sampleInfos = list(filter(lambda x: x.id == id, self.settings.sampleModels))
@ -101,6 +106,7 @@ class RVC:
def loadModel(self, props: LoadModelParams): def loadModel(self, props: LoadModelParams):
target_slot_idx = props.slot target_slot_idx = props.slot
params = props.params params = props.params
slotInfo: ModelSlot = ModelSlot()
print("loadModel", params) print("loadModel", params)
# サンプルが指定されたときはダウンロードしてメタデータをでっちあげる # サンプルが指定されたときはダウンロードしてメタデータをでっちあげる
@ -113,34 +119,43 @@ class RVC:
print("[Voice Changer] sampleInfo is None") print("[Voice Changer] sampleInfo is None")
return return
modelPath, indexPath = downloadModelFiles(sampleInfo, useIndex) modelPath, indexPath = downloadModelFiles(sampleInfo, useIndex)
params["files"]["rvcModel"] = modelPath slotInfo.modelFile = modelPath
if indexPath is not None: if indexPath is not None:
params["files"]["rvcIndex"] = indexPath slotInfo.indexFile = indexPath
params["credit"] = sampleInfo.credit
params["description"] = sampleInfo.description slotInfo.sampleId = sampleInfo.id
params["name"] = sampleInfo.name slotInfo.credit = sampleInfo.credit
params["sampleId"] = sampleInfo.id slotInfo.description = sampleInfo.description
params["termsOfUseUrl"] = sampleInfo.termsOfUseUrl slotInfo.name = sampleInfo.name
params["sampleRate"] = sampleInfo.sampleRate slotInfo.termsOfUseUrl = sampleInfo.termsOfUseUrl
params["modelType"] = sampleInfo.modelType # slotInfo.samplingRate = sampleInfo.sampleRate
params["f0"] = sampleInfo.f0 # slotInfo.modelType = sampleInfo.modelType
# slotInfo.f0 = sampleInfo.f0
else:
slotInfo.modelFile = params["files"]["rvcModel"]
slotInfo.indexFile = (
params["files"]["rvcIndex"] if "rvcIndex" in params["files"] else None
)
slotInfo.defaultTune = params["defaultTune"]
slotInfo.defaultIndexRatio = params["defaultIndexRatio"]
slotInfo.isONNX = slotInfo.modelFile.endswith(".onnx")
if slotInfo.isONNX:
_setInfoByONNX(slotInfo)
else:
_setInfoByPytorch(slotInfo)
# メタデータを見て、永続化モデルフォルダに移動させる # メタデータを見て、永続化モデルフォルダに移動させる
# その際に、メタデータのファイル格納場所も書き換える # その際に、メタデータのファイル格納場所も書き換える
slotDir = os.path.join( slotDir = os.path.join(
self.params.model_dir, RVC_MODEL_DIRNAME, str(target_slot_idx) self.params.model_dir, RVC_MODEL_DIRNAME, str(target_slot_idx)
) )
os.makedirs(slotDir, exist_ok=True) os.makedirs(slotDir, exist_ok=True)
slotInfo.modelFile = self.moveToModelDir(slotInfo.modelFile, slotDir)
modelDst = self.moveToModelDir(params["files"]["rvcModel"], slotDir) if slotInfo.indexFile is not None:
params["files"]["rvcModel"] = modelDst slotInfo.indexFile = self.moveToModelDir(slotInfo.indexFile, slotDir)
if "rvcFeature" in params["files"]: json.dump(asdict(slotInfo), open(os.path.join(slotDir, "params.json"), "w"))
featureDst = self.moveToModelDir(params["files"]["rvcFeature"], slotDir)
params["files"]["rvcFeature"] = featureDst
if "rvcIndex" in params["files"]:
indexDst = self.moveToModelDir(params["files"]["rvcIndex"], slotDir)
params["files"]["rvcIndex"] = indexDst
json.dump(params, open(os.path.join(slotDir, "params.json"), "w"))
self.loadSlots() self.loadSlots()
# 初回のみロード(起動時にスロットにモデルがあった場合はinitialLoadはFalseになっている) # 初回のみロード(起動時にスロットにモデルがあった場合はinitialLoadはFalseになっている)
@ -156,16 +171,22 @@ class RVC:
def loadSlots(self): def loadSlots(self):
dirname = os.path.join(self.params.model_dir, RVC_MODEL_DIRNAME) dirname = os.path.join(self.params.model_dir, RVC_MODEL_DIRNAME)
self.settings.modelSlots = []
if not os.path.exists(dirname): if not os.path.exists(dirname):
return return
for slot_idx in range(RVC_MAX_SLOT_NUM): modelSlots: list[ModelSlot] = []
for slot_idx in range(len(self.settings.modelSlots)):
slotDir = os.path.join( slotDir = os.path.join(
self.params.model_dir, RVC_MODEL_DIRNAME, str(slot_idx) self.params.model_dir, RVC_MODEL_DIRNAME, str(slot_idx)
) )
modelSlot = generateModelSlot(slotDir) jsonDict = os.path.join(slotDir, "params.json")
self.settings.modelSlots.append(modelSlot) if os.path.exists(jsonDict):
jsonDict = json.load(open(os.path.join(slotDir, "params.json")))
slotInfo = ModelSlot(**jsonDict)
else:
slotInfo = ModelSlot()
modelSlots.append(slotInfo)
self.settings.modelSlots = modelSlots
def update_settings(self, key: str, val: int | float | str): def update_settings(self, key: str, val: int | float | str):
if key in self.settings.intData: if key in self.settings.intData:
@ -276,13 +297,21 @@ class RVC:
convertOffset = -1 * convertSize convertOffset = -1 * convertSize
self.audio_buffer = self.audio_buffer[convertOffset:] # 変換対象の部分だけ抽出 self.audio_buffer = self.audio_buffer[convertOffset:] # 変換対象の部分だけ抽出
audio_buffer = torch.from_numpy(self.audio_buffer).to(device=self.pipeline.device, dtype=torch.float32)
if self.pipeline is not None:
device = self.pipeline.device
else:
device = torch.device("cpu")
audio_buffer = torch.from_numpy(self.audio_buffer).to(
device=device, dtype=torch.float32
)
# 出力部分だけ切り出して音量を確認。(TODO:段階的消音にする) # 出力部分だけ切り出して音量を確認。(TODO:段階的消音にする)
cropOffset = -1 * (inputSize + crossfadeSize) cropOffset = -1 * (inputSize + crossfadeSize)
cropEnd = -1 * (crossfadeSize) cropEnd = -1 * (crossfadeSize)
crop = audio_buffer[cropOffset:cropEnd] crop = audio_buffer[cropOffset:cropEnd]
vol = torch.sqrt(torch.square(crop).mean(axis=0)).detach().cpu().numpy() vol = torch.sqrt(torch.square(crop).mean()).detach().cpu().numpy()
vol = max(vol, self.prevVol * 0.0) vol = max(vol, self.prevVol * 0.0)
self.prevVol = vol self.prevVol = vol
@ -312,7 +341,9 @@ class RVC:
if vol < self.settings.silentThreshold: if vol < self.settings.silentThreshold:
return np.zeros(convertSize).astype(np.int16) return np.zeros(convertSize).astype(np.int16)
audio = torchaudio.functional.resample(audio, self.settings.modelSamplingRate, 16000, rolloff=0.99) audio = torchaudio.functional.resample(
audio, self.settings.modelSamplingRate, 16000, rolloff=0.99
)
repeat = 3 if half else 1 repeat = 3 if half else 1
repeat *= self.settings.rvcQuality # 0 or 3 repeat *= self.settings.rvcQuality # 0 or 3
sid = 0 sid = 0
@ -341,7 +372,7 @@ class RVC:
def __del__(self): def __del__(self):
del self.pipeline del self.pipeline
print("---------- REMOVING ---------------") # print("---------- REMOVING ---------------")
remove_path = os.path.join("RVC") remove_path = os.path.join("RVC")
sys.path = [x for x in sys.path if x.endswith(remove_path) is False] sys.path = [x for x in sys.path if x.endswith(remove_path) is False]
@ -351,7 +382,7 @@ class RVC:
try: try:
file_path = val.__file__ file_path = val.__file__
if file_path.find("RVC" + os.path.sep) >= 0: if file_path.find("RVC" + os.path.sep) >= 0:
print("remove", key, file_path) # print("remove", key, file_path)
sys.modules.pop(key) sys.modules.pop(key)
except Exception: # type:ignore except Exception: # type:ignore
# print(e) # print(e)

11
server/voice_changer/RVC/RVCSettings.py
View File

@ -1,5 +1,6 @@
from dataclasses import dataclass, field from dataclasses import dataclass, field
from ModelSample import RVCModelSample from ModelSample import RVCModelSample
from const import RVC_MAX_SLOT_NUM
from voice_changer.RVC.ModelSlot import ModelSlot from voice_changer.RVC.ModelSlot import ModelSlot
@ -17,15 +18,9 @@ class RVCSettings:
framework: str = "PyTorch" # PyTorch or ONNX framework: str = "PyTorch" # PyTorch or ONNX
modelSlots: list[ModelSlot] = field( modelSlots: list[ModelSlot] = field(
default_factory=lambda: [ default_factory=lambda: [ModelSlot() for _x in range(RVC_MAX_SLOT_NUM)]
ModelSlot(), # 1
ModelSlot(), # 2
ModelSlot(), # 3
ModelSlot(), # 4
ModelSlot(), # 5
ModelSlot(), # 6(merged)
]
) )
sampleModels: list[RVCModelSample] = field(default_factory=lambda: []) sampleModels: list[RVCModelSample] = field(default_factory=lambda: [])
indexRatio: float = 0 indexRatio: float = 0

89
server/voice_changer/RVC/SampleDownloader.py
View File

@ -1,11 +1,14 @@
from concurrent.futures import ThreadPoolExecutor from concurrent.futures import ThreadPoolExecutor
from dataclasses import asdict
import os import os
from const import RVC_MODEL_DIRNAME, TMP_DIR from const import RVC_MODEL_DIRNAME, TMP_DIR
from Downloader import download, download_no_tqdm from Downloader import download, download_no_tqdm
from ModelSample import RVCModelSample, getModelSamples from ModelSample import RVCModelSample, getModelSamples
from typing import Any
import json import json
from voice_changer.RVC.ModelSlot import ModelSlot
from voice_changer.RVC.ModelSlotGenerator import _setInfoByONNX, _setInfoByPytorch
def checkRvcModelExist(model_dir: str): def checkRvcModelExist(model_dir: str):
rvcModelDir = os.path.join(model_dir, RVC_MODEL_DIRNAME) rvcModelDir = os.path.join(model_dir, RVC_MODEL_DIRNAME)
@ -15,12 +18,38 @@ def checkRvcModelExist(model_dir: str):
def downloadInitialSampleModels(sampleJsons: list[str], model_dir: str): def downloadInitialSampleModels(sampleJsons: list[str], model_dir: str):
# sampleModelIds = [
# ("TokinaShigure_o", True),
# ("KikotoMahiro_o", False),
# ("Amitaro_o", False),
# ("Tsukuyomi-chan_o", False),
# ]
sampleModelIds = [ sampleModelIds = [
("TokinaShigure_o", True), # オフィシャルモデルテスト
("KikotoMahiro_o", False), # ("test-official-v1-f0-48k-l9-hubert_t", True),
("Amitaro_o", False), # ("test-official-v1-nof0-48k-l9-hubert_t", False),
("Tsukuyomi-chan_o", False), # ("test-official-v2-f0-40k-l12-hubert_t", False),
# ("test-official-v2-nof0-40k-l12-hubert_t", False),
# ("test-official-v1-f0-48k-l9-hubert_o", True),
# ("test-official-v1-nof0-48k-l9-hubert_o", False),
# ("test-official-v2-f0-40k-l12-hubert_o", False),
# ("test-official-v2-nof0-40k-l12-hubert_o", False),
# DDPNモデルテスト(torch)
# ("test-ddpn-v1-f0-48k-l9-hubert_t", False),
# ("test-ddpn-v1-nof0-48k-l9-hubert_t", False),
# ("test-ddpn-v2-f0-40k-l12-hubert_t", False),
# ("test-ddpn-v2-nof0-40k-l12-hubert_t", False),
# ("test-ddpn-v2-f0-40k-l12-hubert_jp_t", False),
# ("test-ddpn-v2-nof0-40k-l12-hubert_jp_t", False),
# DDPNモデルテスト(onnx)
("test-ddpn-v1-f0-48k-l9-hubert_o", False),
("test-ddpn-v1-nof0-48k-l9-hubert_o", False),
("test-ddpn-v2-f0-40k-l12-hubert_o", False),
("test-ddpn-v2-nof0-40k-l12-hubert_o", False),
("test-ddpn-v2-f0-40k-l12-hubert_jp_o", False),
("test-ddpn-v2-nof0-40k-l12-hubert_jp_o", False),
] ]
sampleModels = getModelSamples(sampleJsons, "RVC") sampleModels = getModelSamples(sampleJsons, "RVC")
if sampleModels is None: if sampleModels is None:
return return
@ -29,7 +58,6 @@ def downloadInitialSampleModels(sampleJsons: list[str], model_dir: str):
slot_count = 0 slot_count = 0
line_num = 0 line_num = 0
for initSampleId in sampleModelIds: for initSampleId in sampleModelIds:
print(initSampleId)
# 初期サンプルをサーチ # 初期サンプルをサーチ
match = False match = False
for sample in sampleModels: for sample in sampleModels:
@ -41,7 +69,8 @@ def downloadInitialSampleModels(sampleJsons: list[str], model_dir: str):
continue continue
# 検出されたら、、、 # 検出されたら、、、
sampleParams: Any = {"files": {}} slotInfo: ModelSlot = ModelSlot()
# sampleParams: Any = {"files": {}}
slotDir = os.path.join(model_dir, RVC_MODEL_DIRNAME, str(slot_count)) slotDir = os.path.join(model_dir, RVC_MODEL_DIRNAME, str(slot_count))
os.makedirs(slotDir, exist_ok=True) os.makedirs(slotDir, exist_ok=True)
@ -56,7 +85,7 @@ def downloadInitialSampleModels(sampleJsons: list[str], model_dir: str):
"position": line_num, "position": line_num,
} }
) )
sampleParams["files"]["rvcModel"] = modelFilePath slotInfo.modelFile = modelFilePath
line_num += 1 line_num += 1
if ( if (
@ -75,29 +104,45 @@ def downloadInitialSampleModels(sampleJsons: list[str], model_dir: str):
"position": line_num, "position": line_num,
} }
) )
sampleParams["files"]["rvcIndex"] = indexPath slotInfo.indexFile = indexPath
line_num += 1 line_num += 1
sampleParams["sampleId"] = sample.id slotInfo.sampleId = sample.id
sampleParams["defaultTune"] = 0 slotInfo.credit = sample.credit
sampleParams["defaultIndexRatio"] = 1 slotInfo.description = sample.description
sampleParams["credit"] = sample.credit slotInfo.name = sample.name
sampleParams["description"] = sample.description slotInfo.termsOfUseUrl = sample.termsOfUseUrl
sampleParams["name"] = sample.name
sampleParams["sampleId"] = sample.id
sampleParams["termsOfUseUrl"] = sample.termsOfUseUrl
sampleParams["sampleRate"] = sample.sampleRate
sampleParams["modelType"] = sample.modelType
sampleParams["f0"] = sample.f0
jsonFilePath = os.path.join(slotDir, "params.json") slotInfo.defaultTune = 0
json.dump(sampleParams, open(jsonFilePath, "w")) slotInfo.defaultIndexRatio = 1
slotInfo.isONNX = slotInfo.modelFile.endswith(".onnx")
# この時点ではまだファイルはダウンロードされていない
# if slotInfo.isONNX:
# _setInfoByONNX(slotInfo)
# else:
# _setInfoByPytorch(slotInfo)
json.dump(asdict(slotInfo), open(os.path.join(slotDir, "params.json"), "w"))
slot_count += 1 slot_count += 1
# ダウンロード
print("[Voice Changer] Downloading model files...") print("[Voice Changer] Downloading model files...")
with ThreadPoolExecutor() as pool: with ThreadPoolExecutor() as pool:
pool.map(download, downloadParams) pool.map(download, downloadParams)
# メタデータ作成
print("[Voice Changer] Generating metadata...")
for slotId in range(slot_count):
slotDir = os.path.join(model_dir, RVC_MODEL_DIRNAME, str(slotId))
jsonDict = json.load(open(os.path.join(slotDir, "params.json")))
slotInfo = ModelSlot(**jsonDict)
if slotInfo.isONNX:
_setInfoByONNX(slotInfo)
else:
_setInfoByPytorch(slotInfo)
json.dump(asdict(slotInfo), open(os.path.join(slotDir, "params.json"), "w"))
def downloadModelFiles(sampleInfo: RVCModelSample, useIndex: bool = True): def downloadModelFiles(sampleInfo: RVCModelSample, useIndex: bool = True):
downloadParams = [] downloadParams = []

6
server/voice_changer/RVC/onnxExporter/export2onnx.py
View File

@ -38,13 +38,11 @@ def export2onnx(gpu: int, modelSlot: ModelSlot):
metadata = { metadata = {
"application": "VC_CLIENT", "application": "VC_CLIENT",
"version": "2", "version": "2",
# ↓EnumInferenceTypesのままだとシリアライズできないのでテキスト化 "modelType": modelSlot.modelType,
"modelType": modelSlot.modelType.value,
"samplingRate": modelSlot.samplingRate, "samplingRate": modelSlot.samplingRate,
"f0": modelSlot.f0, "f0": modelSlot.f0,
"embChannels": modelSlot.embChannels, "embChannels": modelSlot.embChannels,
# ↓EnumEmbedderTypesのままだとシリアライズできないのでテキスト化 "embedder": modelSlot.embedder,
"embedder": modelSlot.embedder.value,
"embOutputLayer": modelSlot.embOutputLayer, "embOutputLayer": modelSlot.embOutputLayer,
"useFinalProj": modelSlot.useFinalProj, "useFinalProj": modelSlot.useFinalProj,
} }

24
server/voice_changer/RVC/pipeline/Pipeline.py
View File

@ -81,7 +81,9 @@ class Pipeline(object):
self.t_pad = self.sr * repeat self.t_pad = self.sr * repeat
self.t_pad_tgt = self.targetSR * repeat self.t_pad_tgt = self.targetSR * repeat
audio_pad = F.pad(audio.unsqueeze(0), (self.t_pad, self.t_pad), mode="reflect").squeeze(0) audio_pad = F.pad(
audio.unsqueeze(0), (self.t_pad, self.t_pad), mode="reflect"
).squeeze(0)
p_len = audio_pad.shape[0] // self.window p_len = audio_pad.shape[0] // self.window
sid = torch.tensor(sid, device=self.device).unsqueeze(0).long() sid = torch.tensor(sid, device=self.device).unsqueeze(0).long()
@ -102,8 +104,8 @@ class Pipeline(object):
pitchf = torch.tensor( pitchf = torch.tensor(
pitchf, device=self.device, dtype=torch.float pitchf, device=self.device, dtype=torch.float
).unsqueeze(0) ).unsqueeze(0)
except IndexError as e: except IndexError:
print(e) # print(e)
raise NotEnoughDataExtimateF0() raise NotEnoughDataExtimateF0()
# tensor型調整 # tensor型調整
@ -142,7 +144,7 @@ class Pipeline(object):
k = 1 k = 1
if k == 1: if k == 1:
_, ix = self.index.search(npy, 1) _, ix = self.index.search(npy, 1)
npy = self.big_npy[ix.squeeze()] npy = self.big_npy[ix.squeeze()]
else: else:
score, ix = self.index.search(npy, k=8) score, ix = self.index.search(npy, k=8)
weight = np.square(1 / score) weight = np.square(1 / score)
@ -171,12 +173,16 @@ class Pipeline(object):
try: try:
with torch.no_grad(): with torch.no_grad():
audio1 = ( audio1 = (
( torch.clip(
torch.clip(self.inferencer.infer(feats, p_len, pitch, pitchf, sid)[0][0, 0].to(dtype=torch.float32), -1., 1.) * 32767.5 - .5 self.inferencer.infer(feats, p_len, pitch, pitchf, sid)[0][
0, 0
].to(dtype=torch.float32),
-1.0,
1.0,
) )
.data * 32767.5
.to(dtype=torch.int16) - 0.5
) ).data.to(dtype=torch.int16)
except RuntimeError as e: except RuntimeError as e:
if "HALF" in e.__str__().upper(): if "HALF" in e.__str__().upper():
raise HalfPrecisionChangingException() raise HalfPrecisionChangingException()

2
server/voice_changer/SoVitsSvc40/SoVitsSvc40.py
View File

@ -468,7 +468,7 @@ class SoVitsSvc40:
try: try:
file_path = val.__file__ file_path = val.__file__
if file_path.find("so-vits-svc-40" + os.path.sep) >= 0: if file_path.find("so-vits-svc-40" + os.path.sep) >= 0:
print("remove", key, file_path) # print("remove", key, file_path)
sys.modules.pop(key) sys.modules.pop(key)
except Exception: # type:ignore except Exception: # type:ignore
pass pass

2
server/voice_changer/SoVitsSvc40v2/SoVitsSvc40v2.py
View File

@ -417,7 +417,7 @@ class SoVitsSvc40v2:
try: try:
file_path = val.__file__ file_path = val.__file__
if file_path.find("so-vits-svc-40v2" + os.path.sep) >= 0: if file_path.find("so-vits-svc-40v2" + os.path.sep) >= 0:
print("remove", key, file_path) # print("remove", key, file_path)
sys.modules.pop(key) sys.modules.pop(key)
except: # type:ignore except: # type:ignore
pass pass

10
server/voice_changer/VoiceChanger.py
View File

@ -495,7 +495,7 @@ class VoiceChanger:
result = output_wav result = output_wav
else: else:
print("[Voice Changer] no sola buffer. (You can ignore this.)") print("[Voice Changer] warming up... generating sola buffer.")
result = np.zeros(4096).astype(np.int16) result = np.zeros(4096).astype(np.int16)
if ( if (
@ -562,11 +562,11 @@ class VoiceChanger:
except ONNXInputArgumentException as e: except ONNXInputArgumentException as e:
print("[Voice Changer] [Exception] onnx are waiting valid input.", e) print("[Voice Changer] [Exception] onnx are waiting valid input.", e)
return np.zeros(1).astype(np.int16), [0, 0, 0] return np.zeros(1).astype(np.int16), [0, 0, 0]
except HalfPrecisionChangingException as e: except HalfPrecisionChangingException:
print("[Voice Changer] Switching model configuration....", e) print("[Voice Changer] Switching model configuration....")
return np.zeros(1).astype(np.int16), [0, 0, 0] return np.zeros(1).astype(np.int16), [0, 0, 0]
except NotEnoughDataExtimateF0 as e: except NotEnoughDataExtimateF0:
print("[Voice Changer] not enough data", e) print("[Voice Changer] warming up... waiting more data.")
return np.zeros(1).astype(np.int16), [0, 0, 0] return np.zeros(1).astype(np.int16), [0, 0, 0]
except DeviceChangingException as e: except DeviceChangingException as e:
print("[Voice Changer] embedder:", e) print("[Voice Changer] embedder:", e)