RVC/Retrieval-based-Voice-Conversion-WebUI
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Retrieval-based-Voice-Conve…/uvr5_pack/utils.py
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2023-04-15 00:10:04 +09:00

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import torch
import numpy as np
from tqdm import tqdm
def make_padding(width, cropsize, offset):
left = offset
roi_size = cropsize - left * 2
if roi_size == 0:
roi_size = cropsize
right = roi_size - (width % roi_size) + left
return left, right, roi_size
def inference(X_spec, device, model, aggressiveness, data):
"""
data ： dic configs
"""
def _execute(
X_mag_pad, roi_size, n_window, device, model, aggressiveness, is_half=True
):
model.eval()
with torch.no_grad():
preds = []
iterations = [n_window]
total_iterations = sum(iterations)
for i in tqdm(range(n_window)):
start = i * roi_size
X_mag_window = X_mag_pad[
None, :, :, start : start + data["window_size"]
]
X_mag_window = torch.from_numpy(X_mag_window)
if is_half:
X_mag_window = X_mag_window.half()
X_mag_window = X_mag_window.to(device)
pred = model.predict(X_mag_window, aggressiveness)
pred = pred.detach().cpu().numpy()
preds.append(pred[0])
pred = np.concatenate(preds, axis=2)
return pred
def preprocess(X_spec):
X_mag = np.abs(X_spec)
X_phase = np.angle(X_spec)
return X_mag, X_phase
X_mag, X_phase = preprocess(X_spec)
coef = X_mag.max()
X_mag_pre = X_mag / coef
n_frame = X_mag_pre.shape[2]
pad_l, pad_r, roi_size = make_padding(n_frame, data["window_size"], model.offset)
n_window = int(np.ceil(n_frame / roi_size))
X_mag_pad = np.pad(X_mag_pre, ((0, 0), (0, 0), (pad_l, pad_r)), mode="constant")
if list(model.state_dict().values())[0].dtype == torch.float16:
is_half = True
else:
is_half = False
pred = _execute(
X_mag_pad, roi_size, n_window, device, model, aggressiveness, is_half
)
pred = pred[:, :, :n_frame]
if data["tta"]:
pad_l += roi_size // 2
pad_r += roi_size // 2
n_window += 1
X_mag_pad = np.pad(X_mag_pre, ((0, 0), (0, 0), (pad_l, pad_r)), mode="constant")
pred_tta = _execute(
X_mag_pad, roi_size, n_window, device, model, aggressiveness, is_half
)
pred_tta = pred_tta[:, :, roi_size // 2 :]
pred_tta = pred_tta[:, :, :n_frame]
return (pred + pred_tta) * 0.5 * coef, X_mag, np.exp(1.0j * X_phase)
else:
return pred * coef, X_mag, np.exp(1.0j * X_phase)
def _get_name_params(model_path, model_hash):
ModelName = model_path
if model_hash == "47939caf0cfe52a0e81442b85b971dfd":
model_params_auto = str("uvr5_pack/lib_v5/modelparams/4band_44100.json")
param_name_auto = str("4band_44100")
if model_hash == "4e4ecb9764c50a8c414fee6e10395bbe":
model_params_auto = str("uvr5_pack/lib_v5/modelparams/4band_v2.json")
param_name_auto = str("4band_v2")
if model_hash == "ca106edd563e034bde0bdec4bb7a4b36":
model_params_auto = str("uvr5_pack/lib_v5/modelparams/4band_v2.json")
param_name_auto = str("4band_v2")
if model_hash == "e60a1e84803ce4efc0a6551206cc4b71":
model_params_auto = str("uvr5_pack/lib_v5/modelparams/4band_44100.json")
param_name_auto = str("4band_44100")
if model_hash == "a82f14e75892e55e994376edbf0c8435":
model_params_auto = str("uvr5_pack/lib_v5/modelparams/4band_44100.json")
param_name_auto = str("4band_44100")
if model_hash == "6dd9eaa6f0420af9f1d403aaafa4cc06":
model_params_auto = str("uvr5_pack/lib_v5/modelparams/4band_v2_sn.json")
param_name_auto = str("4band_v2_sn")
if model_hash == "08611fb99bd59eaa79ad27c58d137727":
model_params_auto = str("uvr5_pack/lib_v5/modelparams/4band_v2_sn.json")
param_name_auto = str("4band_v2_sn")
if model_hash == "5c7bbca45a187e81abbbd351606164e5":
model_params_auto = str("uvr5_pack/lib_v5/modelparams/3band_44100_msb2.json")
param_name_auto = str("3band_44100_msb2")
if model_hash == "d6b2cb685a058a091e5e7098192d3233":
model_params_auto = str("uvr5_pack/lib_v5/modelparams/3band_44100_msb2.json")
param_name_auto = str("3band_44100_msb2")
if model_hash == "c1b9f38170a7c90e96f027992eb7c62b":
model_params_auto = str("uvr5_pack/lib_v5/modelparams/4band_44100.json")
param_name_auto = str("4band_44100")
if model_hash == "c3448ec923fa0edf3d03a19e633faa53":
model_params_auto = str("uvr5_pack/lib_v5/modelparams/4band_44100.json")
param_name_auto = str("4band_44100")
if model_hash == "68aa2c8093d0080704b200d140f59e54":
model_params_auto = str("uvr5_pack/lib_v5/modelparams/3band_44100.json")
param_name_auto = str("3band_44100.json")
if model_hash == "fdc83be5b798e4bd29fe00fe6600e147":
model_params_auto = str("uvr5_pack/lib_v5/modelparams/3band_44100_mid.json")
param_name_auto = str("3band_44100_mid.json")
if model_hash == "2ce34bc92fd57f55db16b7a4def3d745":
model_params_auto = str("uvr5_pack/lib_v5/modelparams/3band_44100_mid.json")
param_name_auto = str("3band_44100_mid.json")
if model_hash == "52fdca89576f06cf4340b74a4730ee5f":
model_params_auto = str("uvr5_pack/lib_v5/modelparams/4band_44100.json")
param_name_auto = str("4band_44100.json")
if model_hash == "41191165b05d38fc77f072fa9e8e8a30":
model_params_auto = str("uvr5_pack/lib_v5/modelparams/4band_44100.json")
param_name_auto = str("4band_44100.json")
if model_hash == "89e83b511ad474592689e562d5b1f80e":
model_params_auto = str("uvr5_pack/lib_v5/modelparams/2band_32000.json")
param_name_auto = str("2band_32000.json")
if model_hash == "0b954da81d453b716b114d6d7c95177f":
model_params_auto = str("uvr5_pack/lib_v5/modelparams/2band_32000.json")
param_name_auto = str("2band_32000.json")
# v4 Models
if model_hash == "6a00461c51c2920fd68937d4609ed6c8":
model_params_auto = str("uvr5_pack/lib_v5/modelparams/1band_sr16000_hl512.json")
param_name_auto = str("1band_sr16000_hl512")
if model_hash == "0ab504864d20f1bd378fe9c81ef37140":
model_params_auto = str("uvr5_pack/lib_v5/modelparams/1band_sr32000_hl512.json")
param_name_auto = str("1band_sr32000_hl512")
if model_hash == "7dd21065bf91c10f7fccb57d7d83b07f":
model_params_auto = str("uvr5_pack/lib_v5/modelparams/1band_sr32000_hl512.json")
param_name_auto = str("1band_sr32000_hl512")
if model_hash == "80ab74d65e515caa3622728d2de07d23":
model_params_auto = str("uvr5_pack/lib_v5/modelparams/1band_sr32000_hl512.json")
param_name_auto = str("1band_sr32000_hl512")
if model_hash == "edc115e7fc523245062200c00caa847f":
model_params_auto = str("uvr5_pack/lib_v5/modelparams/1band_sr33075_hl384.json")
param_name_auto = str("1band_sr33075_hl384")
if model_hash == "28063e9f6ab5b341c5f6d3c67f2045b7":
model_params_auto = str("uvr5_pack/lib_v5/modelparams/1band_sr33075_hl384.json")
param_name_auto = str("1band_sr33075_hl384")
if model_hash == "b58090534c52cbc3e9b5104bad666ef2":
model_params_auto = str("uvr5_pack/lib_v5/modelparams/1band_sr44100_hl512.json")
param_name_auto = str("1band_sr44100_hl512")
if model_hash == "0cdab9947f1b0928705f518f3c78ea8f":
model_params_auto = str("uvr5_pack/lib_v5/modelparams/1band_sr44100_hl512.json")
param_name_auto = str("1band_sr44100_hl512")
if model_hash == "ae702fed0238afb5346db8356fe25f13":
model_params_auto = str(
"uvr5_pack/lib_v5/modelparams/1band_sr44100_hl1024.json"
)
param_name_auto = str("1band_sr44100_hl1024")
# User Models
# 1 Band
if "1band_sr16000_hl512" in ModelName:
model_params_auto = str("uvr5_pack/lib_v5/modelparams/1band_sr16000_hl512.json")
param_name_auto = str("1band_sr16000_hl512")
if "1band_sr32000_hl512" in ModelName:
model_params_auto = str("uvr5_pack/lib_v5/modelparams/1band_sr32000_hl512.json")
param_name_auto = str("1band_sr32000_hl512")
if "1band_sr33075_hl384" in ModelName:
model_params_auto = str("uvr5_pack/lib_v5/modelparams/1band_sr33075_hl384.json")
param_name_auto = str("1band_sr33075_hl384")
if "1band_sr44100_hl256" in ModelName:
model_params_auto = str("uvr5_pack/lib_v5/modelparams/1band_sr44100_hl256.json")
param_name_auto = str("1band_sr44100_hl256")
if "1band_sr44100_hl512" in ModelName:
model_params_auto = str("uvr5_pack/lib_v5/modelparams/1band_sr44100_hl512.json")
param_name_auto = str("1band_sr44100_hl512")
if "1band_sr44100_hl1024" in ModelName:
model_params_auto = str(
"uvr5_pack/lib_v5/modelparams/1band_sr44100_hl1024.json"
)
param_name_auto = str("1band_sr44100_hl1024")
# 2 Band
if "2band_44100_lofi" in ModelName:
model_params_auto = str("uvr5_pack/lib_v5/modelparams/2band_44100_lofi.json")
param_name_auto = str("2band_44100_lofi")
if "2band_32000" in ModelName:
model_params_auto = str("uvr5_pack/lib_v5/modelparams/2band_32000.json")
param_name_auto = str("2band_32000")
if "2band_48000" in ModelName:
model_params_auto = str("uvr5_pack/lib_v5/modelparams/2band_48000.json")
param_name_auto = str("2band_48000")
# 3 Band
if "3band_44100" in ModelName:
model_params_auto = str("uvr5_pack/lib_v5/modelparams/3band_44100.json")
param_name_auto = str("3band_44100")
if "3band_44100_mid" in ModelName:
model_params_auto = str("uvr5_pack/lib_v5/modelparams/3band_44100_mid.json")
param_name_auto = str("3band_44100_mid")
if "3band_44100_msb2" in ModelName:
model_params_auto = str("uvr5_pack/lib_v5/modelparams/3band_44100_msb2.json")
param_name_auto = str("3band_44100_msb2")
# 4 Band
if "4band_44100" in ModelName:
model_params_auto = str("uvr5_pack/lib_v5/modelparams/4band_44100.json")
param_name_auto = str("4band_44100")
if "4band_44100_mid" in ModelName:
model_params_auto = str("uvr5_pack/lib_v5/modelparams/4band_44100_mid.json")
param_name_auto = str("4band_44100_mid")
if "4band_44100_msb" in ModelName:
model_params_auto = str("uvr5_pack/lib_v5/modelparams/4band_44100_msb.json")
param_name_auto = str("4band_44100_msb")
if "4band_44100_msb2" in ModelName:
model_params_auto = str("uvr5_pack/lib_v5/modelparams/4band_44100_msb2.json")
param_name_auto = str("4band_44100_msb2")
if "4band_44100_reverse" in ModelName:
model_params_auto = str("uvr5_pack/lib_v5/modelparams/4band_44100_reverse.json")
param_name_auto = str("4band_44100_reverse")
if "4band_44100_sw" in ModelName:
model_params_auto = str("uvr5_pack/lib_v5/modelparams/4band_44100_sw.json")
param_name_auto = str("4band_44100_sw")
if "4band_v2" in ModelName:
model_params_auto = str("uvr5_pack/lib_v5/modelparams/4band_v2.json")
param_name_auto = str("4band_v2")
if "4band_v2_sn" in ModelName:
model_params_auto = str("uvr5_pack/lib_v5/modelparams/4band_v2_sn.json")
param_name_auto = str("4band_v2_sn")
if "tmodelparam" in ModelName:
model_params_auto = str("uvr5_pack/lib_v5/modelparams/tmodelparam.json")
param_name_auto = str("User Model Param Set")
return param_name_auto, model_params_auto
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