Update infer/modules/vc/pipeline.py

infer/modules/vc/pipeline.py

@@ -7,7 +7,7 @@ logger = logging.getLogger(__name__)
 
 from functools import lru_cache
 from time import time as ttime
-
+from torchfcpe import spawn_bundled_infer_model
 import faiss
 import librosa
 import numpy as np
@@ -61,6 +61,18 @@ def change_rms(data1, sr1, data2, sr2, rate):  # 1是输入音频，2是输出
     ).numpy()
     return data2
 
+def get_torchfcpe(self, x, sr, f0_min, f0_max, p_len, *args, **kwargs):
+        self.model_torchfcpe = spawn_bundled_infer_model(device=self.device)
+        f0 = self.model_torchfcpe.infer(
+            torch.from_numpy(x).float().unsqueeze(0).unsqueeze(-1).to(self.device),
+            sr=sr,
+            decoder_mode="local_argmax",
+            threshold=0.006,
+            f0_min=f0_min,
+            f0_max=f0_max,
+            output_interp_target_length=p_len
+        )
+        return f0.squeeze().cpu().numpy()
 
 class Pipeline(object):
     def __init__(self, tgt_sr, config):
@@ -139,6 +151,8 @@ class Pipeline(object):
             f0 = torchcrepe.filter.mean(f0, 3)
             f0[pd < 0.1] = 0
             f0 = f0[0].cpu().numpy()
+        elif method == "torchfcpe":
+            f0 = self.get_torchfcpe(x, self.sr, f0_min, f0_max, p_len)
         elif f0_method == "rmvpe":
             if not hasattr(self, "model_rmvpe"):
                 from infer.lib.rmvpe import RMVPE