RVC: RMVPE support

server/voice_changer/RVC/pipeline/Pipeline.py

@@ -124,8 +124,10 @@ class Pipeline(object):
             else:
                 pitch = None
                 pitchf = None
-        except IndexError:
+        except IndexError as e:  # NOQA
             # print(e)
+            # import traceback
+            # traceback.print_exc()
             raise NotEnoughDataExtimateF0()
 
         # tensor型調整

server/voice_changer/RVC/pitchExtractor/PitchExtractorManager.py

@@ -5,6 +5,7 @@ from voice_changer.RVC.pitchExtractor.DioPitchExtractor import DioPitchExtractor
 from voice_changer.RVC.pitchExtractor.HarvestPitchExtractor import HarvestPitchExtractor
 from voice_changer.RVC.pitchExtractor.CrepePitchExtractor import CrepePitchExtractor
 from voice_changer.RVC.pitchExtractor.PitchExtractor import PitchExtractor
+from voice_changer.RVC.pitchExtractor.RMVPEPitchExtractor import RMVPEPitchExtractor
 from voice_changer.utils.VoiceChangerParams import VoiceChangerParams
 
 
@@ -37,6 +38,8 @@ class PitchExtractorManager(Protocol):
             return CrepeOnnxPitchExtractor(pitchExtractorType, cls.params.crepe_onnx_tiny, gpu)
         elif pitchExtractorType == "crepe_full":
             return CrepeOnnxPitchExtractor(pitchExtractorType, cls.params.crepe_onnx_full, gpu)
+        elif pitchExtractorType == "rmvpe":
+            return RMVPEPitchExtractor(cls.params.rmvpe, gpu)
         else:
             # return hubert as default
             print("[Voice Changer] PitchExctractor not found", pitchExtractorType)

server/voice_changer/RVC/pitchExtractor/RMVPEPitchExtractor.py

@@ -0,0 +1,49 @@
+import torch
+import numpy as np
+from const import PitchExtractorType
+from voice_changer.DiffusionSVC.pitchExtractor.PitchExtractor import PitchExtractor
+from voice_changer.DiffusionSVC.pitchExtractor.rmvpe.rmvpe import RMVPE
+
+
+class RMVPEPitchExtractor(PitchExtractor):
+
+    def __init__(self, file: str, gpu: int):
+        super().__init__()
+        self.pitchExtractorType: PitchExtractorType = "rmvpe"
+        self.f0_min = 50
+        self.f0_max = 1100
+        self.f0_mel_min = 1127 * np.log(1 + self.f0_min / 700)
+        self.f0_mel_max = 1127 * np.log(1 + self.f0_max / 700)
+
+        self.uv_interp = True
+        self.input_sr = -1
+        if torch.cuda.is_available() and gpu >= 0:
+            self.device = torch.device("cuda:" + str(torch.cuda.current_device()))
+        else:
+            self.device = torch.device("cpu")
+
+        self.rmvpe = RMVPE(model_path=file, is_half=False, device=self.device)
+
+    def extract(self, audio, pitchf, f0_up_key, sr, window, silence_front=0):
+        hop_size = 160  # RMVPE固定
+
+        offset_frame_number = silence_front * 16000
+        start_frame = int(offset_frame_number / hop_size)  # frame
+        real_silence_front = start_frame * hop_size / 16000  # 秒
+        audio = audio[int(np.round(real_silence_front * 16000)):]
+
+        f0 = self.rmvpe.infer_from_audio_t(audio, thred=0.03)
+
+        f0 = f0 * 2 ** (float(f0_up_key) / 12)
+        pitchf[-f0.shape[0]:] = f0[:pitchf.shape[0]]
+        f0 = pitchf
+
+        f0bak = f0.copy()
+        f0_mel = 1127 * np.log(1 + f0 / 700)
+        f0_mel[f0_mel > 0] = (f0_mel[f0_mel > 0] - self.f0_mel_min) * 254 / (
+            self.f0_mel_max - self.f0_mel_min
+        ) + 1
+        f0_mel[f0_mel <= 1] = 1
+        f0_mel[f0_mel > 255] = 255
+        f0_coarse = np.rint(f0_mel).astype(int)
+        return f0_coarse, f0bak