rvc/infer/infer.py

import os
import sys
import torch
import numpy as np
import soundfile as sf
from vc_infer_pipeline import VC
from rvc.lib.utils import load_audio
from rvc.lib.tools.split_audio import process_audio, merge_audio
from fairseq import checkpoint_utils
from rvc.lib.infer_pack.models import (
    SynthesizerTrnMs256NSFsid,
    SynthesizerTrnMs256NSFsid_nono,
    SynthesizerTrnMs768NSFsid,
    SynthesizerTrnMs768NSFsid_nono,
)

from rvc.configs.config import Config

config = Config()

torch.manual_seed(114514)
hubert_model = None


def load_hubert():
    global hubert_model
    models, _, _ = checkpoint_utils.load_model_ensemble_and_task(
        ["hubert_base.pt"],
        suffix="",
    )
    hubert_model = models[0]
    hubert_model = hubert_model.to(config.device)
    if config.is_half:
        hubert_model = hubert_model.half()
    else:
        hubert_model = hubert_model.float()
    hubert_model.eval()


def vc_single(
    sid=0,
    input_audio_path=None,
    f0_up_key=None,
    f0_file=None,
    f0_method=None,
    file_index=None,
    index_rate=None,
    resample_sr=0,
    rms_mix_rate=1,
    protect=0.33,
    hop_length=None,
    output_path=None,
    split_audio=False,
):
    global tgt_sr, net_g, vc, hubert_model, version

    if input_audio_path is None:
        return "Please, load an audio!", None

    f0_up_key = int(f0_up_key)
    try:
        audio = load_audio(input_audio_path, 16000)
        audio_max = np.abs(audio).max() / 0.95

        if audio_max > 1:
            audio /= audio_max

        if not hubert_model:
            load_hubert()
        if_f0 = cpt.get("f0", 1)

        file_index = (
            file_index.strip(" ")
            .strip('"')
            .strip("\n")
            .strip('"')
            .strip(" ")
            .replace("trained", "added")
        )
        if tgt_sr != resample_sr >= 16000:
            tgt_sr = resample_sr
        if split_audio == "True":
            result, new_dir_path = process_audio(input_audio_path)
            if result == "Error":
                return "Error with Split Audio", None
            dir_path = new_dir_path.strip(" ").strip('"').strip("\n").strip('"').strip(" ")
            if dir_path != "":
                paths = [
                    os.path.join(root, name)
                    for root, _, files in os.walk(dir_path, topdown=False)
                    for name in files
                    if name.endswith(".wav") and root == dir_path
                ]
            try:
                for path in paths:
                    info, opt = vc_single(
                        sid,
                        path,
                        f0_up_key,
                        None,
                        f0_method,
                        file_index,
                        index_rate,
                        resample_sr,
                        rms_mix_rate,
                        protect,
                        hop_length,
                        path,
                        False,
                    )
                    #new_dir_path
            except Exception as error:
                print(error)
                return "Error", None
            print("Finished processing segmented audio, now merging audio...")
            merge_timestamps_file = os.path.join(os.path.dirname(new_dir_path), f"{os.path.basename(input_audio_path).split('.')[0]}_timestamps.txt")
            tgt_sr, audio_opt  = merge_audio(merge_timestamps_file)
      
        else:
            audio_opt = vc.pipeline(
                hubert_model,
                net_g,
                sid,
                audio,
                input_audio_path,
                f0_up_key,
                f0_method,
                file_index,
                index_rate,
                if_f0,
                filter_radius,
                tgt_sr,
                resample_sr,
                rms_mix_rate,
                version,
                protect,
                hop_length,
                f0_file=f0_file,
            )
        

        if output_path is not None:
            sf.write(output_path, audio_opt, tgt_sr, format="WAV")

        return (tgt_sr, audio_opt)

    except Exception as error:
        print(error)


def get_vc(weight_root, sid):
    global n_spk, tgt_sr, net_g, vc, cpt, version
    if sid == "" or sid == []:
        global hubert_model
        if hubert_model is not None:
            print("clean_empty_cache")
            del net_g, n_spk, vc, hubert_model, tgt_sr  # ,cpt
            hubert_model = net_g = n_spk = vc = hubert_model = tgt_sr = None
            if torch.cuda.is_available():
                torch.cuda.empty_cache()

            if_f0 = cpt.get("f0", 1)
            version = cpt.get("version", "v1")
            if version == "v1":
                if if_f0 == 1:
                    net_g = SynthesizerTrnMs256NSFsid(
                        *cpt["config"], is_half=config.is_half
                    )
                else:
                    net_g = SynthesizerTrnMs256NSFsid_nono(*cpt["config"])
            elif version == "v2":
                if if_f0 == 1:
                    net_g = SynthesizerTrnMs768NSFsid(
                        *cpt["config"], is_half=config.is_half
                    )
                else:
                    net_g = SynthesizerTrnMs768NSFsid_nono(*cpt["config"])
            del net_g, cpt
            if torch.cuda.is_available():
                torch.cuda.empty_cache()
            cpt = None
    person = weight_root
    cpt = torch.load(person, map_location="cpu")
    tgt_sr = cpt["config"][-1]
    cpt["config"][-3] = cpt["weight"]["emb_g.weight"].shape[0]
    if_f0 = cpt.get("f0", 1)

    version = cpt.get("version", "v1")
    if version == "v1":
        if if_f0 == 1:
            net_g = SynthesizerTrnMs256NSFsid(*cpt["config"], is_half=config.is_half)
        else:
            net_g = SynthesizerTrnMs256NSFsid_nono(*cpt["config"])
    elif version == "v2":
        if if_f0 == 1:
            net_g = SynthesizerTrnMs768NSFsid(*cpt["config"], is_half=config.is_half)
        else:
            net_g = SynthesizerTrnMs768NSFsid_nono(*cpt["config"])
    del net_g.enc_q
    print(net_g.load_state_dict(cpt["weight"], strict=False))
    net_g.eval().to(config.device)
    if config.is_half:
        net_g = net_g.half()
    else:
        net_g = net_g.float()
    vc = VC(tgt_sr, config)
    n_spk = cpt["config"][-3]


f0up_key = sys.argv[1]
filter_radius = sys.argv[2]
index_rate = float(sys.argv[3])
hop_length = sys.argv[4]
f0method = sys.argv[5]

audio_input_path = sys.argv[6]
audio_output_path = sys.argv[7]

model_path = sys.argv[8]
index_path = sys.argv[9]
split_audio = sys.argv[10]

sid = f0up_key
input_audio = audio_input_path
f0_pitch = f0up_key
f0_file = None
f0_method = f0method
file_index = index_path
index_rate = index_rate
output_file = audio_output_path
split_audio = split_audio

get_vc(model_path, 0)

try:
    result, audio_opt = vc_single(
        sid=0,
        input_audio_path=input_audio,
        f0_up_key=f0_pitch,
        f0_file=None,
        f0_method=f0_method,
        file_index=file_index,
        index_rate=index_rate,
        hop_length=hop_length,
        output_path=output_file,
        split_audio=split_audio
    )

    if os.path.exists(output_file) and os.path.getsize(output_file) > 0:
        message = result
    else:
        message = result

    print(f"Conversion completed. Output file: '{output_file}'")

except Exception as error:
    print(f"Voice conversion failed: {error}")