Spaces:
Running
Running
| 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] | |
| try: | |
| split_audio = sys.argv[10] | |
| except IndexError: | |
| split_audio = None | |
| 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}") | |