From ad4adc960f5267ae1c9668c90c5101208a8f5844 Mon Sep 17 00:00:00 2001 From: mrq Date: Fri, 17 Feb 2023 20:10:27 +0000 Subject: [PATCH] small fixes --- README.md | 2 +- src/utils.py | 21 ++++++++++++++------- 2 files changed, 15 insertions(+), 8 deletions(-) diff --git a/README.md b/README.md index 811d70e..cbd425c 100755 --- a/README.md +++ b/README.md @@ -12,4 +12,4 @@ This is not endorsed by [neonbjb](https://github.com/neonbjb/). I do not expect ## Documentation -Please consult [the wiki](https://git.ecker.tech/mrq/ai-voice-cloning/wiki) for documentation. \ No newline at end of file +Please consult [the wiki](https://git.ecker.tech/mrq/ai-voice-cloning/wiki) for the documentation, including how to install, prepare voices for, and use the software. \ No newline at end of file diff --git a/src/utils.py b/src/utils.py index 3545fcf..5af1777 100755 --- a/src/utils.py +++ b/src/utils.py @@ -55,7 +55,7 @@ def setup_args(): 'sample-batch-size': None, 'embed-output-metadata': True, 'latents-lean-and-mean': True, - 'voice-fixer': True, + 'voice-fixer': False, # getting tired of long initialization times in a Colab for downloading a large dataset for it 'voice-fixer-use-cuda': True, 'force-cpu-for-conditioning-latents': False, 'device-override': None, @@ -167,7 +167,7 @@ def generate( progress(0, desc="Loading voice...") voice_samples, conditioning_latents = load_voice(voice) - if voice_samples is not None: + if voice_samples is not None and len(voice_samples) > 0: sample_voice = torch.cat(voice_samples, dim=-1).squeeze().cpu() conditioning_latents = tts.get_conditioning_latents(voice_samples, return_mels=not args.latents_lean_and_mean, progress=progress, slices=voice_latents_chunks, force_cpu=args.force_cpu_for_conditioning_latents) @@ -374,7 +374,7 @@ def generate( with open(f'{outdir}/{voice}_{name}.json', 'w', encoding="utf-8") as f: f.write(json.dumps(info, indent='\t') ) - if args.voice_fixer and voicefixer: + if args.voice_fixer and voicefixer is not None: fixed_output_voices = [] for path in progress.tqdm(output_voices, desc="Running voicefix..."): fixed = path.replace(".wav", "_fixed.wav") @@ -409,6 +409,7 @@ def generate( if 'latents' in info: del info['latents'] + os.makedirs('./config/', exist_ok=True) with open(f'./config/generate.json', 'w', encoding="utf-8") as f: f.write(json.dumps(info, indent='\t') ) @@ -422,13 +423,18 @@ def generate( stats, ) +import subprocess + def run_training(config_path): + print("Unloading TTS to save VRAM.") global tts del tts tts = None - import subprocess - subprocess.run(["python", "./src/train.py", "-opt", config_path], env=os.environ.copy(), shell=True, stdout=subprocess.PIPE) + cmd = ["python", "./src/train.py", "-opt", config_path] + + print("Spawning process: ", " ".join(cmd)) + subprocess.run(cmd, env=os.environ.copy(), shell=True, stdout=subprocess.STDOUT, stderr=subprocess.STDOUT) """ from train import train train(config) @@ -501,7 +507,7 @@ def prepare_dataset( files, outdir, language=None ): for file in files: print(f"Transcribing file: {file}") - result = whisper_model.transcribe(file, language=language) + result = whisper_model.transcribe(file, language=language if language else "English") results[os.path.basename(file)] = result print(f"Transcribed file: {file}, {len(result['segments'])} found.") @@ -557,7 +563,7 @@ def import_voice(file, saveAs = None): path = f"{outdir}/{os.path.basename(filename)}" waveform, sampling_rate = torchaudio.load(filename) - if args.voice_fixer: + if args.voice_fixer and voicefixer is not None: # resample to best bandwidth since voicefixer will do it anyways through librosa if sampling_rate != 44100: print(f"Resampling imported voice sample: {path}") @@ -714,6 +720,7 @@ def export_exec_settings( listen, share, check_for_updates, models_from_local_on 'output-volume': args.output_volume, } + os.makedirs('./config/', exist_ok=True) with open(f'./config/exec.json', 'w', encoding="utf-8") as f: f.write(json.dumps(settings, indent='\t') )