forked from mrq/tortoise-tts
revamped result formatting, added "kludgy" stop button
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9e0fbff545
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4f903159ee
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@ -36,6 +36,8 @@ from tortoise.utils.device import get_device, get_device_name, get_device_batch_
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pbar = None
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STOP_SIGNAL = False
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MODELS_DIR = os.environ.get('TORTOISE_MODELS_DIR')
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MODELS = {
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'autoregressive.pth': 'https://huggingface.co/jbetker/tortoise-tts-v2/resolve/main/.models/autoregressive.pth',
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@ -49,6 +51,11 @@ MODELS = {
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}
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def tqdm_override(arr, verbose=False, progress=None, desc=None):
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global STOP_SIGNAL
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if STOP_SIGNAL:
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STOP_SIGNAL = False
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raise Exception("Kill signal detected")
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if verbose and desc is not None:
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print(desc)
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@ -60,6 +67,7 @@ def download_models(specific_models=None):
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"""
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Call to download all the models that Tortoise uses.
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"""
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os.makedirs(MODELS_DIR, exist_ok=True)
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def show_progress(block_num, block_size, total_size):
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61
webui.py
61
webui.py
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@ -16,6 +16,8 @@ from datetime import datetime
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from fastapi import FastAPI
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import tortoise.api
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from tortoise.api import TextToSpeech
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from tortoise.utils.audio import load_audio, load_voice, load_voices, get_voice_dir
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from tortoise.utils.text import split_and_recombine_text
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@ -124,7 +126,7 @@ def generate(
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start_time = time.time()
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outdir = f"./results/{voice}/{int(start_time)}/"
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outdir = f"./results/{voice}/"
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os.makedirs(outdir, exist_ok=True)
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audio_cache = {}
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@ -140,6 +142,22 @@ def generate(
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volume_adjust = torchaudio.transforms.Vol(gain=args.output_volume, gain_type="amplitude") if args.output_volume != 1 else None
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idx = 0
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for i, file in enumerate(os.listdir(outdir)):
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if file[-4:] == ".wav":
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idx = idx + 1
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def get_name(line=0, candidate=0, combined=False):
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name = f"{idx}"
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if len(texts) > 1:
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name = f"{name}_{line}"
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if candidates > 1:
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name = f"{name}_{candidate}"
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if combined:
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return f"{idx}_combined"
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return name
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for line, cut_text in enumerate(texts):
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if emotion == "Custom":
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if prompt.strip() != "":
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@ -154,13 +172,14 @@ def generate(
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if isinstance(gen, list):
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for j, g in enumerate(gen):
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os.makedirs(f'{outdir}/candidate_{j}', exist_ok=True)
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audio_cache[f"candidate_{j}/result_{line}.wav"] = {
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name = get_name(line=line, candidate=j)
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audio_cache[name] = {
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'audio': g,
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'text': cut_text,
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}
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else:
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audio_cache[f"result_{line}.wav"] = {
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name = get_name(line=line)
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audio_cache[name] = {
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'audio': gen,
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'text': cut_text,
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}
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@ -173,7 +192,7 @@ def generate(
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audio = volume_adjust(audio)
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audio_cache[k]['audio'] = audio
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torchaudio.save(f'{outdir}/{k}', audio, args.output_sample_rate)
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torchaudio.save(f'{outdir}/{voice}_{k}.wav', audio, args.output_sample_rate)
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output_voice = None
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@ -182,30 +201,29 @@ def generate(
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audio_clips = []
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for line in range(len(texts)):
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if isinstance(gen, list):
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audio = audio_cache[f'candidate_{candidate}/result_{line}.wav']['audio']
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name = get_name(line=line, candidate=candidate)
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audio = audio_cache[name]['audio']
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else:
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audio = audio_cache[f'result_{line}.wav']['audio']
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name = get_name(line=line)
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audio = audio_cache[name]['audio']
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audio_clips.append(audio)
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name = get_name(combined=True)
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audio = torch.cat(audio_clips, dim=-1)
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torchaudio.save(f'{outdir}/combined_{candidate}.wav', audio, args.output_sample_rate)
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torchaudio.save(f'{outdir}/{voice}_{name}.wav', audio, args.output_sample_rate)
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audio = audio.squeeze(0).cpu()
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audio_cache[f'combined_{candidate}.wav'] = {
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audio_cache[name] = {
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'audio': audio,
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'text': cut_text,
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}
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if output_voice is None:
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output_voice = f'{outdir}/combined_{candidate}.wav'
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output_voice = f'{outdir}/{voice}_{name}.wav'
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# output_voice = audio
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else:
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if isinstance(gen, list):
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output_voice = f'{outdir}/candidate_0/result_0.wav'
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#output_voice = gen[0]
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else:
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output_voice = f'{outdir}/result_0.wav'
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#output_voice = gen
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name = get_name()
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output_voice = f'{outdir}/{voice}_{name}.wav'
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info = {
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'text': text,
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@ -231,7 +249,7 @@ def generate(
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'time': time.time()-start_time,
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}
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with open(f'{outdir}/input.json', 'w', encoding="utf-8") as f:
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with open(f'{outdir}/input_{idx}.json', 'w', encoding="utf-8") as f:
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f.write(json.dumps(info, indent='\t') )
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if voice is not None and conditioning_latents is not None:
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@ -242,7 +260,7 @@ def generate(
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for path in audio_cache:
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info['text'] = audio_cache[path]['text']
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metadata = music_tag.load_file(f"{outdir}/{path}")
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metadata = music_tag.load_file(f"{outdir}/{voice}_{path}.wav")
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metadata['lyrics'] = json.dumps(info)
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metadata.save()
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@ -389,6 +407,9 @@ def check_for_updates():
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def reload_tts():
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tts = setup_tortoise()
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def cancel_generate():
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tortoise.api.STOP_SIGNAL = True
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def update_voices():
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return gr.Dropdown.update(choices=sorted(os.listdir(get_voice_dir())) + ["microphone"])
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@ -574,7 +595,7 @@ def setup_gradio():
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usedSeed = gr.Textbox(label="Seed", placeholder="0", interactive=False)
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submit = gr.Button(value="Generate")
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#stop = gr.Button(value="Stop")
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stop = gr.Button(value="Stop")
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with gr.Tab("Utilities"):
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with gr.Row():
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with gr.Column():
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@ -676,7 +697,7 @@ def setup_gradio():
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if args.check_for_updates:
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webui.load(check_for_updates)
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#stop.click(fn=None, inputs=None, outputs=None, cancels=[submit_event])
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stop.click(fn=cancel_generate, inputs=None, outputs=None, cancels=[submit_event])
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webui.queue(concurrency_count=args.concurrency_count)
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