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barghavani
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Delete app.py
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app.py
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# -*- coding: utf-8 -*-
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"""app
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Automatically generated by Colaboratory.
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Original file is located at
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https://colab.research.google.com/drive/1LnYpxRP3tX4uiJ-gnE2YN6hhSdJ-rvTz
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"""
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import tempfile ,os
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from TTS.config import load_config
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import gradio as gr
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from TTS.utils.manage import ModelManager
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from TTS.utils.synthesizer import Synthesizer
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MODEL_NAMES=[
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"vits male azure(best)",
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"common voice reduce",
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"vits arman ebook",
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#"persian-tts-grapheme-arm24-finetuned-on1",
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#"glowtts-male",
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#"glowtts-female",
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#"female tacotron2"
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]
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MAX_TXT_LEN = 800
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model_path = os.getcwd() + "/best_model.pth"
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config_path = os.getcwd() + "/config.json"
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from TTS.utils.download import download_url
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modelInfo=[
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["vits-male-azure","best_model_15934.pth","config.json","saillab/persian-tts-azure-grapheme-60K/resolve/main/"],
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["common_voice_reduce","checkpoint_26000.pth","config.json","https://huggingface.co/saillab/persian-tts-cv15-reduct-grapheme-multispeaker/resolve/main/"],
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["vits_arman_ebook","best_model_66651.pth","config.json","https://huggingface.co/saillab/persian-tts-grapheme-arm24-finetuned-on1/resolve/main/"]
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#["glowtts-female","best_model.pth","config.json","https://huggingface.co/Kamtera/persian-tts-female-glow_tts/resolve/main/"],
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#["vits male1 (best)","checkpoint_88000.pth","config.json","https://huggingface.co/Kamtera/persian-tts-male1-vits/resolve/main/"],
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#["vits female1","checkpoint_50000.pth","config.json","https://huggingface.co/Kamtera/persian-tts-female1-vits/resolve/main/"],
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#["female tacotron2","checkpoint_313000.pth","config.json","https://huggingface.co/Kamtera/persian-tts-female-tacotron2/resolve/main/"]
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]
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for d in modelInfo:
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directory=d[0]
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if not os.path.exists(directory):
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os.makedirs(directory)
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print("|> Downloading: ",directory)
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download_url(
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d[3]+d[1],directory,"best_model.pth"
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)
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download_url(
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d[3]+d[2],directory,"config.json"
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)
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def tts(text: str,model_name: str):
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if len(text) > MAX_TXT_LEN:
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text = text[:MAX_TXT_LEN]
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print(f"Input text was cutoff since it went over the {MAX_TXT_LEN} character limit.")
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print(text)
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# synthesize
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synthesizer = Synthesizer(
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model_name+"/best_model.pth", model_name+"/config.json"
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)
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if synthesizer is None:
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raise NameError("model not found")
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wavs = synthesizer.tts(text)
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# return output
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with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as fp:
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synthesizer.save_wav(wavs, fp)
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return fp.name
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description="""
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This is a demo of persian text to speech model.
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**Github : https://github.com/UNHSAILLab/Persian-TTS **
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Models can be found here: <br>
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|Model|Dataset|
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|----|------|
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|["vits male azure(best)"](https://huggingface.co/saillab/persian-tts-azure-grapheme-60K)|
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|["common voice reduce"](https://huggingface.co/saillab/persian-tts-cv15-reduct-grapheme-multispeaker)|
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|["vits arman ebook"](https://huggingface.co/saillab/persian-tts-grapheme-arm24-finetuned-on1)|
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"""
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article= ""
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examples=[
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["و خداوند شما را با ارسال روح در جسم زندگانی و حیات بخشید","vits male azure(best)"],
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["تاجر تو چه تجارت می کنی ، تو را چه که چه تجارت می کنم؟","vits male azure(best)"],
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["شیش سیخ جیگر سیخی شیش هزار","vits male azure(best)"],
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["سه شیشه شیر ، سه سیر سرشیر","vits male azure(best)"],
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["دزدی دزدید ز بز دزدی بزی ، عجب دزدی که دزدید ز بز دزدی بزی","vits male azure(best)"],
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["مثنوی یکی از قالب های شعری است ک هر بیت قافیه ی جداگانه دارد","vits male azure(best)"],
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["در گلو ماند خس او سالها، چیست آن خس مهر جاه و مالها","vits male azure(best)"],
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]
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iface = gr.Interface(
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fn=tts,
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inputs=[
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gr.Textbox(
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label="Text",
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value="برای گسترش زبان فارسی به ما بپیوندید و در این مسیر ما را یاری کنید",
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),
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gr.Radio(
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label="Pick a TTS Model ",
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choices=MODEL_NAMES,
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value="vits-female",
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),
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],
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outputs=gr.Audio(label="Output",type='filepath'),
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examples=examples,
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title="🗣️ Persian tts 🗣️",
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description=description,
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article=article,
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live=False
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)
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iface.launch(share=False)
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