Spaces:
Sleeping
Sleeping
| import os | |
| import urllib.request | |
| from Utility.storage_config import MODELS_DIR | |
| def report(block_number, read_size, total_size): | |
| if block_number % 1000 == 0: | |
| return_to_front = '\b' * 52 | |
| percent = round(((block_number * read_size) / total_size) * 100) | |
| print(f"{return_to_front}[{'█' * (percent // 2)}{'.' * (50 - (percent // 2))}]", end='') | |
| if block_number * read_size >= total_size: | |
| return_to_front = '\b' * 52 | |
| print(f"{return_to_front}Download complete!\n") | |
| def download_models(): | |
| ############# | |
| print("Downloading Aligner Model") | |
| os.makedirs(os.path.join(MODELS_DIR, "Aligner"), exist_ok=True) | |
| filename, headers = urllib.request.urlretrieve( | |
| url="https://github.com/DigitalPhonetics/IMS-Toucan/releases/download/v2.5/aligner.pt", | |
| filename=os.path.abspath(os.path.join(MODELS_DIR, "Aligner", "aligner.pt")), | |
| reporthook=report) | |
| ############# | |
| print("Downloading Multilingual ToucanTTS Model") | |
| os.makedirs(os.path.join(MODELS_DIR, "ToucanTTS_Meta"), exist_ok=True) | |
| filename, headers = urllib.request.urlretrieve( | |
| url="https://github.com/DigitalPhonetics/IMS-Toucan/releases/download/v2.5/ToucanTTS_Meta.pt", | |
| filename=os.path.abspath(os.path.join(MODELS_DIR, "ToucanTTS_Meta", "best.pt")), | |
| reporthook=report) | |
| ############# | |
| print("Downloading Fast Vocoder Model") | |
| os.makedirs(os.path.join(MODELS_DIR, "Avocodo"), exist_ok=True) | |
| filename, headers = urllib.request.urlretrieve( | |
| url="https://github.com/DigitalPhonetics/IMS-Toucan/releases/download/v2.5/Avocodo.pt", | |
| filename=os.path.abspath(os.path.join(MODELS_DIR, "Avocodo", "best.pt")), | |
| reporthook=report) | |
| ############# | |
| print("Downloading Highest Quality Vocoder Model") | |
| os.makedirs(os.path.join(MODELS_DIR, "BigVGAN"), exist_ok=True) | |
| filename, headers = urllib.request.urlretrieve( | |
| url="https://github.com/DigitalPhonetics/IMS-Toucan/releases/download/v2.5/BigVGAN.pt", | |
| filename=os.path.abspath(os.path.join(MODELS_DIR, "BigVGAN", "best.pt")), | |
| reporthook=report) | |
| ############# | |
| print("Downloading Embedding Model") | |
| os.makedirs(os.path.join(MODELS_DIR, "Embedding"), exist_ok=True) | |
| filename, headers = urllib.request.urlretrieve( | |
| url="https://github.com/DigitalPhonetics/IMS-Toucan/releases/download/v2.5/embedding_function.pt", | |
| filename=os.path.abspath(os.path.join(MODELS_DIR, "Embedding", "embedding_function.pt")), | |
| reporthook=report) | |
| ############# | |
| print("Downloading Embedding GAN") | |
| os.makedirs(os.path.join(MODELS_DIR, "Embedding"), exist_ok=True) | |
| filename, headers = urllib.request.urlretrieve( | |
| url="https://github.com/DigitalPhonetics/IMS-Toucan/releases/download/v2.5/embedding_gan.pt", | |
| filename=os.path.abspath(os.path.join(MODELS_DIR, "Embedding", "embedding_gan.pt")), | |
| reporthook=report) | |
| if __name__ == '__main__': | |
| download_models() | |