/
run_model_downloader.py
68 lines (56 loc) · 2.92 KB
/
run_model_downloader.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
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()