Spaces:
Running
on
Zero
Running
on
Zero
File size: 3,955 Bytes
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import os
from concurrent.futures import ThreadPoolExecutor
from tqdm import tqdm
import requests
url_base = "https://huggingface.co./IAHispano/Applio/resolve/main/Resources"
pretraineds_v1_list = [
(
"pretrained_v1/",
[
"D32k.pth",
"D40k.pth",
"D48k.pth",
"G32k.pth",
"G40k.pth",
"G48k.pth",
"f0D32k.pth",
"f0D40k.pth",
"f0D48k.pth",
"f0G32k.pth",
"f0G40k.pth",
"f0G48k.pth",
],
),
]
pretraineds_v2_list = [
(
"pretrained_v2/",
[
"D32k.pth",
"D40k.pth",
"D48k.pth",
"G32k.pth",
"G40k.pth",
"G48k.pth",
"f0D32k.pth",
"f0D40k.pth",
"f0D48k.pth",
"f0G32k.pth",
"f0G40k.pth",
"f0G48k.pth",
],
),
]
models_list = [
(
"predictors/",
[
"rmvpe.pt",
"fcpe.pt",
],
),
]
embedders_list = [
(
"embedders/",
[
"contentvec_base.pt",
],
),
]
executables_list = ["ffmpeg.exe", "ffprobe.exe"]
folder_mapping_list = {
"pretrained_v1/": "rvc/models/pretraineds/pretrained_v1/",
"pretrained_v2/": "rvc/models/pretraineds/pretrained_v2/",
"embedders/": "rvc/models/embedders/",
"predictors/": "rvc/models/predictors/",
}
def download_file(url, destination_path, desc):
if not os.path.exists(destination_path):
os.makedirs(os.path.dirname(destination_path) or ".", exist_ok=True)
response = requests.get(url, stream=True)
total_size = int(response.headers.get("content-length", 0))
block_size = 1024
t = tqdm(total=total_size, unit="iB", unit_scale=True, desc=desc)
with open(destination_path, "wb") as file:
for data in response.iter_content(block_size):
t.update(len(data))
file.write(data)
t.close()
if total_size != 0 and t.n != total_size:
print("ERROR: Something went wrong during the download")
def download_files(file_list):
with ThreadPoolExecutor() as executor:
futures = []
for file_name in file_list:
destination_path = os.path.join(file_name)
url = f"{url_base}/{file_name}"
futures.append(
executor.submit(download_file, url, destination_path, file_name)
)
for future in futures:
future.result()
def download_mapping_files(list):
with ThreadPoolExecutor() as executor:
futures = []
for remote_folder, file_list in list:
local_folder = folder_mapping_list.get(remote_folder, "")
for file in file_list:
destination_path = os.path.join(local_folder, file)
url = f"{url_base}/{remote_folder}{file}"
futures.append(
executor.submit(
download_file, url, destination_path, f"{remote_folder}{file}"
)
)
for future in futures:
future.result()
def prequisites_download_pipeline(pretraineds_v1, pretraineds_v2, models, exe):
if models == True:
download_mapping_files(models_list)
download_mapping_files(embedders_list)
if exe == True:
if os.name == "nt":
download_files(executables_list)
else:
print("Executable files are only available for Windows")
if pretraineds_v1 == True:
download_mapping_files(pretraineds_v1_list)
if pretraineds_v2 == True:
download_mapping_files(pretraineds_v2_list)
# Clear the console after all downloads are completed
clear_console()
def clear_console():
if os.name == "nt":
os.system("cls")
else:
os.system("clear")
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