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import os
import torch
import torchvision.transforms as transforms
from huggingface_hub import snapshot_download
from PIL import Image
MODEL_DIR = snapshot_download(
"ccmusic-database/chest_falsetto",
cache_dir="./__pycache__",
)
def toCUDA(x):
if hasattr(x, "cuda"):
if torch.cuda.is_available():
return x.cuda()
return x
def find_files(folder_path=f"{MODEL_DIR}/examples", ext=".wav"):
wav_files = []
for root, _, files in os.walk(folder_path):
for file in files:
if file.endswith(ext):
file_path = os.path.join(root, file)
wav_files.append(file_path)
return wav_files
def get_modelist(model_dir=MODEL_DIR, assign_model=""):
try:
entries = os.listdir(model_dir)
except OSError as e:
print(f"Cannot access {model_dir}: {e}")
return
output = []
for entry in entries:
full_path = os.path.join(model_dir, entry)
if entry == ".git" or entry == "examples":
print(f"Skip .git / examples dir: {full_path}")
continue
if os.path.isdir(full_path):
model = os.path.basename(full_path)
if assign_model and assign_model.lower() in model:
output.insert(0, model)
else:
output.append(model)
return output
def embed_img(img_path: str, input_size=224):
transform = transforms.Compose(
[
transforms.Resize([input_size, input_size]),
transforms.ToTensor(),
transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5)),
]
)
img = Image.open(img_path).convert("RGB")
return transform(img).unsqueeze(0)
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