initial refactor of rvc studio

2024-05-13 01:42:24 -04:00
parent 2d8f191d61
commit aa3493d87c
139 changed files with 25883 additions and 1 deletions
@@ -0,0 +1,30 @@
+from functools import lru_cache
+import os
+
+from ...lib import BASE_CACHE_DIR, PersistedDict
+
+MENU_ITEMS = {
+    "Get help": "https://github.com/SayanoAI/RVC-Studio/discussions",
+    "Report a Bug": "https://github.com/SayanoAI/RVC-Studio/issues",
+    "About": """This project provides a comprehensive platform for training RVC models and generating AI voice covers.
+    Check out this github for more info: https://github.com/SayanoAI/RVC-Studio
+    """
+}
+
+DEVICE_OPTIONS = ["cpu","cuda"]
+PITCH_EXTRACTION_OPTIONS = ["rmvpe","rmvpe+"]
+MERGE_OPTIONS=["median","mean","min","max"]
+TTS_MODELS = ["edge","speecht5"]
+N_THREADS_OPTIONS=[1,2,4,8,12,16]
+SR_MAP = {"32k": 32000,"40k": 40000, "48k": 48000}
+
+@lru_cache
+def get_servers():
+    os.makedirs(BASE_CACHE_DIR,exist_ok=True)
+    fname = os.path.join(BASE_CACHE_DIR,"servers.shelve")
+    servers = PersistedDict(fname)
+    return servers
+
+SERVERS = get_servers()
+RVC_INFERENCE_URL = SERVERS.RVC_INFERENCE_URL
+UVR_INFERENCE_URL = SERVERS.UVR_INFERENCE_URL
@@ -0,0 +1,121 @@
+import re
+from typing import IO, List, Tuple
+import unicodedata
+import requests
+import os
+import zipfile
+
+from ...lib import BASE_CACHE_DIR, BASE_MODELS_DIR
+
+RVC_DOWNLOAD_LINK = 'https://huggingface.co/datasets/SayanoAI/RVC-Studio/resolve/main/'
+MDX_MODELS = ["MDXNET/UVR-MDX-NET-vocal_FT.onnx"]
+KARAFAN_MODELS = ["karafan/MDX23C-8KFFT-InstVoc_HQ.ckpt"]
+VR_MODELS = ["UVR/UVR-DeEcho-DeReverb.pth","UVR/HP5-vocals+instrumentals.pth"]
+RVC_MODELS = [
+    "RVC/Claire.pth",
+    "RVC/Sayano.pth",
+    "RVC/Mae_v2.pth",
+    "RVC/Fuji.pth",
+    "RVC/Monika.pth"]
+BASE_MODELS = ["hubert_base.pt", "rmvpe.pt"]
+VITS_MODELS = ["VITS/pretrained_ljs.pth"]
+PRETRAINED_MODELS = [
+    "pretrained_v2/D48k.pth",
+    "pretrained_v2/G48k.pth",
+    "pretrained_v2/D32k.pth",
+    "pretrained_v2/G32k.pth",
+    "pretrained_v2/D40k.pth",
+    "pretrained_v2/G40k.pth",
+    "pretrained_v2/f0D48k.pth",
+    "pretrained_v2/f0G48k.pth",
+    "pretrained_v2/f0D40k.pth",
+    "pretrained_v2/f0G40k.pth",
+    "pretrained_v2/f0D32k.pth",
+    "pretrained_v2/f0G32k.pth",
+
+    "pretrained_v2/f0_RIN_E3_40k_D.pth",
+    "pretrained_v2/f0_RIN_E3_40k_G.pth",
+    "pretrained_v2/f0Ov2Super32kD.pth",
+    "pretrained_v2/f0Ov2Super32kG.pth",
+    "pretrained_v2/f0Ov2Super40kD.pth",
+    "pretrained_v2/f0Ov2Super40kG.pth",
+]
+LLM_MODELS = [
+    "https://huggingface.co/TheBloke/Airoboros-L2-7B-2.1-GGUF/resolve/main/airoboros-l2-7b-2.1.Q4_K_M.gguf",
+    "https://huggingface.co/TheBloke/Pygmalion-2-7B-GGUF/resolve/main/pygmalion-2-7b.Q4_K_M.gguf",
+    "https://huggingface.co/TheBloke/Zarablend-MX-L2-7B-GGUF/resolve/main/zarablend-mx-l2-7b.Q4_K_M.gguf",
+    "https://huggingface.co/TheBloke/MythoMax-L2-Kimiko-v2-13B-GGUF/resolve/main/mythomax-l2-kimiko-v2-13b.Q4_K_M.gguf"
+]
+STT_MODELS = [
+    "https://alphacephei.com/vosk/models/vosk-model-en-us-0.22-lgraph.zip"
+]
+
+def download_file(params: Tuple[str, str]):
+    model_path, download_link = params
+    if os.path.isfile(model_path): raise FileExistsError(f"{model_path} already exists!")
+    os.makedirs(os.path.dirname(model_path), exist_ok=True)
+    
+    with requests.get(download_link,stream=True) as r:
+        r.raise_for_status()
+        with open(model_path, 'wb') as f:
+            for chunk in r.iter_content(chunk_size=8192):
+                f.write(chunk)
+        return True
+
+def download_link_generator(download_link: str,model_list: List[str]):
+    for model in model_list:
+        model_path = os.path.join(BASE_MODELS_DIR,model)
+        yield (model_path, f"{download_link}{model}")
+
+def save_file(params: Tuple[str, any]):
+    (data_path, datum) = params
+    if "zip" in os.path.splitext(data_path)[-1]: return save_zipped_files(params) # unzip
+    else:
+        try:
+            with open(data_path,"wb") as f:
+                f.write(datum)
+            return f"Successfully saved file to: {data_path}"
+        except Exception as e:
+            return f"Failed to save file: {e}"
+
+def save_file_generator(save_dir: str, data: List[IO]):
+    for datum in data:
+        data_path = os.path.join(save_dir,datum.name)
+        yield (data_path, datum.read())
+
+def save_zipped_files(params: Tuple[str, any]):
+    (data_path, datum) = params
+
+    try:
+        print(f"saving zip file: {data_path}")
+        temp_dir = os.path.join(BASE_CACHE_DIR,"zips")
+        os.makedirs(temp_dir,exist_ok=True)
+        name = os.path.basename(data_path)
+        zip_path = os.path.join(temp_dir,name)
+
+        with open(zip_path,"wb") as f:
+            f.write(datum)
+
+        print(f"extracting zip file: {zip_path}")
+        with zipfile.ZipFile(zip_path, 'r') as zip_ref:
+            zip_ref.extractall(os.path.dirname(data_path))
+        print(f"finished extracting zip file")
+        
+        os.remove(zip_path) # cleanup
+        return f"Successfully saved files to: {data_path}"
+    except Exception as e:
+        return f"Failed to save files: {e}"
+    
+def slugify_filepath(filepath):
+    # Split the path into directory and filename
+    directory, filename = os.path.split(filepath)
+    # Normalize the filename
+    filename = unicodedata.normalize('NFKD', filename)
+    # Encode the filename as ASCII and ignore errors
+    filename = filename.encode('ascii', 'ignore').decode()
+    # Convert the filename to lowercase
+    filename = filename.lower()
+    # Replace spaces and other unwanted characters with dashes
+    filename = re.sub(r'[^a-z0-9.-]+', '-', filename)
+    # Join the directory and the slugified filename
+    return os.path.join(directory, filename)