Spaces:
Runtime error
Runtime error
xJuuzouYTx
commited on
Commit
•
42cf67e
1
Parent(s):
66d588d
[ADD] error messages
Browse files- RVC_BOOK.ipynb +36 -0
- app.py +7 -0
- inference.py +6 -0
- utils/model.py +2 -17
RVC_BOOK.ipynb
ADDED
@@ -0,0 +1,36 @@
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# <font color='#018ada'>ULTIVC Juuxn Version</font>\n",
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"---\n",
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"![youtube.png](data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAMAAAAoLQ9TAAAAJ1BMVEVHcEz/AAD/AAD/AAD/AAD/AAD/AAD/AAD/AAD/////mJj/wcH/jY3aUCqcAAAACHRSTlMA8czbELSvDrGIfzkAAABCSURBVBiVY2AgA7CwMTMycgABIyMzGztQgIkDCTABBThQAEyAixtNgIeTkwu/AIYWZEMxrGVhZWaE8BiZWVnI8RoAJWEEDt2WmW4AAAAASUVORK5CYII=) **[YouTube](https://www.youtube.com/@Juuxn)**\n",
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"\n",
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"**Enlaces que podrían interesarte:**\n",
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"\n",
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"- [Tutorial para este cuaderno](https://www.youtube.com/watch?v=gTWA2qyzX7k) - [Tutorial para cuaderno tradicional](https://www.youtube.com/embed/R8-PivPpv8o) - [Transferir archivo de mega a Drive](https://colab.research.google.com/drive/1utTesfmBv-uQ8Upa7TEVpM57kmcq9YN6?usp=sharing)\n",
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"---"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"vscode": {
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"languageId": "plaintext"
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}
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},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"language_info": {
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"name": "python"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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app.py
CHANGED
@@ -70,6 +70,13 @@ def infer(model, f0_method, audio_file):
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def post_model(name, model_url, version, creator):
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modelname = model_downloader(model_url, zips_folder, unzips_folder)
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model_files = get_model(unzips_folder, modelname)
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md5_hash = calculate_md5(os.path.join(unzips_folder,model_files['pth']))
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zipfile = compress(modelname, list(model_files.values()))
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file_to_upload = open(zipfile, "rb")
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def post_model(name, model_url, version, creator):
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modelname = model_downloader(model_url, zips_folder, unzips_folder)
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model_files = get_model(unzips_folder, modelname)
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if not model_files:
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return "No se encontrado un modelo valido, verifica el contenido del enlace e intentalo más tarde."
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if not model_files.get('pth'):
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return "No se encontrado un modelo valido, verifica el contenido del enlace e intentalo más tarde."
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md5_hash = calculate_md5(os.path.join(unzips_folder,model_files['pth']))
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zipfile = compress(modelname, list(model_files.values()))
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file_to_upload = open(zipfile, "rb")
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inference.py
CHANGED
@@ -198,6 +198,12 @@ class Inference:
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modelname = model.model_downloader(self._model_name, "./zips/", "./weights/")
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model_info = model.get_model(os.path.join(current_dir, 'weights') , modelname)
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index = model_info.get('index', '')
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pth = model_info.get('pth', None)
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modelname = model.model_downloader(self._model_name, "./zips/", "./weights/")
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model_info = model.get_model(os.path.join(current_dir, 'weights') , modelname)
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if not model_info:
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return "No se encontrado un modelo valido, verifica el contenido del enlace e intentalo más tarde."
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if not model_info.get('pth'):
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return "No se encontrado un modelo valido, verifica el contenido del enlace e intentalo más tarde."
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index = model_info.get('index', '')
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pth = model_info.get('pth', None)
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utils/model.py
CHANGED
@@ -100,27 +100,12 @@ def model_downloader(url, zip_path, dest_path):
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else:
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return None
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def get_models(weight_path):
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# Obtener todos los elementos en la ruta
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files = os.listdir(weight_path)
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# Filtrar solo los directorios
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return [file for file in files if os.path.isdir(os.path.join(weight_path, file))]
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def get_model(weight_path, modelname):
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resources = {}
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for root, dirs, files in os.walk(os.path.join(weight_path, modelname)):
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for file in files:
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if file.endswith('.index'):
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resources['index'] = os.path.relpath(os.path.join(root, file))
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if file.endswith('.pth'):
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resources['pth'] = os.path.relpath(os.path.join(root, file), start=weight_path)
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return resources
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def get_audios(audios_path):
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# Obtener todos los elementos en la ruta
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files = os.listdir(audios_path)
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# Filtrar solo los directorios
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return [file for file in files if not os.path.isdir(os.path.join(audios_path, file)) and os.path.join(audios_path, file).endswith(('.mp3', '.wav'))]
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else:
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return None
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def get_model(weight_path, modelname):
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resources = {}
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for root, dirs, files in os.walk(os.path.join(weight_path, modelname)):
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for file in files:
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if file.endswith('.index'):
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resources['index'] = os.path.relpath(os.path.join(root, file))
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if file.endswith('.pth') and not 'G_' in file and not 'D_' in file:
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resources['pth'] = os.path.relpath(os.path.join(root, file), start=weight_path)
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return resources
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