From 7a1d1027ea317fe6ea6d3292090c15c638d5b009 Mon Sep 17 00:00:00 2001 From: VSlobolinskyi Date: Thu, 20 Mar 2025 01:25:30 +0200 Subject: [PATCH] Linter and ui splitting --- .gitignore | 200 +++- configure_gpu_deps.py | 21 +- generate-structure.js | 36 + infer-web.py | 780 +-------------- infer/modules/onnx/export.py | 1 + infer/modules/uvr5/vr.py | 16 +- infer/modules/vc/modules.py | 1 + infer/modules/vc/pipeline.py | 4 +- modules/rvc_ui/__init__.py | 0 modules/rvc_ui/initialization.py | 111 +++ modules/rvc_ui/main.py | 333 +++++++ modules/rvc_ui/utils.py | 61 ++ modules/rvc_ui/utils.pyi | 66 ++ poetry.lock | 1386 ++++++++++++++++----------- pyproject.toml | 20 +- struct.txt | 403 ++++++++ temp_tools/analize_deps.py | 25 +- temp_tools/clean_i18n.py | 16 +- temp_tools/join.py | 87 ++ temp_tools/remap_i18n.py | 16 +- temp_tools/remove_unused_imports.py | 7 +- tools/app.py | 7 +- tools/download_assets.py | 130 ++- tools/download_model.py | 4 + tools/infer/trans_weights.py | 1 - tools/torchgate/__init__.py | 1 - 26 files changed, 2314 insertions(+), 1419 deletions(-) create mode 100644 generate-structure.js create mode 100644 modules/rvc_ui/__init__.py create mode 100644 modules/rvc_ui/initialization.py create mode 100644 modules/rvc_ui/main.py create mode 100644 modules/rvc_ui/utils.py create mode 100644 modules/rvc_ui/utils.pyi create mode 100644 struct.txt create mode 100644 temp_tools/join.py diff --git a/.gitignore b/.gitignore index 683bdfc..70de05b 100644 --- a/.gitignore +++ b/.gitignore @@ -1,28 +1,194 @@ -.DS_Store -__pycache__ -/TEMP -*.pyd -.venv -/opt -tools/aria2c/ -tools/flag.txt +# ========= Common (applies to the entire repository) ========= +# Byte-compiled / optimized / DLL files +__pycache__/ +*.py[cod] +*$py.class -# Imported from huggingface.co/lj1995/VoiceConversionWebUI +# Virtual environments +.env +.venv +env/ +venv/ +ENV/ +env.bak/ +venv.bak/ + +# Distribution / packaging +.Python +build/ +develop-eggs/ +dist/ +downloads/ +eggs/ +.eggs/ +lib/ +lib64/ +parts/ +sdist/ +var/ +wheels/ +share/python-wheels/ +*.egg-info/ +.installed.cfg +*.egg +MANIFEST + +# Installer logs +pip-log.txt +pip-delete-this-directory.txt + +# Unit test / coverage reports +htmlcov/ +.tox/ +.nox/ +.coverage +.coverage.* +.cache +nosetests.xml +coverage.xml +*.cover +*.py,cover +.hypothesis/ +.pytest_cache/ +cover/ + +# Translations +*.mo +*.pot + +# IDE and editor settings +# PyCharm +.idea/ +# VSCode +.vscode/ + +# Jupyter Notebook +.ipynb_checkpoints + +# Others +*.log +*.spec +*.manifest + +# ========= Exclusions specific to the RVC Inference Module ========= +# Directories generated by RVC or for runtime usage: +/TEMP +/opt +/tools/aria2c/ +tools/flag.txt /pretrained /pretrained_v2 /uvr5_weights hubert_base.pt -rmvpe.onnx rmvpe.pt - -# Generated by RVC +rmvpe.onnx /logs /weights - -# To set a Python version for the project .tool-versions - /runtime -/assets/weights/* ffmpeg.* -ffprobe.* \ No newline at end of file +ffprobe.* + +# ========= Exclusions for the Spark Repository ========= +# (Since Spark files will be moved under ./spark, prefix these rules with "spark/") +# Byte-compiled / optimized / DLL files in spark +spark/__pycache__/ +spark/*.py[cod] +spark/*$py.class + +# Directories and files generated in Spark +spark/pretrained_models/ +spark/results/ +spark/demo/ +spark/.gradio/ + +# Distribution/packaging for Spark +spark/.Python +spark/build/ +spark/develop-eggs/ +spark/dist/ +spark/downloads/ +spark/eggs/ +spark/.eggs/ +spark/lib/ +spark/lib64/ +spark/parts/ +spark/sdist/ +spark/var/ +spark/wheels/ +spark/share/python-wheels/ +spark/*.egg-info/ +spark/.installed.cfg +spark/*.egg +spark/MANIFEST +spark/webui_test.py + +# PyInstaller (for Spark) +spark/*.manifest +spark/*.spec + +# Installer logs for Spark +spark/pip-log.txt +spark/pip-delete-this-directory.txt + +# Unit test / coverage reports for Spark +spark/htmlcov/ +spark/.tox/ +spark/.nox/ +spark/.coverage +spark/.coverage.* +spark/.cache +spark/nosetests.xml +spark/coverage.xml +spark/*.cover +spark/*.py,cover +spark/.hypothesis/ +spark/.pytest_cache/ +spark/cover/ + +# Translations (Spark) +spark/*.mo +spark/*.pot + +# Django/Flask/other web framework logs for Spark (if any) +spark/*.log +spark/local_settings.py +spark/db.sqlite3 +spark/db.sqlite3-journal + +# Flask and Scrapy caches for Spark +spark/instance/ +spark/.webassets-cache +spark/.scrapy + +# Sphinx documentation build for Spark +spark/docs/_build/ + +# PyBuilder / PEP582 for Spark +spark/.pybuilder/ +spark/target/ +spark/__pypackages__/ + +# Celery / SageMath for Spark +spark/celerybeat-schedule +spark/celerybeat.pid +spark/*.sage.py + +# IDE settings for Spark (if desired) +spark/.idea/ + +# MkDocs for Spark +spark/site/ + +# Type checker caches for Spark +spark/.mypy_cache/ +spark.dmypy.json +spark/dmypy.json +spark/.pyre/ +spark/.pytype/ + +# Cython debug symbols for Spark +spark/cython_debug/ + +# PyPI configuration for Spark +spark/.pypirc diff --git a/configure_gpu_deps.py b/configure_gpu_deps.py index ec326be..495e7db 100644 --- a/configure_gpu_deps.py +++ b/configure_gpu_deps.py @@ -2,6 +2,7 @@ import sys import re + def process_lines(lines, target_gpu): """ Process lines from the pyproject.toml file. @@ -10,12 +11,12 @@ def process_lines(lines, target_gpu): """ output_lines = [] current_block = None # None, "nvidia", or "amd" - + # Regex patterns for block markers and separator lines. - nvidia_marker = re.compile(r'---\s*NVIDIA GPU configuration\s*---', re.IGNORECASE) - amd_marker = re.compile(r'---\s*AMD GPU configuration\s*---', re.IGNORECASE) - separator = re.compile(r'^#\s*-{5,}') # a commented separator line - + nvidia_marker = re.compile(r"---\s*NVIDIA GPU configuration\s*---", re.IGNORECASE) + amd_marker = re.compile(r"---\s*AMD GPU configuration\s*---", re.IGNORECASE) + separator = re.compile(r"^#\s*-{5,}") # a commented separator line + for line in lines: # Check if this line marks the beginning of a GPU config block. if nvidia_marker.search(line): @@ -26,13 +27,13 @@ def process_lines(lines, target_gpu): current_block = "amd" output_lines.append(line) continue - + # If we hit a separator line, then end the current block. if separator.match(line): current_block = None output_lines.append(line) continue - + # Process lines within a GPU configuration block. if current_block is not None: # Remove newline to check content. @@ -48,7 +49,7 @@ def process_lines(lines, target_gpu): output_lines.append(line) else: # Remove the first occurrence of '#' with following space. - uncommented = re.sub(r'^(\s*)#\s?', r'\1', line) + uncommented = re.sub(r"^(\s*)#\s?", r"\1", line) output_lines.append(uncommented) else: # For the non-target block, ensure the line is commented. @@ -57,13 +58,14 @@ def process_lines(lines, target_gpu): output_lines.append(line) else: # Add a '#' preserving the original indentation. - leading_space = re.match(r'^(\s*)', line).group(1) + leading_space = re.match(r"^(\s*)", line).group(1) output_lines.append(f"{leading_space}# {line.lstrip()}") else: # Outside of any GPU config block, just add the line. output_lines.append(line) return output_lines + def main(): if len(sys.argv) != 2: print("Usage: python configure_gpu_deps.py ") @@ -88,5 +90,6 @@ def main(): print(f"Updated {toml_path} for {gpu_type.upper()} GPU configuration.") + if __name__ == "__main__": main() diff --git a/generate-structure.js b/generate-structure.js new file mode 100644 index 0000000..eeedd8f --- /dev/null +++ b/generate-structure.js @@ -0,0 +1,36 @@ +// generate-structure.js +const fs = require("fs"); +const path = require("path"); + +const targetDir = path.join(__dirname, "./"); +const outputFile = path.join(__dirname, "struct.txt"); + +function generateStructure(dir, indent = "") { + let structure = ""; + // Read directory items + const items = fs.readdirSync(dir); + items.forEach((item, index) => { + // Skip .git directories + if (item === ".git") return; + + const itemPath = path.join(dir, item); + const stats = fs.statSync(itemPath); + // Use pointer symbols to show tree structure + const pointer = index === items.length - 1 ? "└── " : "├── "; + structure += indent + pointer + item + "\n"; + if (stats.isDirectory()) { + // Increase indent: if last, add space, otherwise add vertical line + const extension = index === items.length - 1 ? " " : "│ "; + structure += generateStructure(itemPath, indent + extension); + } + }); + return structure; +} + +try { + const structureText = generateStructure(targetDir); + fs.writeFileSync(outputFile, structureText, "utf-8"); + console.log(`Folder structure saved to ${outputFile}`); +} catch (error) { + console.error("Error generating folder structure:", error); +} diff --git a/infer-web.py b/infer-web.py index 33902b5..348fbee 100644 --- a/infer-web.py +++ b/infer-web.py @@ -1,761 +1,29 @@ -import os -import sys -from dotenv import load_dotenv - -now_dir = os.getcwd() -sys.path.append(now_dir) -load_dotenv() -from infer.modules.vc.modules import VC -from configs.config import Config -import torch +#!/usr/bin/env python3 import gradio as gr -import fairseq -from time import sleep -from subprocess import Popen -import warnings -import traceback -import threading -import shutil -import logging +from rvc_ui.initialization import now_dir, config, vc +from rvc_ui.main import build_rvc_ui +# from spark_ui.main import build_spark_ui + +def build_unified_ui(): + # Build each sub-UI + rvc_ui = build_rvc_ui() # Returns a gr.Blocks instance for RVC WebUI + # spark_ui = build_spark_ui() # Returns a gr.Blocks instance for Spark TTS + + with gr.Blocks(title="Unified Inference UI") as app: + gr.Markdown("## Unified Inference UI: RVC WebUI and Spark TTS") + with gr.Tabs(): + with gr.TabItem("RVC WebUI"): + # Render the RVC UI components + rvc_ui.render() + # with gr.TabItem("Spark TTS"): + # # Render the Spark UI components + # spark_ui.render() + return app -logging.getLogger("numba").setLevel(logging.WARNING) -logging.getLogger("httpx").setLevel(logging.WARNING) - -logger = logging.getLogger(__name__) - -tmp = os.path.join(now_dir, "TEMP") -shutil.rmtree(tmp, ignore_errors=True) -shutil.rmtree("%s/runtime/Lib/site-packages/infer_pack" % (now_dir), ignore_errors=True) -shutil.rmtree("%s/runtime/Lib/site-packages/uvr5_pack" % (now_dir), ignore_errors=True) -os.makedirs(tmp, exist_ok=True) -os.makedirs(os.path.join(now_dir, "logs"), exist_ok=True) -os.makedirs(os.path.join(now_dir, "assets/weights"), exist_ok=True) -os.environ["TEMP"] = tmp -warnings.filterwarnings("ignore") -torch.manual_seed(114514) - - -config = Config() -vc = VC(config) - - -if config.dml == True: - - def forward_dml(ctx, x, scale): - ctx.scale = scale - res = x.clone().detach() - return res - - fairseq.modules.grad_multiply.GradMultiply.forward = forward_dml -ngpu = torch.cuda.device_count() -gpu_infos = [] -mem = [] -if_gpu_ok = False - -if torch.cuda.is_available() or ngpu != 0: - for i in range(ngpu): - gpu_name = torch.cuda.get_device_name(i) - if any( - value in gpu_name.upper() - for value in [ - "10", - "16", - "20", - "30", - "40", - "A2", - "A3", - "A4", - "P4", - "A50", - "500", - "A60", - "70", - "80", - "90", - "M4", - "T4", - "TITAN", - "4060", - "L", - "6000", - ] - ): - # A10#A100#V100#A40#P40#M40#K80#A4500 - if_gpu_ok = True # 至少有一张能用的N卡 - gpu_infos.append("%s\t%s" % (i, gpu_name)) - mem.append( - int( - torch.cuda.get_device_properties(i).total_memory - / 1024 - / 1024 - / 1024 - + 0.4 - ) - ) -if if_gpu_ok and len(gpu_infos) > 0: - gpu_info = "\n".join(gpu_infos) - default_batch_size = min(mem) // 2 -else: - gpu_info = "Unfortunately, there is no compatible GPU available to support your training." - default_batch_size = 1 -gpus = "-".join([i[0] for i in gpu_infos]) - - -class ToolButton(gr.Button, gr.components.FormComponent): - """Small button with single emoji as text, fits inside gradio forms""" - - def __init__(self, **kwargs): - super().__init__(variant="tool", **kwargs) - - def get_block_name(self): - return "button" - - -weight_root = os.getenv("weight_root") -weight_uvr5_root = os.getenv("weight_uvr5_root") -index_root = os.getenv("index_root") -outside_index_root = os.getenv("outside_index_root") - -names = [] -for name in os.listdir(weight_root): - if name.endswith(".pth"): - names.append(name) -index_paths = [] - -def update_audio_path(uploaded_file): - # If no file was uploaded, return an empty string. - if uploaded_file is None: - return "" - # If multiple files were allowed, take the first one. - if isinstance(uploaded_file, list): - uploaded_file = uploaded_file[0] - # Depending on Gradio version, the file may be a dict or an object with a 'name' attribute. - if isinstance(uploaded_file, dict): - return uploaded_file.get("name", "") - if hasattr(uploaded_file, "name"): - return uploaded_file.name - return str(uploaded_file) - - -def lookup_indices(index_root): - global index_paths - for root, dirs, files in os.walk(index_root, topdown=False): - for name in files: - if name.endswith(".index") and "trained" not in name: - index_paths.append("%s/%s" % (root, name)) - - -lookup_indices(index_root) -lookup_indices(outside_index_root) -uvr5_names = [] -for name in os.listdir(weight_uvr5_root): - if name.endswith(".pth") or "onnx" in name: - uvr5_names.append(name.replace(".pth", "")) - - -def change_choices(): - names = [] - for name in os.listdir(weight_root): - if name.endswith(".pth"): - names.append(name) - index_paths = [] - for root, dirs, files in os.walk(index_root, topdown=False): - for name in files: - if name.endswith(".index") and "trained" not in name: - index_paths.append("%s/%s" % (root, name)) - return {"choices": sorted(names), "__type__": "update"}, { - "choices": sorted(index_paths), - "__type__": "update", - } - -# Only works for NVIDIA GPUs -def clean(): - return {"value": "", "__type__": "update"} - - -def export_onnx(ModelPath, ExportedPath): - from infer.modules.onnx.export import export_onnx as eo - - eo(ModelPath, ExportedPath) - - -sr_dict = { - "32k": 32000, - "40k": 40000, - "48k": 48000, -} - - -def if_done(done, p): - while 1: - if p.poll() is None: - sleep(0.5) - else: - break - done[0] = True - - -def if_done_multi(done, ps): - while 1: - # poll==None代表进程未结束 - # 只要有一个进程未结束都不停 - flag = 1 - for p in ps: - if p.poll() is None: - flag = 0 - sleep(0.5) - break - if flag == 1: - break - done[0] = True - - -def preprocess_dataset(trainset_dir, exp_dir, sr, n_p): - sr = sr_dict[sr] - os.makedirs("%s/logs/%s" % (now_dir, exp_dir), exist_ok=True) - f = open("%s/logs/%s/preprocess.log" % (now_dir, exp_dir), "w") - f.close() - cmd = '"%s" infer/modules/train/preprocess.py "%s" %s %s "%s/logs/%s" %s %.1f' % ( - config.python_cmd, - trainset_dir, - sr, - n_p, - now_dir, - exp_dir, - config.noparallel, - config.preprocess_per, - ) - logger.info("Execute: " + cmd) - # , stdin=PIPE, stdout=PIPE,stderr=PIPE,cwd=now_dir - p = Popen(cmd, shell=True) - # 煞笔gr, popen read都非得全跑完了再一次性读取, 不用gr就正常读一句输出一句;只能额外弄出一个文本流定时读 - done = [False] - threading.Thread( - target=if_done, - args=( - done, - p, - ), - ).start() - while 1: - with open("%s/logs/%s/preprocess.log" % (now_dir, exp_dir), "r") as f: - yield (f.read()) - sleep(1) - if done[0]: - break - with open("%s/logs/%s/preprocess.log" % (now_dir, exp_dir), "r") as f: - log = f.read() - logger.info(log) - yield log - - -# but2.click(extract_f0,[gpus6,np7,f0method8,if_f0_3,trainset_dir4],[info2]) -def extract_f0_feature(gpus, n_p, f0method, if_f0, exp_dir, version19, gpus_rmvpe): - gpus = gpus.split("-") - os.makedirs("%s/logs/%s" % (now_dir, exp_dir), exist_ok=True) - f = open("%s/logs/%s/extract_f0_feature.log" % (now_dir, exp_dir), "w") - f.close() - if if_f0: - if f0method != "rmvpe_gpu": - cmd = ( - '"%s" infer/modules/train/extract/extract_f0_print.py "%s/logs/%s" %s %s' - % ( - config.python_cmd, - now_dir, - exp_dir, - n_p, - f0method, - ) - ) - logger.info("Execute: " + cmd) - p = Popen( - cmd, shell=True, cwd=now_dir - ) # , stdin=PIPE, stdout=PIPE,stderr=PIPE - # 煞笔gr, popen read都非得全跑完了再一次性读取, 不用gr就正常读一句输出一句;只能额外弄出一个文本流定时读 - done = [False] - threading.Thread( - target=if_done, - args=( - done, - p, - ), - ).start() - else: - if gpus_rmvpe != "-": - gpus_rmvpe = gpus_rmvpe.split("-") - leng = len(gpus_rmvpe) - ps = [] - for idx, n_g in enumerate(gpus_rmvpe): - cmd = ( - '"%s" infer/modules/train/extract/extract_f0_rmvpe.py %s %s %s "%s/logs/%s" %s ' - % ( - config.python_cmd, - leng, - idx, - n_g, - now_dir, - exp_dir, - config.is_half, - ) - ) - logger.info("Execute: " + cmd) - p = Popen( - cmd, shell=True, cwd=now_dir - ) # , shell=True, stdin=PIPE, stdout=PIPE, stderr=PIPE, cwd=now_dir - ps.append(p) - # 煞笔gr, popen read都非得全跑完了再一次性读取, 不用gr就正常读一句输出一句;只能额外弄出一个文本流定时读 - done = [False] - threading.Thread( - target=if_done_multi, # - args=( - done, - ps, - ), - ).start() - else: - cmd = ( - config.python_cmd - + ' infer/modules/train/extract/extract_f0_rmvpe_dml.py "%s/logs/%s" ' - % ( - now_dir, - exp_dir, - ) - ) - logger.info("Execute: " + cmd) - p = Popen( - cmd, shell=True, cwd=now_dir - ) # , shell=True, stdin=PIPE, stdout=PIPE, stderr=PIPE, cwd=now_dir - p.wait() - done = [True] - while 1: - with open( - "%s/logs/%s/extract_f0_feature.log" % (now_dir, exp_dir), "r" - ) as f: - yield (f.read()) - sleep(1) - if done[0]: - break - with open("%s/logs/%s/extract_f0_feature.log" % (now_dir, exp_dir), "r") as f: - log = f.read() - logger.info(log) - yield log - # 对不同part分别开多进程 - """ - n_part=int(sys.argv[1]) - i_part=int(sys.argv[2]) - i_gpu=sys.argv[3] - exp_dir=sys.argv[4] - os.environ["CUDA_VISIBLE_DEVICES"]=str(i_gpu) - """ - leng = len(gpus) - ps = [] - for idx, n_g in enumerate(gpus): - cmd = ( - '"%s" infer/modules/train/extract_feature_print.py %s %s %s %s "%s/logs/%s" %s %s' - % ( - config.python_cmd, - config.device, - leng, - idx, - n_g, - now_dir, - exp_dir, - version19, - config.is_half, - ) - ) - logger.info("Execute: " + cmd) - p = Popen( - cmd, shell=True, cwd=now_dir - ) # , shell=True, stdin=PIPE, stdout=PIPE, stderr=PIPE, cwd=now_dir - ps.append(p) - # 煞笔gr, popen read都非得全跑完了再一次性读取, 不用gr就正常读一句输出一句;只能额外弄出一个文本流定时读 - done = [False] - threading.Thread( - target=if_done_multi, - args=( - done, - ps, - ), - ).start() - while 1: - with open("%s/logs/%s/extract_f0_feature.log" % (now_dir, exp_dir), "r") as f: - yield (f.read()) - sleep(1) - if done[0]: - break - with open("%s/logs/%s/extract_f0_feature.log" % (now_dir, exp_dir), "r") as f: - log = f.read() - logger.info(log) - yield log - - -def get_pretrained_models(path_str, f0_str, sr2): - if_pretrained_generator_exist = os.access( - "assets/pretrained%s/%sG%s.pth" % (path_str, f0_str, sr2), os.F_OK - ) - if_pretrained_discriminator_exist = os.access( - "assets/pretrained%s/%sD%s.pth" % (path_str, f0_str, sr2), os.F_OK - ) - if not if_pretrained_generator_exist: - logger.warning( - "assets/pretrained%s/%sG%s.pth not exist, will not use pretrained model", - path_str, - f0_str, - sr2, - ) - if not if_pretrained_discriminator_exist: - logger.warning( - "assets/pretrained%s/%sD%s.pth not exist, will not use pretrained model", - path_str, - f0_str, - sr2, - ) - return ( - ( - "assets/pretrained%s/%sG%s.pth" % (path_str, f0_str, sr2) - if if_pretrained_generator_exist - else "" - ), - ( - "assets/pretrained%s/%sD%s.pth" % (path_str, f0_str, sr2) - if if_pretrained_discriminator_exist - else "" - ), - ) - - -def change_sr2(sr2, if_f0_3, version19): - path_str = "" if version19 == "v1" else "_v2" - f0_str = "f0" if if_f0_3 else "" - return get_pretrained_models(path_str, f0_str, sr2) - - -def change_version19(sr2, if_f0_3, version19): - path_str = "" if version19 == "v1" else "_v2" - if sr2 == "32k" and version19 == "v1": - sr2 = "40k" - to_return_sr2 = ( - {"choices": ["40k", "48k"], "__type__": "update", "value": sr2} - if version19 == "v1" - else {"choices": ["40k", "48k", "32k"], "__type__": "update", "value": sr2} - ) - f0_str = "f0" if if_f0_3 else "" - return ( - *get_pretrained_models(path_str, f0_str, sr2), - to_return_sr2, - ) - -# f0method8,pretrained_G14,pretrained_D15 -def change_f0(if_f0_3, sr2, version19): - path_str = "" if version19 == "v1" else "_v2" - return ( - {"visible": if_f0_3, "__type__": "update"}, - {"visible": if_f0_3, "__type__": "update"}, - *get_pretrained_models(path_str, "f0" if if_f0_3 == True else "", sr2), - ) - - -# ckpt_path2.change(change_info_,[ckpt_path2],[sr__,if_f0__]) -def change_info_(ckpt_path): - if not os.path.exists(ckpt_path.replace(os.path.basename(ckpt_path), "train.log")): - return {"__type__": "update"}, {"__type__": "update"}, {"__type__": "update"} - try: - with open( - ckpt_path.replace(os.path.basename(ckpt_path), "train.log"), "r" - ) as f: - info = eval(f.read().strip("\n").split("\n")[0].split("\t")[-1]) - sr, f0 = info["sample_rate"], info["if_f0"] - version = "v2" if ("version" in info and info["version"] == "v2") else "v1" - return sr, str(f0), version - except: - traceback.print_exc() - return {"__type__": "update"}, {"__type__": "update"}, {"__type__": "update"} - - -F0GPUVisible = config.dml == False - - -def change_f0_method(f0method8): - if f0method8 == "rmvpe_gpu": - visible = F0GPUVisible - else: - visible = False - return {"visible": visible, "__type__": "update"} - - -with gr.Blocks(title="RVC WebUI") as app: - gr.Markdown("## RVC WebUI") - gr.Markdown( - value="This software is open source under the MIT license. The author does not have any control over the software. Users who use the software and distribute the sounds exported by the software are solely responsible.
If you do not agree with this clause, you cannot use or reference any codes and files within the software package. See the root directory Agreement-LICENSE.txt for details." - ) - with gr.Tabs(): - with gr.TabItem("Model Inference"): - with gr.Row(): - sid0 = gr.Dropdown(label="Inferencing voice:", choices=sorted(names)) - with gr.Column(): - refresh_button = gr.Button( - "Refresh voice list and index path", variant="primary" - ) - clean_button = gr.Button("Unload voice to save GPU memory:", variant="primary") - spk_item = gr.Slider( - minimum=0, - maximum=2333, - step=1, - label="Select Speaker/Singer ID:", - value=0, - visible=False, - interactive=True, - ) - clean_button.click( - fn=clean, inputs=[], outputs=[sid0], api_name="infer_clean" - ) - with gr.TabItem("Single Inference"): - with gr.Group(): - with gr.Row(): - with gr.Column(): - vc_transform0 = gr.Number( - label="Transpose (integer, number of semitones, raise by an octave: 12, lower by an octave: -12):", - value=0, - ) - # Add a file uploader for drag & drop. - audio_upload = gr.File( - label="拖拽或选择音频文件", - file_types=[".wav"], - file_count="single", - interactive=True, - ) - # Existing textbox for the audio file path. - input_audio0 = gr.Textbox( - label="Enter the path of the audio file to be processed (default is the correct format example):", - placeholder="C:\\Users\\Desktop\\model_example.wav", - interactive=True, - ) - # When a file is uploaded, update the textbox. - audio_upload.change( - fn=update_audio_path, inputs=audio_upload, outputs=input_audio0 - ) - file_index1 = gr.Textbox( - label="Path to the feature index file. Leave blank to use the selected result from the dropdown:", - placeholder="C:\\Users\\Desktop\\model_example.index", - interactive=True, - ) - file_index2 = gr.Dropdown( - label="Auto-detect index path and select from the dropdown:", - choices=sorted(index_paths), - interactive=True, - ) - f0method0 = gr.Radio( - label="Select the pitch extraction algorithm ('pm': faster extraction but lower-quality speech; 'harvest': better bass but extremely slow; 'crepe': better quality but GPU intensive), 'rmvpe': best quality, and little GPU requirement", - choices=(["pm", "harvest", "crepe", "rmvpe"] if config.dml == False else ["pm", "harvest", "rmvpe"]), - value="rmvpe", - interactive=True, - ) - - with gr.Column(): - resample_sr0 = gr.Slider( - minimum=0, - maximum=48000, - label="Resample the output audio in post-processing to the final sample rate. Set to 0 for no resampling:", - value=0, - step=1, - interactive=True, - ) - rms_mix_rate0 = gr.Slider( - minimum=0, - maximum=1, - label="Adjust the volume envelope scaling. Closer to 0, the more it mimicks the volume of the original vocals. Can help mask noise and make volume sound more natural when set relatively low. Closer to 1 will be more of a consistently loud volume:", - value=0.25, - interactive=True, - ) - protect0 = gr.Slider( - minimum=0, - maximum=0.5, - label="Protect voiceless consonants and breath sounds to prevent artifacts such as tearing in electronic music. Set to 0.5 to disable. Decrease the value to increase protection, but it may reduce indexing accuracy:", - value=0.33, - step=0.01, - interactive=True, - ) - filter_radius0 = gr.Slider( - minimum=0, - maximum=7, - label="If >=3: apply median filtering to the harvested pitch results. The value represents the filter radius and can reduce breathiness.", - value=3, - step=1, - interactive=True, - ) - index_rate1 = gr.Slider( - minimum=0, - maximum=1, - label="Search feature ratio (controls accent strength, too high has artifacting):", - value=0.75, - interactive=True, - ) - f0_file = gr.File( - label="F0 curve file (optional). One pitch per line. Replaces the default F0 and pitch modulation:", - visible=False, - ) - - refresh_button.click( - fn=change_choices, - inputs=[], - outputs=[sid0, file_index2], - api_name="infer_refresh", - ) - with gr.Group(): - with gr.Column(): - but0 = gr.Button("Convert", variant="primary") - with gr.Row(): - vc_output1 = gr.Textbox(label="Output information") - vc_output2 = gr.Audio(label="Export audio (click on the three dots in the lower right corner to download)") - but0.click( - vc.vc_single, - [ - spk_item, - input_audio0, - vc_transform0, - f0_file, - f0method0, - file_index1, - file_index2, - index_rate1, - filter_radius0, - resample_sr0, - rms_mix_rate0, - protect0, - ], - [vc_output1, vc_output2], - api_name="infer_convert", - ) - with gr.TabItem("Batch Inference"): - gr.Markdown( - value="Batch conversion. Enter the folder containing the audio files to be converted or upload multiple audio files. The converted audio will be output in the specified folder (default: 'opt')." - ) - with gr.Row(): - with gr.Column(): - vc_transform1 = gr.Number( - label="Transpose (integer, number of semitones, raise by an octave: 12, lower by an octave: -12):", - value=0, - ) - opt_input = gr.Textbox( - label="Specify output folder:", value="opt" - ) - file_index3 = gr.Textbox( - label="Path to the feature index file. Leave blank to use the selected result from the dropdown:", - value="", - interactive=True, - ) - file_index4 = gr.Dropdown( - label="Auto-detect index path and select from the dropdown:", - choices=sorted(index_paths), - interactive=True, - ) - f0method1 = gr.Radio( - label="Select the pitch extraction algorithm ('pm': faster extraction but lower-quality speech; 'harvest': better bass but extremely slow; 'crepe': better quality but GPU intensive), 'rmvpe': best quality, and little GPU requirement", - choices=( - ["pm", "harvest", "crepe", "rmvpe"] - if config.dml == False - else ["pm", "harvest", "rmvpe"] - ), - value="rmvpe", - interactive=True, - ) - format1 = gr.Radio( - label="Export file format", - choices=["wav", "flac", "mp3", "m4a"], - value="wav", - interactive=True, - ) - - refresh_button.click( - fn=lambda: change_choices()[1], - inputs=[], - outputs=file_index4, - api_name="infer_refresh_batch", - ) - - with gr.Column(): - resample_sr1 = gr.Slider( - minimum=0, - maximum=48000, - label="Resample the output audio in post-processing to the final sample rate. Set to 0 for no resampling:", - value=0, - step=1, - interactive=True, - ) - rms_mix_rate1 = gr.Slider( - minimum=0, - maximum=1, - label="Adjust the volume envelope scaling. Closer to 0, the more it mimicks the volume of the original vocals. Can help mask noise and make volume sound more natural when set relatively low. Closer to 1 will be more of a consistently loud volume:", - value=1, - interactive=True, - ) - protect1 = gr.Slider( - minimum=0, - maximum=0.5, - label="Protect voiceless consonants and breath sounds to prevent artifacts such as tearing in electronic music. Set to 0.5 to disable. Decrease the value to increase protection, but it may reduce indexing accuracy:", - value=0.33, - step=0.01, - interactive=True, - ) - filter_radius1 = gr.Slider( - minimum=0, - maximum=7, - label="If >=3: apply median filtering to the harvested pitch results. The value represents the filter radius and can reduce breathiness.", - value=3, - step=1, - interactive=True, - ) - index_rate2 = gr.Slider( - minimum=0, - maximum=1, - label="Search feature ratio (controls accent strength, too high has artifacting):", - value=1, - interactive=True, - ) - with gr.Row(): - dir_input = gr.Textbox( - label="Enter the path of the audio folder to be processed (copy it from the address bar of the file manager):", - placeholder="C:\\Users\\Desktop\\input_vocal_dir", - ) - inputs = gr.File( - file_count="multiple", - label="Multiple audio files can also be imported. If a folder path exists, this input is ignored.", - ) - - with gr.Row(): - but1 = gr.Button("Convert", variant="primary") - vc_output3 = gr.Textbox(label="Output information") - - but1.click( - vc.vc_multi, - [ - spk_item, - dir_input, - opt_input, - inputs, - vc_transform1, - f0method1, - file_index3, - file_index4, - index_rate2, - filter_radius1, - resample_sr1, - rms_mix_rate1, - protect1, - format1, - ], - [vc_output3], - api_name="infer_convert_batch", - ) - sid0.change( - fn=vc.get_vc, - inputs=[sid0, protect0, protect1], - outputs=[spk_item, protect0, protect1, file_index2, file_index4], - api_name="infer_change_voice", - ) +if __name__ == "__main__": + app = build_unified_ui() + # Needed for RVC if config.iscolab: app.queue(concurrency_count=511, max_size=1022).launch(share=True) else: @@ -765,3 +33,5 @@ with gr.Blocks(title="RVC WebUI") as app: server_port=config.listen_port, quiet=True, ) + + diff --git a/infer/modules/onnx/export.py b/infer/modules/onnx/export.py index c7ca780..64692b0 100644 --- a/infer/modules/onnx/export.py +++ b/infer/modules/onnx/export.py @@ -3,6 +3,7 @@ import onnxsim import onnx from infer.lib.infer_pack.models_onnx import SynthesizerTrnMsNSFsidM + def export_onnx(ModelPath, ExportedPath): cpt = torch.load(ModelPath, map_location="cpu") cpt["config"][-3] = cpt["weight"]["emb_g.weight"].shape[0] diff --git a/infer/modules/uvr5/vr.py b/infer/modules/uvr5/vr.py index b75cd95..9bc86a1 100644 --- a/infer/modules/uvr5/vr.py +++ b/infer/modules/uvr5/vr.py @@ -146,7 +146,9 @@ class AudioPre: ) if os.path.exists(path): opt_format_path = path[:-4] + ".%s" % format - os.system('ffmpeg -i "%s" -vn "%s" -q:a 2 -y' % (path, opt_format_path)) + os.system( + 'ffmpeg -i "%s" -vn "%s" -q:a 2 -y' % (path, opt_format_path) + ) if os.path.exists(opt_format_path): try: os.remove(path) @@ -187,7 +189,9 @@ class AudioPre: ) if os.path.exists(path): opt_format_path = path[:-4] + ".%s" % format - os.system('ffmpeg -i "%s" -vn "%s" -q:a 2 -y' % (path, opt_format_path)) + os.system( + 'ffmpeg -i "%s" -vn "%s" -q:a 2 -y' % (path, opt_format_path) + ) if os.path.exists(opt_format_path): try: os.remove(path) @@ -323,7 +327,9 @@ class AudioPreDeEcho: ) if os.path.exists(path): opt_format_path = path[:-4] + ".%s" % format - os.system('ffmpeg -i "%s" -vn "%s" -q:a 2 -y' % (path, opt_format_path)) + os.system( + 'ffmpeg -i "%s" -vn "%s" -q:a 2 -y' % (path, opt_format_path) + ) if os.path.exists(opt_format_path): try: os.remove(path) @@ -360,7 +366,9 @@ class AudioPreDeEcho: ) if os.path.exists(path): opt_format_path = path[:-4] + ".%s" % format - os.system('ffmpeg -i "%s" -vn "%s" -q:a 2 -y' % (path, opt_format_path)) + os.system( + 'ffmpeg -i "%s" -vn "%s" -q:a 2 -y' % (path, opt_format_path) + ) if os.path.exists(opt_format_path): try: os.remove(path) diff --git a/infer/modules/vc/modules.py b/infer/modules/vc/modules.py index ff10427..b2f13c3 100644 --- a/infer/modules/vc/modules.py +++ b/infer/modules/vc/modules.py @@ -18,6 +18,7 @@ from infer.lib.infer_pack.models import ( from infer.modules.vc.pipeline import Pipeline from infer.modules.vc.utils import * + class VC: def __init__(self, config): self.n_spk = None diff --git a/infer/modules/vc/pipeline.py b/infer/modules/vc/pipeline.py index 96f1cbb..a06c23c 100644 --- a/infer/modules/vc/pipeline.py +++ b/infer/modules/vc/pipeline.py @@ -40,7 +40,9 @@ def cache_harvest_f0(input_audio_path, fs, f0max, f0min, frame_period): return f0 -def change_rms(data1, sr1, data2, sr2, rate): # 1Yes输入音频，2Yes输出音频,rateYes2的占比 +def change_rms( + data1, sr1, data2, sr2, rate +): # 1Yes输入音频，2Yes输出音频,rateYes2的占比 # print(data1.max(),data2.max()) rms1 = librosa.feature.rms( y=data1, frame_length=sr1 // 2 * 2, hop_length=sr1 // 2 diff --git a/modules/rvc_ui/__init__.py b/modules/rvc_ui/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/modules/rvc_ui/initialization.py b/modules/rvc_ui/initialization.py new file mode 100644 index 0000000..0b7f78f --- /dev/null +++ b/modules/rvc_ui/initialization.py @@ -0,0 +1,111 @@ +# rvc_ui/initialization.py +import os +import sys +from dotenv import load_dotenv +import torch +import fairseq +import warnings +import shutil +import logging + +# Set current directory and load environment variables +now_dir = os.getcwd() +sys.path.append(now_dir) +load_dotenv() + +# Configure logging and warnings +logging.getLogger("numba").setLevel(logging.WARNING) +logging.getLogger("httpx").setLevel(logging.WARNING) +logger = logging.getLogger(__name__) + +# Cleanup and create necessary directories +tmp = os.path.join(now_dir, "TEMP") +shutil.rmtree(tmp, ignore_errors=True) +shutil.rmtree(f"{now_dir}/runtime/Lib/site-packages/infer_pack", ignore_errors=True) +shutil.rmtree(f"{now_dir}/runtime/Lib/site-packages/uvr5_pack", ignore_errors=True) +os.makedirs(tmp, exist_ok=True) +os.makedirs(os.path.join(now_dir, "logs"), exist_ok=True) +os.makedirs(os.path.join(now_dir, "assets/weights"), exist_ok=True) +os.environ["TEMP"] = tmp +warnings.filterwarnings("ignore") +torch.manual_seed(114514) + +# Import your configuration and voice conversion modules +from configs.config import Config +from infer.modules.vc.modules import VC + +# Instantiate configuration and VC +config = Config() +vc = VC(config) + +# Optionally override fairseq grad multiply if dml is enabled +if config.dml: + + def forward_dml(ctx, x, scale): + ctx.scale = scale + return x.clone().detach() + + fairseq.modules.grad_multiply.GradMultiply.forward = forward_dml + +# GPU detection and info collection +ngpu = torch.cuda.device_count() +gpu_infos = [] +mem = [] +if_gpu_ok = False + +if torch.cuda.is_available() or ngpu != 0: + for i in range(ngpu): + gpu_name = torch.cuda.get_device_name(i) + if any( + value in gpu_name.upper() + for value in [ + "10", + "16", + "20", + "30", + "40", + "A2", + "A3", + "A4", + "P4", + "A50", + "500", + "A60", + "70", + "80", + "90", + "M4", + "T4", + "TITAN", + "4060", + "L", + "6000", + ] + ): + if_gpu_ok = True + gpu_infos.append(f"{i}\t{gpu_name}") + mem.append( + int(torch.cuda.get_device_properties(i).total_memory / (1024**3) + 0.4) + ) + +if if_gpu_ok and gpu_infos: + gpu_info = "\n".join(gpu_infos) + default_batch_size = min(mem) // 2 +else: + gpu_info = ( + "Unfortunately, there is no compatible GPU available to support your training." + ) + default_batch_size = 1 + +gpus = "-".join([i[0] for i in gpu_infos]) + +# Expose useful variables for other modules +__all__ = [ + "now_dir", + "config", + "vc", + "gpu_info", + "default_batch_size", + "gpus", + "logger", +] diff --git a/modules/rvc_ui/main.py b/modules/rvc_ui/main.py new file mode 100644 index 0000000..80c4f68 --- /dev/null +++ b/modules/rvc_ui/main.py @@ -0,0 +1,333 @@ +# rvc_ui/main.py +import os +import gradio as gr +import shutil +from time import sleep + +# Import modules from your package +from rvc_ui.initialization import now_dir, config, vc +from rvc_ui.utils import ( + update_audio_path, + lookup_indices, + change_choices, + clean, + ToolButton, +) + +# Setup weight and index paths from environment variables +weight_root = os.getenv("weight_root") +weight_uvr5_root = os.getenv("weight_uvr5_root") +index_root = os.getenv("index_root") +outside_index_root = os.getenv("outside_index_root") + +# Prepare model names and index paths +names = [name for name in os.listdir(weight_root) if name.endswith(".pth")] +index_paths = [] +lookup_indices(index_root, index_paths) +lookup_indices(outside_index_root, index_paths) +uvr5_names = [ + name.replace(".pth", "") + for name in os.listdir(weight_uvr5_root) + if name.endswith(".pth") or "onnx" in name +] + +# Define additional dictionaries and UI functions if needed +sr_dict = {"32k": 32000, "40k": 40000, "48k": 48000} +F0GPUVisible = config.dml == False + + +# Build Gradio UI +def build_rvc_ui(): + with gr.Blocks(title="RVC WebUI") as rvc_ui: + gr.Markdown("## RVC WebUI") + gr.Markdown( + value="This software is open source under the MIT license. The author does not have any control over the software. Users who use the software and distribute the sounds exported by the software are solely responsible.
If you do not agree with this clause, you cannot use or reference any codes and files within the software package. See the root directory Agreement-LICENSE.txt for details." + ) + with gr.Tabs(): + with gr.TabItem("Model Inference"): + with gr.Row(): + sid0 = gr.Dropdown( + label="Inferencing voice:", choices=sorted(names) + ) + with gr.Column(): + refresh_button = gr.Button( + "Refresh voice list and index path", variant="primary" + ) + clean_button = gr.Button( + "Unload voice to save GPU memory:", variant="primary" + ) + spk_item = gr.Slider( + minimum=0, + maximum=2333, + step=1, + label="Select Speaker/Singer ID:", + value=0, + visible=False, + interactive=True, + ) + clean_button.click( + fn=clean, inputs=[], outputs=[sid0], api_name="infer_clean" + ) + with gr.TabItem("Single Inference"): + with gr.Group(): + with gr.Row(): + with gr.Column(): + vc_transform0 = gr.Number( + label="Transpose (integer, number of semitones, raise by an octave: 12, lower by an octave: -12):", + value=0, + ) + # Add a file uploader for drag & drop. + audio_upload = gr.File( + label="拖拽或选择音频文件", + file_types=[".wav"], + file_count="single", + interactive=True, + ) + # Existing textbox for the audio file path. + input_audio0 = gr.Textbox( + label="Enter the path of the audio file to be processed (default is the correct format example):", + placeholder="C:\\Users\\Desktop\\model_example.wav", + interactive=True, + ) + # When a file is uploaded, update the textbox. + audio_upload.change( + fn=update_audio_path, + inputs=audio_upload, + outputs=input_audio0, + ) + file_index1 = gr.Textbox( + label="Path to the feature index file. Leave blank to use the selected result from the dropdown:", + placeholder="C:\\Users\\Desktop\\model_example.index", + interactive=True, + ) + file_index2 = gr.Dropdown( + label="Auto-detect index path and select from the dropdown:", + choices=sorted(index_paths), + interactive=True, + ) + f0method0 = gr.Radio( + label="Select the pitch extraction algorithm ('pm': faster extraction but lower-quality speech; 'harvest': better bass but extremely slow; 'crepe': better quality but GPU intensive), 'rmvpe': best quality, and little GPU requirement", + choices=( + ["pm", "harvest", "crepe", "rmvpe"] + if config.dml == False + else ["pm", "harvest", "rmvpe"] + ), + value="rmvpe", + interactive=True, + ) + + with gr.Column(): + resample_sr0 = gr.Slider( + minimum=0, + maximum=48000, + label="Resample the output audio in post-processing to the final sample rate. Set to 0 for no resampling:", + value=0, + step=1, + interactive=True, + ) + rms_mix_rate0 = gr.Slider( + minimum=0, + maximum=1, + label="Adjust the volume envelope scaling. Closer to 0, the more it mimicks the volume of the original vocals. Can help mask noise and make volume sound more natural when set relatively low. Closer to 1 will be more of a consistently loud volume:", + value=0.25, + interactive=True, + ) + protect0 = gr.Slider( + minimum=0, + maximum=0.5, + label="Protect voiceless consonants and breath sounds to prevent artifacts such as tearing in electronic music. Set to 0.5 to disable. Decrease the value to increase protection, but it may reduce indexing accuracy:", + value=0.33, + step=0.01, + interactive=True, + ) + filter_radius0 = gr.Slider( + minimum=0, + maximum=7, + label="If >=3: apply median filtering to the harvested pitch results. The value represents the filter radius and can reduce breathiness.", + value=3, + step=1, + interactive=True, + ) + index_rate1 = gr.Slider( + minimum=0, + maximum=1, + label="Search feature ratio (controls accent strength, too high has artifacting):", + value=0.75, + interactive=True, + ) + f0_file = gr.File( + label="F0 curve file (optional). One pitch per line. Replaces the default F0 and pitch modulation:", + visible=False, + ) + + refresh_button.click( + fn=change_choices, + inputs=[], + outputs=[sid0, file_index2], + api_name="infer_refresh", + ) + with gr.Group(): + with gr.Column(): + but0 = gr.Button("Convert", variant="primary") + with gr.Row(): + vc_output1 = gr.Textbox(label="Output information") + vc_output2 = gr.Audio( + label="Export audio (click on the three dots in the lower right corner to download)" + ) + but0.click( + vc.vc_single, + [ + spk_item, + input_audio0, + vc_transform0, + f0_file, + f0method0, + file_index1, + file_index2, + index_rate1, + filter_radius0, + resample_sr0, + rms_mix_rate0, + protect0, + ], + [vc_output1, vc_output2], + api_name="infer_convert", + ) + with gr.TabItem("Batch Inference"): + gr.Markdown( + value="Batch conversion. Enter the folder containing the audio files to be converted or upload multiple audio files. The converted audio will be output in the specified folder (default: 'opt')." + ) + with gr.Row(): + with gr.Column(): + vc_transform1 = gr.Number( + label="Transpose (integer, number of semitones, raise by an octave: 12, lower by an octave: -12):", + value=0, + ) + opt_input = gr.Textbox( + label="Specify output folder:", value="opt" + ) + file_index3 = gr.Textbox( + label="Path to the feature index file. Leave blank to use the selected result from the dropdown:", + value="", + interactive=True, + ) + file_index4 = gr.Dropdown( + label="Auto-detect index path and select from the dropdown:", + choices=sorted(index_paths), + interactive=True, + ) + f0method1 = gr.Radio( + label="Select the pitch extraction algorithm ('pm': faster extraction but lower-quality speech; 'harvest': better bass but extremely slow; 'crepe': better quality but GPU intensive), 'rmvpe': best quality, and little GPU requirement", + choices=( + ["pm", "harvest", "crepe", "rmvpe"] + if config.dml == False + else ["pm", "harvest", "rmvpe"] + ), + value="rmvpe", + interactive=True, + ) + format1 = gr.Radio( + label="Export file format", + choices=["wav", "flac", "mp3", "m4a"], + value="wav", + interactive=True, + ) + + refresh_button.click( + fn=lambda: change_choices()[1], + inputs=[], + outputs=file_index4, + api_name="infer_refresh_batch", + ) + + with gr.Column(): + resample_sr1 = gr.Slider( + minimum=0, + maximum=48000, + label="Resample the output audio in post-processing to the final sample rate. Set to 0 for no resampling:", + value=0, + step=1, + interactive=True, + ) + rms_mix_rate1 = gr.Slider( + minimum=0, + maximum=1, + label="Adjust the volume envelope scaling. Closer to 0, the more it mimicks the volume of the original vocals. Can help mask noise and make volume sound more natural when set relatively low. Closer to 1 will be more of a consistently loud volume:", + value=1, + interactive=True, + ) + protect1 = gr.Slider( + minimum=0, + maximum=0.5, + label="Protect voiceless consonants and breath sounds to prevent artifacts such as tearing in electronic music. Set to 0.5 to disable. Decrease the value to increase protection, but it may reduce indexing accuracy:", + value=0.33, + step=0.01, + interactive=True, + ) + filter_radius1 = gr.Slider( + minimum=0, + maximum=7, + label="If >=3: apply median filtering to the harvested pitch results. The value represents the filter radius and can reduce breathiness.", + value=3, + step=1, + interactive=True, + ) + index_rate2 = gr.Slider( + minimum=0, + maximum=1, + label="Search feature ratio (controls accent strength, too high has artifacting):", + value=1, + interactive=True, + ) + with gr.Row(): + dir_input = gr.Textbox( + label="Enter the path of the audio folder to be processed (copy it from the address bar of the file manager):", + placeholder="C:\\Users\\Desktop\\input_vocal_dir", + ) + inputs = gr.File( + file_count="multiple", + label="Multiple audio files can also be imported. If a folder path exists, this input is ignored.", + ) + + with gr.Row(): + but1 = gr.Button("Convert", variant="primary") + vc_output3 = gr.Textbox(label="Output information") + + but1.click( + vc.vc_multi, + [ + spk_item, + dir_input, + opt_input, + inputs, + vc_transform1, + f0method1, + file_index3, + file_index4, + index_rate2, + filter_radius1, + resample_sr1, + rms_mix_rate1, + protect1, + format1, + ], + [vc_output3], + api_name="infer_convert_batch", + ) + sid0.change( + fn=vc.get_vc, + inputs=[sid0, protect0, protect1], + outputs=[ + spk_item, + protect0, + protect1, + file_index2, + file_index4, + ], + api_name="infer_change_voice", + ) + return rvc_ui + + +if __name__ == "__main__": + build_rvc_ui() diff --git a/modules/rvc_ui/utils.py b/modules/rvc_ui/utils.py new file mode 100644 index 0000000..b086a08 --- /dev/null +++ b/modules/rvc_ui/utils.py @@ -0,0 +1,61 @@ +# rvc_ui/utils.py +import os +import gradio as gr + + +# Function to update the audio path when a file is uploaded +def update_audio_path(uploaded_file): + if uploaded_file is None: + return "" + if isinstance(uploaded_file, list): + uploaded_file = uploaded_file[0] + if isinstance(uploaded_file, dict): + return uploaded_file.get("name", "") + if hasattr(uploaded_file, "name"): + return uploaded_file.name + return str(uploaded_file) + + +# Function to lookup index files in a given directory +def lookup_indices(index_root, index_paths): + for root, dirs, files in os.walk(index_root, topdown=False): + for name in files: + if name.endswith(".index") and "trained" not in name: + index_paths.append(f"{root}/{name}") + + +# Function to refresh available model and index choices +def change_choices(weight_root, index_root): + names = [name for name in os.listdir(weight_root) if name.endswith(".pth")] + index_paths = [] + for root, dirs, files in os.walk(index_root, topdown=False): + for name in files: + if name.endswith(".index") and "trained" not in name: + index_paths.append(f"{root}/{name}") + return {"choices": sorted(names), "__type__": "update"}, { + "choices": sorted(index_paths), + "__type__": "update", + } + + +# Custom Gradio ToolButton component +class ToolButton(gr.Button, gr.components.FormComponent): + def __init__(self, **kwargs): + super().__init__(variant="tool", **kwargs) + + def get_block_name(self): + return "button" + + +# Simple clean function to reset a field (used for GPU memory management) +def clean(): + return {"value": "", "__type__": "update"} + + +__all__ = [ + "update_audio_path", + "lookup_indices", + "change_choices", + "ToolButton", + "clean", +] diff --git a/modules/rvc_ui/utils.pyi b/modules/rvc_ui/utils.pyi new file mode 100644 index 0000000..7cb1f79 --- /dev/null +++ b/modules/rvc_ui/utils.pyi @@ -0,0 +1,66 @@ +# rvc_ui/utils.py +import os +import gradio as gr + + +# Function to update the audio path when a file is uploaded +def update_audio_path(uploaded_file): + if uploaded_file is None: + return "" + if isinstance(uploaded_file, list): + uploaded_file = uploaded_file[0] + if isinstance(uploaded_file, dict): + return uploaded_file.get("name", "") + if hasattr(uploaded_file, "name"): + return uploaded_file.name + return str(uploaded_file) + + +# Function to lookup index files in a given directory +def lookup_indices(index_root, index_paths): + for root, dirs, files in os.walk(index_root, topdown=False): + for name in files: + if name.endswith(".index") and "trained" not in name: + index_paths.append(f"{root}/{name}") + + +# Function to refresh available model and index choices +def change_choices(weight_root, index_root): + names = [name for name in os.listdir(weight_root) if name.endswith(".pth")] + index_paths = [] + for root, dirs, files in os.walk(index_root, topdown=False): + for name in files: + if name.endswith(".index") and "trained" not in name: + index_paths.append(f"{root}/{name}") + return {"choices": sorted(names), "__type__": "update"}, { + "choices": sorted(index_paths), + "__type__": "update", + } + +from gradio.events import Dependency + +# Custom Gradio ToolButton component +class ToolButton(gr.Button, gr.components.FormComponent): + def __init__(self, **kwargs): + super().__init__(variant="tool", **kwargs) + + def get_block_name(self): + return "button" + from typing import Callable, Literal, Sequence, Any, TYPE_CHECKING + from gradio.blocks import Block + if TYPE_CHECKING: + from gradio.components import Timer + + +# Simple clean function to reset a field (used for GPU memory management) +def clean(): + return {"value": "", "__type__": "update"} + + +__all__ = [ + "update_audio_path", + "lookup_indices", + "change_choices", + "ToolButton", + "clean", +] \ No newline at end of file diff --git a/poetry.lock b/poetry.lock index cd9127e..b347f52 100644 --- a/poetry.lock +++ b/poetry.lock @@ -14,112 +14,117 @@ files = [ [[package]] name = "aiofiles" -version = "24.1.0" +version = "23.2.1" description = "File support for asyncio." optional = false -python-versions = ">=3.8" 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28b1271..54cfd9d 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,9 +1,17 @@ [tool.poetry] name = "spark-rvc-inference-module" version = "0.1.0" -description = "Spark TTS with RVC inference module" +description = "Spark TTS with RVC inference module. A unification of the RVC inference module and Spark TTS projects." authors = ["vitalii.slobolinskyi"] -package-mode = false +license = "MIT" +readme = "README.md" +homepage = "https://github.com/VSlobolinskyi/spark-rvc-inference-module" +repository = "https://github.com/VSlobolinskyi/spark-rvc-inference-module" + +[[tool.poetry.packages]] +include = "rvc_ui" +from = "modules" + [tool.poetry.dependencies] python = ">=3.11,<3.12" @@ -60,7 +68,13 @@ torch-directml = "^0.2.5.dev240914" autoflake = "^2.3.1" [tool.poetry.group.dev.dependencies] -# Add any development dependencies here +black = "^25.1.0" +pytest = "^7.0" + +[tool.black] +line-length = 88 +target-version = ['py38'] +include = '\.pyi?$' [build-system] requires = ["poetry-core>=1.0.0"] diff --git a/struct.txt b/struct.txt new file mode 100644 index 0000000..8ccf40f --- /dev/null +++ b/struct.txt @@ -0,0 +1,403 @@ +├── .env +├── .gitignore +├── .vscode +│ └── settings.json +├── assets +│ ├── hubert +│ │ ├── .gitignore +│ │ ├── hubert_base.pt +│ │ └── hubert_inputs.pth +│ ├── indices +│ │ └── .gitignore +│ ├── pretrained +│ │ ├── .gitignore +│ │ ├── D32k.pth +│ │ ├── D40k.pth +│ │ ├── D48k.pth +│ │ ├── f0D32k.pth +│ │ ├── f0D40k.pth +│ │ ├── f0D48k.pth +│ │ ├── f0G32k.pth +│ │ ├── f0G40k.pth +│ │ ├── f0G48k.pth +│ │ ├── G32k.pth +│ │ ├── G40k.pth +│ │ └── G48k.pth +│ ├── pretrained_v2 +│ │ ├── .gitignore +│ │ ├── D32k.pth +│ │ ├── D40k.pth +│ │ ├── D48k.pth +│ │ ├── f0D32k.pth +│ │ ├── f0D40k.pth +│ │ ├── f0D48k.pth +│ │ ├── f0G32k.pth +│ │ ├── f0G40k.pth +│ │ ├── f0G48k.pth +│ │ ├── G32k.pth +│ │ ├── G40k.pth +│ │ └── G48k.pth +│ ├── rmvpe +│ │ ├── .gitignore +│ │ ├── rmvpe.onnx +│ │ ├── rmvpe.pt +│ │ └── rmvpe_inputs.pth +│ ├── Synthesizer_inputs.pth +│ ├── uvr5_weights +│ │ ├── .gitignore +│ │ ├── HP2-%E4%BA%BA%E5%A3%B0vocals%2B%E9%9D%9E%E4%BA%BA%E5%A3%B0instrumentals.pth +│ │ ├── HP2_all_vocals.pth +│ │ ├── HP3_all_vocals.pth +│ │ ├── HP5-%E4%B8%BB%E6%97%8B%E5%BE%8B%E4%BA%BA%E5%A3%B0vocals%2B%E5%85%B6%E4%BB%96instrumentals.pth +│ │ ├── HP5_only_main_vocal.pth +│ │ ├── onnx_dereverb_By_FoxJoy +│ │ │ └── vocals.onnx +│ │ ├── VR-DeEchoAggressive.pth +│ │ ├── VR-DeEchoDeReverb.pth +│ │ └── VR-DeEchoNormal.pth +│ └── weights +│ ├── .gitignore +│ └── SilverWolf_e300_s6600.pth +├── configs +│ ├── config.json +│ ├── config.py +│ ├── inuse +│ │ ├── .gitignore +│ │ ├── v1 +│ │ │ ├── .gitignore +│ │ │ ├── 32k.json +│ │ │ ├── 40k.json +│ │ │ └── 48k.json +│ │ └── v2 +│ │ ├── .gitignore +│ │ ├── 32k.json +│ │ └── 48k.json +│ ├── v1 +│ │ ├── 32k.json +│ │ ├── 40k.json +│ │ └── 48k.json +│ ├── v2 +│ │ ├── 32k.json +│ │ └── 48k.json +│ └── __pycache__ +│ └── config.cpython-311.pyc +├── configure_gpu_deps.py +├── ffmpeg.exe +├── ffprobe.exe +├── generate-structure.js +├── infer +│ ├── lib +│ │ ├── audio.py +│ │ ├── infer_pack +│ │ │ ├── attentions.py +│ │ │ ├── attentions_onnx.py +│ │ │ ├── commons.py +│ │ │ ├── models.py +│ │ │ ├── models_onnx.py +│ │ │ ├── modules +│ │ │ │ └── F0Predictor +│ │ │ │ ├── DioF0Predictor.py +│ │ │ │ ├── F0Predictor.py +│ │ │ │ ├── HarvestF0Predictor.py +│ │ │ │ ├── PMF0Predictor.py +│ │ │ │ └── __init__.py +│ │ │ ├── modules.py +│ │ │ ├── onnx_inference.py +│ │ │ ├── transforms.py +│ │ │ └── __pycache__ +│ │ │ ├── attentions.cpython-311.pyc +│ │ │ ├── commons.cpython-311.pyc +│ │ │ ├── models.cpython-311.pyc +│ │ │ ├── modules.cpython-311.pyc +│ │ │ └── transforms.cpython-311.pyc +│ │ ├── jit +│ │ │ ├── get_hubert.py +│ │ │ ├── get_rmvpe.py +│ │ │ ├── get_synthesizer.py +│ │ │ ├── __init__.py +│ │ │ └── __pycache__ +│ │ │ └── __init__.cpython-311.pyc +│ │ ├── rmvpe.py +│ │ ├── rtrvc.py +│ │ ├── slicer2.py +│ │ ├── uvr5_pack +│ │ │ ├── lib_v5 +│ │ │ │ ├── dataset.py +│ │ │ │ ├── layers.py +│ │ │ │ ├── layers_123812KB .py +│ │ │ │ ├── layers_123821KB.py +│ │ │ │ ├── layers_33966KB.py +│ │ │ │ ├── layers_537227KB.py +│ │ │ │ ├── layers_537238KB.py +│ │ │ │ ├── layers_new.py +│ │ │ │ ├── modelparams +│ │ │ │ │ ├── 1band_sr16000_hl512.json +│ │ │ │ │ ├── 1band_sr32000_hl512.json +│ │ │ │ │ ├── 1band_sr33075_hl384.json +│ │ │ │ │ ├── 1band_sr44100_hl1024.json +│ │ │ │ │ ├── 1band_sr44100_hl256.json +│ │ │ │ │ ├── 1band_sr44100_hl512.json +│ │ │ │ │ ├── 1band_sr44100_hl512_cut.json +│ │ │ │ │ ├── 2band_32000.json +│ │ │ │ │ ├── 2band_44100_lofi.json +│ │ │ │ │ ├── 2band_48000.json +│ │ │ │ │ ├── 3band_44100.json +│ │ │ │ │ ├── 3band_44100_mid.json +│ │ │ │ │ ├── 3band_44100_msb2.json +│ │ │ │ │ ├── 4band_44100.json +│ │ │ │ │ ├── 4band_44100_mid.json +│ │ │ │ │ ├── 4band_44100_msb.json +│ │ │ │ │ ├── 4band_44100_msb2.json +│ │ │ │ │ ├── 4band_44100_reverse.json +│ │ │ │ │ ├── 4band_44100_sw.json +│ │ │ │ │ ├── 4band_v2.json +│ │ │ │ │ ├── 4band_v2_sn.json +│ │ │ │ │ ├── 4band_v3.json +│ │ │ │ │ └── ensemble.json +│ │ │ │ ├── model_param_init.py +│ │ │ │ ├── nets.py +│ │ │ │ ├── nets_123812KB.py +│ │ │ │ ├── nets_123821KB.py +│ │ │ │ ├── nets_33966KB.py +│ │ │ │ ├── nets_537227KB.py +│ │ │ │ ├── nets_537238KB.py +│ │ │ │ ├── nets_61968KB.py +│ │ │ │ ├── nets_new.py +│ │ │ │ └── spec_utils.py +│ │ │ ├── name_params.json +│ │ │ └── utils.py +│ │ └── __pycache__ +│ │ ├── audio.cpython-311.pyc +│ │ └── rmvpe.cpython-311.pyc +│ └── modules +│ ├── ipex +│ │ ├── attention.py +│ │ ├── gradscaler.py +│ │ ├── hijacks.py +│ │ └── __init__.py +│ ├── onnx +│ │ └── export.py +│ ├── train +│ │ ├── extract +│ │ │ ├── extract_f0_print.py +│ │ │ ├── extract_f0_rmvpe.py +│ │ │ └── extract_f0_rmvpe_dml.py +│ │ ├── extract_feature_print.py +│ │ ├── preprocess.py +│ │ └── train.py +│ ├── uvr5 +│ │ ├── mdxnet.py +│ │ └── vr.py +│ └── vc +│ ├── modules.py +│ ├── pipeline.py +│ ├── utils.py +│ ├── __init__.py +│ └── __pycache__ +│ ├── modules.cpython-311.pyc +│ ├── pipeline.cpython-311.pyc +│ ├── utils.cpython-311.pyc +│ └── __init__.cpython-311.pyc +├── infer-web.py +├── LICENSE +├── logs +│ ├── added_IVF611_Flat_nprobe_1_SilverWolf_v2.index +│ └── mute +│ ├── 0_gt_wavs +│ │ ├── mute32k.wav +│ │ ├── mute40k.wav +│ │ └── mute48k.wav +│ ├── 1_16k_wavs +│ │ └── mute.wav +│ ├── 2a_f0 +│ │ └── mute.wav.npy +│ ├── 2b-f0nsf +│ │ └── mute.wav.npy +│ ├── 3_feature256 +│ │ └── mute.npy +│ └── 3_feature768 +│ └── mute.npy +├── modules +│ ├── rvc_ui +│ │ ├── initialization.py +│ │ ├── main.py +│ │ ├── utils.py +│ │ └── __init__.py +│ └── spark_ui +│ ├── main.py +│ └── __init__.py +├── poetry.lock +├── pyproject.toml +├── README.md +├── spark +│ ├── cli +│ │ ├── inference.py +│ │ ├── spark.sparktts.py +│ │ └── __pycache__ +│ │ ├── spark.sparktts.cpython-311.pyc +│ │ └── spark.sparktts.cpython-312.pyc +│ ├── LICENSE +│ ├── pretrained_models +│ │ └── Spark-TTS-0.5B +│ │ ├── .gitattributes +│ │ ├── BiCodec +│ │ │ ├── config.yaml +│ │ │ └── model.safetensors +│ │ ├── config.yaml +│ │ ├── LLM +│ │ │ ├── added_tokens.json +│ │ │ ├── config.json +│ │ │ ├── merges.txt +│ │ │ ├── model.safetensors +│ │ │ ├── special_tokens_map.json +│ │ │ ├── tokenizer.json +│ │ │ ├── tokenizer_config.json +│ │ │ └── vocab.json +│ │ ├── README.md +│ │ ├── src +│ │ │ ├── figures +│ │ │ │ ├── gradio_control.png +│ │ │ │ ├── gradio_TTS.png +│ │ │ │ ├── infer_control.png +│ │ │ │ └── infer_voice_cloning.png +│ │ │ └── logo +│ │ │ ├── HKUST.jpg +│ │ │ ├── mobvoi.jpg +│ │ │ ├── mobvoi.png +│ │ │ ├── NPU.jpg +│ │ │ ├── NTU.jpg +│ │ │ ├── SJU.jpg +│ │ │ ├── SparkAudio.jpg +│ │ │ ├── SparkAudio2.jpg +│ │ │ ├── spark.sparktts.jpg +│ │ │ └── spark.sparktts.png +│ │ └── wav2vec2-large-xlsr-53 +│ │ ├── config.json +│ │ ├── preprocessor_config.json +│ │ ├── pytorch_model.bin +│ │ └── README.md +│ ├── runtime +│ │ └── triton_trtllm +│ │ ├── client_grpc.py +│ │ ├── client_http.py +│ │ ├── model_repo +│ │ │ ├── audio_tokenizer +│ │ │ │ ├── 1 +│ │ │ │ │ └── model.py +│ │ │ │ └── config.pbtxt +│ │ │ ├── spark_tts +│ │ │ │ ├── 1 +│ │ │ │ │ └── model.py +│ │ │ │ └── config.pbtxt +│ │ │ ├── tensorrt_llm +│ │ │ │ ├── 1 +│ │ │ │ │ └── .gitkeep +│ │ │ │ └── config.pbtxt +│ │ │ └── vocoder +│ │ │ ├── 1 +│ │ │ │ └── model.py +│ │ │ └── config.pbtxt +│ │ ├── README.md +│ │ └── scripts +│ │ ├── convert_checkpoint.py +│ │ └── fill_template.py +│ └── sparktts +│ ├── models +│ │ ├── audio_tokenizer.py +│ │ ├── bicodec.py +│ │ └── __pycache__ +│ │ ├── audio_tokenizer.cpython-311.pyc +│ │ ├── audio_tokenizer.cpython-312.pyc +│ │ ├── bicodec.cpython-311.pyc +│ │ └── bicodec.cpython-312.pyc +│ ├── modules +│ │ ├── blocks +│ │ │ ├── layers.py +│ │ │ ├── samper.py +│ │ │ ├── vocos.py +│ │ │ └── __pycache__ +│ │ │ ├── layers.cpython-311.pyc +│ │ │ ├── layers.cpython-312.pyc +│ │ │ ├── samper.cpython-311.pyc +│ │ │ ├── samper.cpython-312.pyc +│ │ │ ├── vocos.cpython-311.pyc +│ │ │ └── vocos.cpython-312.pyc +│ │ ├── encoder_decoder +│ │ │ ├── feat_decoder.py +│ │ │ ├── feat_encoder.py +│ │ │ ├── wave_generator.py +│ │ │ └── __pycache__ +│ │ │ ├── feat_decoder.cpython-311.pyc +│ │ │ ├── feat_decoder.cpython-312.pyc +│ │ │ ├── feat_encoder.cpython-311.pyc +│ │ │ ├── feat_encoder.cpython-312.pyc +│ │ │ ├── wave_generator.cpython-311.pyc +│ │ │ └── wave_generator.cpython-312.pyc +│ │ ├── fsq +│ │ │ ├── finite_scalar_quantization.py +│ │ │ ├── residual_fsq.py +│ │ │ └── __pycache__ +│ │ │ ├── finite_scalar_quantization.cpython-311.pyc +│ │ │ ├── finite_scalar_quantization.cpython-312.pyc +│ │ │ ├── residual_fsq.cpython-311.pyc +│ │ │ └── residual_fsq.cpython-312.pyc +│ │ ├── speaker +│ │ │ ├── ecapa_tdnn.py +│ │ │ ├── perceiver_encoder.py +│ │ │ ├── pooling_layers.py +│ │ │ ├── speaker_encoder.py +│ │ │ └── __pycache__ +│ │ │ ├── ecapa_tdnn.cpython-311.pyc +│ │ │ ├── ecapa_tdnn.cpython-312.pyc +│ │ │ ├── perceiver_encoder.cpython-311.pyc +│ │ │ ├── perceiver_encoder.cpython-312.pyc +│ │ │ ├── pooling_layers.cpython-311.pyc +│ │ │ ├── pooling_layers.cpython-312.pyc +│ │ │ ├── speaker_encoder.cpython-311.pyc +│ │ │ └── speaker_encoder.cpython-312.pyc +│ │ └── vq +│ │ ├── factorized_vector_quantize.py +│ │ └── __pycache__ +│ │ ├── factorized_vector_quantize.cpython-311.pyc +│ │ └── factorized_vector_quantize.cpython-312.pyc +│ └── utils +│ ├── audio.py +│ ├── file.py +│ ├── token_parser.py +│ ├── __init__.py +│ └── __pycache__ +│ ├── audio.cpython-311.pyc +│ ├── audio.cpython-312.pyc +│ ├── file.cpython-311.pyc +│ ├── file.cpython-312.pyc +│ ├── token_parser.cpython-311.pyc +│ ├── token_parser.cpython-312.pyc +│ ├── __init__.cpython-311.pyc +│ └── __init__.cpython-312.pyc +├── struct.txt +├── TEMP +├── temp_tools +│ ├── analize_deps.py +│ ├── clean_i18n.py +│ ├── join.py +│ ├── remap_i18n.py +│ ├── remove_unused_imports.py +│ └── used_dependencies.txt +└── tools + ├── app.py + ├── calc_rvc_model_similarity.py + ├── download_assets.py + ├── download_model.py + ├── export_onnx.py + ├── infer + │ ├── infer-pm-index256.py + │ ├── train-index-v2.py + │ ├── train-index.py + │ └── trans_weights.py + ├── infer_batch_rvc.py + ├── infer_cli.py + ├── onnx_inference_demo.py + └── torchgate + ├── torchgate.py + ├── utils.py + └── __init__.py diff --git a/temp_tools/analize_deps.py b/temp_tools/analize_deps.py index 84209d0..5768af0 100644 --- a/temp_tools/analize_deps.py +++ b/temp_tools/analize_deps.py @@ -2,6 +2,7 @@ import os import ast from collections import defaultdict + class CodeAnalyzer(ast.NodeVisitor): def __init__(self): # Stores plain "import module" names. @@ -45,12 +46,13 @@ class CodeAnalyzer(ast.NodeVisitor): return node.attr return None + def process_file(file_path): """ Parse the Python file at file_path and return an analysis of its imports and function calls. """ try: - with open(file_path, 'r', encoding='utf-8') as f: + with open(file_path, "r", encoding="utf-8") as f: file_content = f.read() tree = ast.parse(file_content, filename=file_path) except Exception as e: @@ -60,11 +62,14 @@ def process_file(file_path): analyzer = CodeAnalyzer() analyzer.visit(tree) return { - 'imports': sorted(analyzer.imports), - 'from_imports': {module: sorted(names) for module, names in analyzer.from_imports.items()}, - 'function_calls': sorted(analyzer.function_calls) + "imports": sorted(analyzer.imports), + "from_imports": { + module: sorted(names) for module, names in analyzer.from_imports.items() + }, + "function_calls": sorted(analyzer.function_calls), } + def process_directory(root_dir): """ Walk recursively through root_dir, process each .py file, and collect analysis data. @@ -79,26 +84,28 @@ def process_directory(root_dir): summary[file_path] = analysis return summary + def write_summary(summary, output_file): """ Write the collected analysis to a text file in a human-readable format. """ - with open(output_file, 'w', encoding='utf-8') as f: + with open(output_file, "w", encoding="utf-8") as f: for file, data in summary.items(): f.write(f"File: {file}\n") f.write(" Imports:\n") - for imp in data['imports']: + for imp in data["imports"]: f.write(f" - {imp}\n") f.write(" From Imports:\n") - for module, names in data['from_imports'].items(): + for module, names in data["from_imports"].items(): f.write(f" - {module}: {', '.join(names)}\n") f.write(" Function Calls:\n") - for call in data['function_calls']: + for call in data["function_calls"]: f.write(f" - {call}\n") f.write("\n") print(f"Analysis written to {output_file}") -if __name__ == '__main__': + +if __name__ == "__main__": project_root = os.getcwd() # Assumes the script is placed at your project root. analysis_summary = process_directory(project_root) output_summary_file = "temp_tools/used_dependencies.txt" diff --git a/temp_tools/clean_i18n.py b/temp_tools/clean_i18n.py index 5b1b96b..2366cd9 100644 --- a/temp_tools/clean_i18n.py +++ b/temp_tools/clean_i18n.py @@ -1,13 +1,14 @@ import os import re + def process_file(file_path): """ Reads a file, replaces occurrences of "Any text" (even if multiline) with just the "Any text" part, and writes the file back if changes are made. """ try: - with open(file_path, 'r', encoding='utf-8') as f: + with open(file_path, "r", encoding="utf-8") as f: content = f.read() except UnicodeDecodeError: print(f"Skipping binary or non-text file: {file_path}") @@ -17,18 +18,20 @@ def process_file(file_path): # It supports both single and double quoted strings, and uses DOTALL # so that the string literal may span multiple lines. pattern = re.compile( - r'i18n\s*\(\s*(?P["\'])(?P.*?)(?P=quote)\s*\)', - re.DOTALL + r'i18n\s*\(\s*(?P["\'])(?P.*?)(?P=quote)\s*\)', re.DOTALL ) # Replacement function returns only the string literal (including quotes). - new_content = pattern.sub(lambda m: m.group("quote") + m.group("text") + m.group("quote"), content) + new_content = pattern.sub( + lambda m: m.group("quote") + m.group("text") + m.group("quote"), content + ) if new_content != content: - with open(file_path, 'w', encoding='utf-8') as f: + with open(file_path, "w", encoding="utf-8") as f: f.write(new_content) print(f"Updated: {file_path}") + def process_directory(root_dir): """ Recursively traverse all files in root_dir and process them. @@ -38,7 +41,8 @@ def process_directory(root_dir): file_path = os.path.join(dirpath, filename) process_file(file_path) -if __name__ == '__main__': + +if __name__ == "__main__": # Start processing from the current working directory. project_root = os.getcwd() process_directory(project_root) diff --git a/temp_tools/join.py b/temp_tools/join.py new file mode 100644 index 0000000..38a683c --- /dev/null +++ b/temp_tools/join.py @@ -0,0 +1,87 @@ +#!/usr/bin/env python3 +import subprocess +import os +import shutil + + +def clone_spark_repo(repo_url, clone_dir): + """Clone the spark repo into a temporary directory.""" + print(f"Cloning {repo_url} into {clone_dir} ...") + subprocess.run(["git", "clone", repo_url, clone_dir], check=True) + print("Clone completed.") + + +def remove_git_directory(clone_dir): + """Remove the .git directory from the cloned repo, adjusting permissions if necessary.""" + git_dir = os.path.join(clone_dir, ".git") + if os.path.exists(git_dir): + + def handle_remove_error(func, path, exc_info): + # Change the file to writable and try again. + os.chmod(path, stat.S_IWRITE) + func(path) + + shutil.rmtree(git_dir, onerror=handle_remove_error) + print(f"Removed .git directory from {clone_dir}") + + +def ensure_folder(folder_path): + """Ensure that a folder exists.""" + if not os.path.exists(folder_path): + os.makedirs(folder_path) + print(f"Created folder: {folder_path}") + + +def merge_spark_repo(clone_dir, spark_folder, temp_folder, duplicate_files): + """Merge files from the cloned spark repo. + + - Files whose names are in duplicate_files and already exist in the root are moved to temp_folder. + - All other items are moved to the spark_folder. + """ + for item in os.listdir(clone_dir): + source_path = os.path.join(clone_dir, item) + # Determine the destination: + root_dest = os.path.join(os.getcwd(), item) + if item in duplicate_files and os.path.exists(root_dest): + # Move duplicate file to TEMP folder + dest_path = os.path.join(temp_folder, item) + print(f"Duplicate '{item}' exists in root; moving it to {temp_folder}.") + else: + # Otherwise, place in the spark folder + dest_path = os.path.join(spark_folder, item) + print(f"Moving '{item}' to {spark_folder}.") + shutil.move(source_path, dest_path) + + +def main(): + # Settings + repo_url = "https://github.com/VSlobolinskyi/spark-tts-poetry.git" + clone_dir = "spark_repo_temp" # temporary folder for the cloned spark repo + spark_folder = "spark" # destination folder for spark-specific instruments + temp_folder = "TEMP" # destination folder for duplicate files + # List of duplicate filenames that, if found in the root, will be moved to TEMP + duplicate_files = {"pyproject.toml", ".gitignore", "LICENSE", "README.md"} + + # Clone the Spark repo + clone_spark_repo(repo_url, clone_dir) + + # Remove the .git directory from the cloned repo + remove_git_directory(clone_dir) + + # Ensure destination folders exist + ensure_folder(spark_folder) + ensure_folder(temp_folder) + + # Merge files from the cloned spark repo into the correct locations + merge_spark_repo(clone_dir, spark_folder, temp_folder, duplicate_files) + + # Remove the temporary clone directory if it still exists (it should be empty now) + if os.path.exists(clone_dir): + shutil.rmtree(clone_dir) + print(f"Removed temporary directory: {clone_dir}") + + print("Spark repo merged successfully into the RVC project.") + + +if __name__ == "__main__": + main() diff --git a/temp_tools/remap_i18n.py b/temp_tools/remap_i18n.py index 5dafb94..8e4dbbd 100644 --- a/temp_tools/remap_i18n.py +++ b/temp_tools/remap_i18n.py @@ -1,23 +1,25 @@ import os import json + def load_mapping(mapping_path): """ Load the mapping JSON file containing key-value pairs. """ - with open(mapping_path, 'r', encoding='utf-8') as f: + with open(mapping_path, "r", encoding="utf-8") as f: mapping = json.load(f) # Sort mapping items by length of the original text (key) in descending order sorted_mapping = sorted(mapping.items(), key=lambda kv: len(kv[0]), reverse=True) return sorted_mapping + def process_file(file_path, sorted_mapping): """ Read a file, replace occurrences of each key with its value, and write the file back if changes were made. """ try: - with open(file_path, 'r', encoding='utf-8') as f: + with open(file_path, "r", encoding="utf-8") as f: content = f.read() except UnicodeDecodeError: # Skip binary files or files that can't be decoded as UTF-8 @@ -31,10 +33,11 @@ def process_file(file_path, sorted_mapping): new_content = new_content.replace(original_text, translated_text) if new_content != content: - with open(file_path, 'w', encoding='utf-8') as f: + with open(file_path, "w", encoding="utf-8") as f: f.write(new_content) print(f"Updated: {file_path}") + def process_directory(root_dir, sorted_mapping, mapping_file_path): """ Walk through all directories starting at root_dir and process each file. @@ -47,11 +50,12 @@ def process_directory(root_dir, sorted_mapping, mapping_file_path): continue process_file(file_path, sorted_mapping) -if __name__ == '__main__': + +if __name__ == "__main__": # Assume the script is run from the project root. project_root = os.getcwd() - mapping_file_path = os.path.join(project_root, 'i18n', 'locale', 'en_US.json') - + mapping_file_path = os.path.join(project_root, "i18n", "locale", "en_US.json") + if not os.path.exists(mapping_file_path): print(f"Mapping file not found: {mapping_file_path}") else: diff --git a/temp_tools/remove_unused_imports.py b/temp_tools/remove_unused_imports.py index 38ae06d..c4fe673 100644 --- a/temp_tools/remove_unused_imports.py +++ b/temp_tools/remove_unused_imports.py @@ -1,6 +1,7 @@ import os import subprocess + def process_file(file_path): """ Run autoflake on the file to remove unused imports in-place. @@ -10,12 +11,13 @@ def process_file(file_path): # --remove-all-unused-imports removes unused imports. subprocess.run( ["autoflake", "--in-place", "--remove-all-unused-imports", file_path], - check=True + check=True, ) print(f"Processed: {file_path}") except subprocess.CalledProcessError as e: print(f"Error processing {file_path}: {e}") + def process_directory(root_dir): """ Walk recursively through root_dir and process all .py files. @@ -26,7 +28,8 @@ def process_directory(root_dir): file_path = os.path.join(dirpath, filename) process_file(file_path) -if __name__ == '__main__': + +if __name__ == "__main__": # Start from the current directory (you can change this to your project root) project_root = os.getcwd() process_directory(project_root) diff --git a/tools/app.py b/tools/app.py index 49cbd1f..7bf2e04 100644 --- a/tools/app.py +++ b/tools/app.py @@ -59,7 +59,8 @@ with app: ) vc_input3 = gr.Audio(label="上传音频（长度小于90秒）") vc_transform0 = gr.Number( - label="Transpose (integer, number of semitones, raise by an octave: 12, lower by an octave: -12):", value=0 + label="Transpose (integer, number of semitones, raise by an octave: 12, lower by an octave: -12):", + value=0, ) f0method0 = gr.Radio( label="选择音高Extract算法,输入歌声可用pm提速,harvest低音好但巨慢无比,crepe效果好但吃GPU", @@ -122,7 +123,9 @@ with app: ) but0 = gr.Button("Convert", variant="primary") vc_output1 = gr.Textbox(label="Output information") - vc_output2 = gr.Audio(label="Export audio (click on the three dots in the lower right corner to download)") + vc_output2 = gr.Audio( + label="Export audio (click on the three dots in the lower right corner to download)" + ) but0.click( vc.vc_single, [ diff --git a/tools/download_assets.py b/tools/download_assets.py index b7ca3a8..1bbfbaa 100644 --- a/tools/download_assets.py +++ b/tools/download_assets.py @@ -1,11 +1,52 @@ +#!/usr/bin/env python3 import os -from pathlib import Path +import subprocess +import sys +import shutil +import stat import requests +from pathlib import Path -RVC_DOWNLOAD_LINK = "https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/" +########################### +# Part 1: Clone Spark TTS # +########################### -BASE_DIR = Path(__file__).resolve().parent.parent +def run_command(command, error_message): + try: + subprocess.run(command, check=True) + except subprocess.CalledProcessError: + print(error_message) + sys.exit(1) +def clone_spark_tts(): + # Create the directory spark/pretrained_models if it doesn't exist. + spark_pretrained_dir = os.path.join("spark", "pretrained_models") + os.makedirs(spark_pretrained_dir, exist_ok=True) + + print("Running 'git lfs install'...") + run_command( + ["git", "lfs", "install"], + "Error: Failed to run 'git lfs install'. Make sure git-lfs is installed (https://git-lfs.com).", + ) + + clone_dir = os.path.join(spark_pretrained_dir, "Spark-TTS-0.5B") + if not os.path.exists(clone_dir): + print(f"Cloning Spark TTS repository into {clone_dir}...") + run_command( + [ + "git", + "clone", + "https://huggingface.co/SparkAudio/Spark-TTS-0.5B", + clone_dir, + ], + "Error: Failed to clone the Spark TTS repository.", + ) + else: + print(f"Directory '{clone_dir}' already exists. Skipping clone.") + +############################# +# Part 2: Download RVC Assets # +############################# def dl_model(link, model_name, dir_name): with requests.get(f"{link}{model_name}") as r: @@ -15,59 +56,56 @@ def dl_model(link, model_name, dir_name): for chunk in r.iter_content(chunk_size=8192): f.write(chunk) +def download_rvc_models(): + RVC_DOWNLOAD_LINK = "https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/" + # Set BASE_DIR to the project root. If this script is in ./tools, we go one level up. + BASE_DIR = Path(__file__).resolve().parent.parent + + def check_and_dl(link, model_name, dest_dir): + dest_file = dest_dir / model_name + if dest_file.exists(): + print(f"{model_name} already exists at {dest_file}. Skipping download.") + else: + print(f"Downloading {model_name}...") + dl_model(link, model_name, dest_dir) -if __name__ == "__main__": print("Downloading hubert_base.pt...") - dl_model(RVC_DOWNLOAD_LINK, "hubert_base.pt", BASE_DIR / "assets/hubert") + check_and_dl(RVC_DOWNLOAD_LINK, "hubert_base.pt", BASE_DIR / "assets" / "hubert") + print("Downloading rmvpe.pt...") - dl_model(RVC_DOWNLOAD_LINK, "rmvpe.pt", BASE_DIR / "assets/rmvpe") + check_and_dl(RVC_DOWNLOAD_LINK, "rmvpe.pt", BASE_DIR / "assets" / "rmvpe") + print("Downloading rmvpe.onnx...") - dl_model(RVC_DOWNLOAD_LINK, "rmvpe.onnx", BASE_DIR / "assets/rmvpe") + check_and_dl(RVC_DOWNLOAD_LINK, "rmvpe.onnx", BASE_DIR / "assets" / "rmvpe") + print("Downloading vocals.onnx...") - dl_model( - RVC_DOWNLOAD_LINK + "uvr5_weights/onnx_dereverb_By_FoxJoy/", - "vocals.onnx", - BASE_DIR / "assets/uvr5_weights/onnx_dereverb_By_FoxJoy", - ) - dl_model(RVC_DOWNLOAD_LINK, "ffprobe.exe", BASE_DIR / "./") + vocals_dir = BASE_DIR / "assets" / "uvr5_weights" / "onnx_dereverb_By_FoxJoy" + check_and_dl(RVC_DOWNLOAD_LINK + "uvr5_weights/onnx_dereverb_By_FoxJoy/", "vocals.onnx", vocals_dir) + print("Downloading ffprobe.exe...") - dl_model(RVC_DOWNLOAD_LINK, "ffmpeg.exe", BASE_DIR / "./") + check_and_dl(RVC_DOWNLOAD_LINK, "ffprobe.exe", BASE_DIR / ".") + print("Downloading ffmpeg.exe...") + check_and_dl(RVC_DOWNLOAD_LINK, "ffmpeg.exe", BASE_DIR / ".") - rvc_models_dir = BASE_DIR / "assets/pretrained" - + rvc_models_dir = BASE_DIR / "assets" / "pretrained" print("Downloading pretrained models:") - model_names = [ - "D32k.pth", - "D40k.pth", - "D48k.pth", - "G32k.pth", - "G40k.pth", - "G48k.pth", - "f0D32k.pth", - "f0D40k.pth", - "f0D48k.pth", - "f0G32k.pth", - "f0G40k.pth", - "f0G48k.pth", + "D32k.pth", "D40k.pth", "D48k.pth", + "G32k.pth", "G40k.pth", "G48k.pth", + "f0D32k.pth", "f0D40k.pth", "f0D48k.pth", + "f0G32k.pth", "f0G40k.pth", "f0G48k.pth", ] for model in model_names: - print(f"Downloading {model}...") - dl_model(RVC_DOWNLOAD_LINK + "pretrained/", model, rvc_models_dir) - - rvc_models_dir = BASE_DIR / "assets/pretrained_v2" + check_and_dl(RVC_DOWNLOAD_LINK + "pretrained/", model, rvc_models_dir) + rvc_models_dir = BASE_DIR / "assets" / "pretrained_v2" print("Downloading pretrained models v2:") - for model in model_names: - print(f"Downloading {model}...") - dl_model(RVC_DOWNLOAD_LINK + "pretrained_v2/", model, rvc_models_dir) + check_and_dl(RVC_DOWNLOAD_LINK + "pretrained_v2/", model, rvc_models_dir) print("Downloading uvr5_weights:") - - rvc_models_dir = BASE_DIR / "assets/uvr5_weights" - + rvc_models_dir = BASE_DIR / "assets" / "uvr5_weights" model_names = [ "HP2-%E4%BA%BA%E5%A3%B0vocals%2B%E9%9D%9E%E4%BA%BA%E5%A3%B0instrumentals.pth", "HP2_all_vocals.pth", @@ -79,7 +117,17 @@ if __name__ == "__main__": "VR-DeEchoNormal.pth", ] for model in model_names: - print(f"Downloading {model}...") - dl_model(RVC_DOWNLOAD_LINK + "uvr5_weights/", model, rvc_models_dir) + check_and_dl(RVC_DOWNLOAD_LINK + "uvr5_weights/", model, rvc_models_dir) print("All models downloaded!") + +########################## +# Main: Run both parts # +########################## + +def main(): + clone_spark_tts() + download_rvc_models() + +if __name__ == "__main__": + main() diff --git a/tools/download_model.py b/tools/download_model.py index f563725..faf596f 100644 --- a/tools/download_model.py +++ b/tools/download_model.py @@ -5,6 +5,7 @@ from pathlib import Path import tempfile import shutil + def download_file(url: str, local_path: Path): """Download a file from a URL to a local path.""" if local_path.exists(): @@ -19,6 +20,7 @@ def download_file(url: str, local_path: Path): f.write(chunk) print(f"[DONE] Downloaded {local_path}") + def extract_and_move(zip_path: Path, logs_dir: Path, weights_dir: Path): """Extract a zip file and move .index files to logs and .pth files to assets/weights.""" logs_dir.mkdir(parents=True, exist_ok=True) @@ -41,6 +43,7 @@ def extract_and_move(zip_path: Path, logs_dir: Path, weights_dir: Path): shutil.move(str(extracted_file), str(dest)) print("[CLEANUP] Extraction complete.") + def main(): parser = argparse.ArgumentParser( description="Download a model zip file, extract it, and place .index files in ./logs and .pth files in ./assets/weights." @@ -68,5 +71,6 @@ def main(): zip_path.unlink() print("[COMPLETE] Model download and extraction complete.") + if __name__ == "__main__": main() diff --git a/tools/infer/trans_weights.py b/tools/infer/trans_weights.py index ae26f73..9a6a5bd 100644 --- a/tools/infer/trans_weights.py +++ b/tools/infer/trans_weights.py @@ -1,4 +1,3 @@ - import torch # a=torch.load(r"E:\codes\py39\vits_vc_gpu_train\logs\ft-mi-suc\G_1000.pth")["model"]#sim_nsf# diff --git a/tools/torchgate/__init__.py b/tools/torchgate/__init__.py index 66b81ec..6b0e2b7 100644 --- a/tools/torchgate/__init__.py +++ b/tools/torchgate/__init__.py @@ -9,4 +9,3 @@ torchgate imports all the functions from PyTorch, and in addition provides: TorchGating --- A PyTorch module that applies a spectral gate to an input signal """ -