fixed client

app.py

@@ -2,6 +2,18 @@ import gradio as gr
 import shutil
 import numpy as np
 from pathlib import Path
+import os
+from utils import get_hash
+import time
+import torch
+
+
+def get_device_info():
+    if torch.cuda.is_available():
+        device = f"GPU ({torch.cuda.get_device_name(0)})"
+    else:
+        device = "CPU"
+    return f"当前运行环境: {device}"
 
 
 def inference(audio_file):
@@ -10,6 +22,13 @@ def inference(audio_file):
     output_path1 = "downloaded_audio_1.wav"
     output_path2 = "downloaded_audio_2.wav"
 
+    hash_audio = str(get_hash(audio_file))
+    media_dir = os.path.dirname(audio_file)
+
+    outputs = []
+
+    start_time = time.time()
+
     shutil.copy(audio_file, output_path1)
     shutil.copy(audio_file, output_path2)
 
@@ -21,6 +40,7 @@ def get_gui(theme, title, description):
         # Add title and description
         gr.Markdown(title)
         gr.Markdown(description)
+        gr.Markdown(get_device_info())
         
         audio_input = gr.Audio(label="Audio file", type="filepath")  # type: str | Path | bytes | tuple[int, np.ndarray] | None
         download_button = gr.Button("Inference")
@@ -39,24 +59,32 @@ if __name__ == "__main__":
     title = "<center><strong><font size='7'>Vocal BGM Separator</font></strong></center>"
     description = "This demo uses the MDX-Net models to perform Ultimate Vocal Remover (uvr) task for vocal and background sound separation."
     theme = "NoCrypt/miku"
-    # app_gui = get_gui(theme, title, description)
+
+    BASE_DIR = "."  # os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
+    mdxnet_models_dir = os.path.join(BASE_DIR, "mdx_models")
+    output_dir = os.path.join(BASE_DIR, "output")
+
+    # confirm entry points from client
+    # client_local = Client("http://127.0.0.1:7860")
+    # client = Client(f"{HF_USERNAME}/{HF_SPACENAME}", hf_token=HF_TOKEN)
+    # client_local.view_api()
+
+    # entry point for GUI
+    # predict(audio_file, api_name="/inference") -> result
+    app_gui = get_gui(theme, title, description)
+
+    # entry point for API
+    # predict(audio_file, api_name="/predict") -> output
     app_api = gr.Interface(
         fn=inference,
         inputs=gr.Audio(type="filepath"),   # 接收文件路径（也可以换成 type="file"）
         outputs=gr.File(file_count="multiple"),  # 返回多个文件
     )
 
-    # app = gr.TabbedInterface(
-    #     interface_list=[app_api, app_gui],
-    #     tab_names=["GUI", "API"]
-    # )
-
-    app_api.queue(default_concurrency_limit=40)
+    app = gr.TabbedInterface(
+        interface_list=[app_gui, app_api],
+        tab_names=["GUI", "API"]
+    )
 
-    app_api.launch(
-        max_threads=40,
-        share=False,
-        show_error=True,
-        quiet=False,
-        debug=False,
-    )
+    app.queue(default_concurrency_limit=40)
+    app.launch()

requirements.txt

@@ -1,3 +1,7 @@
 gradio
 torch
 torchaudio
+librosa
+onnxruntime
+numpy
+tqdm

utils.py

@@ -0,0 +1,151 @@
+import os, zipfile, shutil, subprocess, shlex, sys # noqa
+from urllib.parse import urlparse
+import re
+import logging
+import hashlib
+
+
+def load_file_from_url(
+    url: str,
+    model_dir: str,
+    file_name: str | None = None,
+    overwrite: bool = False,
+    progress: bool = True,
+) -> str:
+    """Download a file from `url` into `model_dir`,
+    using the file present if possible.
+
+    Returns the path to the downloaded file.
+    """
+    os.makedirs(model_dir, exist_ok=True)
+    if not file_name:
+        parts = urlparse(url)
+        file_name = os.path.basename(parts.path)
+    cached_file = os.path.abspath(os.path.join(model_dir, file_name))
+
+    # Overwrite
+    if os.path.exists(cached_file):
+        if overwrite or os.path.getsize(cached_file) == 0:
+            remove_files(cached_file)
+
+    # Download
+    if not os.path.exists(cached_file):
+        logger.info(f'Downloading: "{url}" to {cached_file}\n')
+        from torch.hub import download_url_to_file
+
+        download_url_to_file(url, cached_file, progress=progress)
+    else:
+        logger.debug(cached_file)
+
+    return cached_file
+
+
+def friendly_name(file: str):
+    if file.startswith("http"):
+        file = urlparse(file).path
+
+    file = os.path.basename(file)
+    model_name, extension = os.path.splitext(file)
+    return model_name, extension
+
+
+def download_manager(
+    url: str,
+    path: str,
+    extension: str = "",
+    overwrite: bool = False,
+    progress: bool = True,
+):
+    url = url.strip()
+
+    name, ext = friendly_name(url)
+    name += ext if not extension else f".{extension}"
+
+    if url.startswith("http"):
+        filename = load_file_from_url(
+            url=url,
+            model_dir=path,
+            file_name=name,
+            overwrite=overwrite,
+            progress=progress,
+        )
+    else:
+        filename = path
+
+    return filename
+
+
+def remove_files(file_list):
+    if isinstance(file_list, str):
+        file_list = [file_list]
+
+    for file in file_list:
+        if os.path.exists(file):
+            os.remove(file)
+
+
+def remove_directory_contents(directory_path):
+    """
+    Removes all files and subdirectories within a directory.
+
+    Parameters:
+    directory_path (str): Path to the directory whose
+    contents need to be removed.
+    """
+    if os.path.exists(directory_path):
+        for filename in os.listdir(directory_path):
+            file_path = os.path.join(directory_path, filename)
+            try:
+                if os.path.isfile(file_path):
+                    os.remove(file_path)
+                elif os.path.isdir(file_path):
+                    shutil.rmtree(file_path)
+            except Exception as e:
+                logger.error(f"Failed to delete {file_path}. Reason: {e}")
+        logger.info(f"Content in '{directory_path}' removed.")
+    else:
+        logger.error(f"Directory '{directory_path}' does not exist.")
+
+
+# Create directory if not exists
+def create_directories(directory_path):
+    if isinstance(directory_path, str):
+        directory_path = [directory_path]
+    for one_dir_path in directory_path:
+        if not os.path.exists(one_dir_path):
+            os.makedirs(one_dir_path)
+            logger.debug(f"Directory '{one_dir_path}' created.")
+
+
+def setup_logger(name_log):
+    logger = logging.getLogger(name_log)
+    logger.setLevel(logging.INFO)
+
+    _default_handler = logging.StreamHandler()  # Set sys.stderr as stream.
+    _default_handler.flush = sys.stderr.flush
+    logger.addHandler(_default_handler)
+
+    logger.propagate = False
+
+    handlers = logger.handlers
+
+    for handler in handlers:
+        formatter = logging.Formatter("[%(levelname)s] >> %(message)s")
+        handler.setFormatter(formatter)
+
+    # logger.handlers
+
+    return logger
+
+
+logger = setup_logger("ss")
+logger.setLevel(logging.INFO)
+
+
+def get_hash(filepath):
+    with open(filepath, 'rb') as f:
+        file_hash = hashlib.blake2b()
+        while chunk := f.read(8192):
+            file_hash.update(chunk)
+
+    return file_hash.hexdigest()[:18]