Spaces:
Running
on
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Running
on
Zero
Commit
·
506ecd3
1
Parent(s):
71f87cb
Download models
Browse files- tools/download_files.py +111 -0
- webui.py +3 -2
tools/download_files.py
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import requests
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import zipfile
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import os
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import argparse
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def download_file_from_google_drive(file_id, destination):
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"""
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通过文件ID下载Google Drive共享文件
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Args:
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file_id (str): Google Drive文件的ID
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destination (str): 本地保存路径
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"""
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# 基本的下载URL
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URL = "https://docs.google.com/uc?export=download"
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session = requests.Session()
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# 发起初始GET请求
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response = session.get(URL, params={'id': file_id}, stream=True)
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token = get_confirm_token(response) # 从响应中获取确认令牌(如果需要)
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if token: # 如果需要确认(大文件)
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params = {'id': file_id, 'confirm': token}
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response = session.get(URL, params=params, stream=True)
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# 将响应内容保存到文件
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save_response_content(response, destination)
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def get_confirm_token(response):
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"""
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从响应中检查是否存在下载确认令牌(cookie)
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Args:
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response (requests.Response): 响应对象
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Returns:
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str: 确认令牌的值(如果存在),否则为None
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"""
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for key, value in response.cookies.items():
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if key.startswith('download_warning'): # 确认令牌的cookie通常以这个开头
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return value
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return None
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def save_response_content(response, destination, chunk_size=32768):
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"""
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以流式方式将响应内容写入文件,支持大文件下载。
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Args:
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response (requests.Response): 流式响应对象
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destination (str): 本地保存路径
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chunk_size (int, optional): 每次迭代写入的块大小. Defaults to 32768.
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"""
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with open(destination, "wb") as f:
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for chunk in response.iter_content(chunk_size):
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if chunk: # 过滤掉保持连接的空白块
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f.write(chunk)
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def download_model_from_modelscope(model_id, destination):
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"""
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从ModelScope下载模型(伪代码,需根据实际API实现)
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Args:
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model_id (str): ModelScope模型ID
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destination (str): 本地保存路径
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"""
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print(f"[ModelScope] Downloading models to {destination},model cache dir={hf_cache_dir}")
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from modelscope import snapshot_download
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snapshot_download("IndexTeam/IndexTTS-2", local_dir="checkpoints")
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snapshot_download("amphion/MaskGCT", local_dir="checkpoints/hf_cache/models--amphion--MaskGCT")
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snapshot_download("facebook/w2v-bert-2.0",local_dir="checkpoints/hf_cache/models--facebook--w2v-bert-2.0")
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snapshot_download("nv-community/bigvgan_v2_22khz_80band_256x",local_dir="checkpoints/hf_cache/models--nvidia--bigvgan_v2_22khz_80band_256x")
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# models--funasr--campplus
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snapshot_download("nv-community/bigvgan_v2_22khz_80band_256x",local_dir="checkpoints/hf_cache/models--nvidia--bigvgan_v2_22khz_80band_256x")
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def download_model_from_huggingface(destination,hf_cache_dir):
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"""
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从HuggingFace下载模型(伪代码,需根据实际API实现)
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Args:
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model_id (str): HuggingFace模型ID
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destination (str): 本地保存路径
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"""
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print(f"[HuggingFace] Downloading models to {destination},model cache dir={hf_cache_dir}")
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from huggingface_hub import snapshot_download
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snapshot_download("IndexTeam/IndexTTS-2", local_dir=destination)
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snapshot_download("amphion/MaskGCT", local_dir=os.path.join(hf_cache_dir,"models--amphion--MaskGCT"))
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snapshot_download("facebook/w2v-bert-2.0",local_dir=os.path.join(hf_cache_dir,"models--facebook--w2v-bert-2.0"))
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snapshot_download("nvidia/bigvgan_v2_22khz_80band_256x",local_dir=os.path.join(hf_cache_dir, "models--nvidia--bigvgan_v2_22khz_80band_256x"))
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snapshot_download("funasr/campplus",local_dir=os.path.join(hf_cache_dir,"models--funasr--campplus"))
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# 使用示例
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(description="下载文件和模型工具")
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parser.add_argument('--model_source', choices=['modelscope', 'huggingface'], default=None, help='模型下载来源')
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args = parser.parse_args()
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if args.model_source:
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if args.model_source == 'modelscope':
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download_model_from_modelscope("checkpoints",os.path.join("checkpoints","hf_cache"))
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elif args.model_source == 'huggingface':
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download_model_from_huggingface("checkpoints",os.path.join("checkpoints","hf_cache"))
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print("Downloading example files from Google Drive...")
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file_id = "1o_dCMzwjaA2azbGOxAE7-4E7NbJkgdgO"
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destination = "example_wavs.zip" # 替换为你希望的本地路径
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download_file_from_google_drive(file_id, destination)
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print(f"File downloaded to: {destination}")
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# 解压下载的zip文件到examples目录
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examples_dir = "examples"
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with zipfile.ZipFile(destination, 'r') as zip_ref:
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zip_ref.extractall(examples_dir)
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print(f"File extracted to: {examples_dir}")
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webui.py
CHANGED
@@ -24,8 +24,9 @@ parser.add_argument("--host", type=str, default="0.0.0.0", help="Host to run the
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parser.add_argument("--model_dir", type=str, default="checkpoints", help="Model checkpoints directory")
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parser.add_argument("--is_fp16", action="store_true", default=False, help="Fp16 infer")
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cmd_args = parser.parse_args()
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if not os.path.exists(cmd_args.model_dir):
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print(f"Model directory {cmd_args.model_dir} does not exist. Please download the model first.")
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parser.add_argument("--model_dir", type=str, default="checkpoints", help="Model checkpoints directory")
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parser.add_argument("--is_fp16", action="store_true", default=False, help="Fp16 infer")
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cmd_args = parser.parse_args()
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from tools.download_files import download_model_from_huggingface
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download_model_from_huggingface("checkpoints",os.path.join(current_dir, "hf_cache"))
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if not os.path.exists(cmd_args.model_dir):
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print(f"Model directory {cmd_args.model_dir} does not exist. Please download the model first.")
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