专业营销软件网站建设,经典软文案例,软件编程培训学校排名,重庆工程造价信息期刊windows部署spleeter 版本2.4.0#xff1a;分离音频的人声和背景音乐
一、Spleeter 是什么#xff1f;
Spleeter 是由法国音乐流媒体公司 Deezer 开发并开源的一款基于深度学习的音频分离工具。它能够将音乐中的不同音轨#xff08;如人声、鼓、贝斯、钢琴等#xff09;分…windows部署spleeter 版本2.4.0分离音频的人声和背景音乐
一、Spleeter 是什么
Spleeter 是由法国音乐流媒体公司 Deezer 开发并开源的一款基于深度学习的音频分离工具。它能够将音乐中的不同音轨如人声、鼓、贝斯、钢琴等分离为独立的音频文件适用于音乐制作、学术研究、音频处理等领域。
二、核心功能
多音轨分离 2stems分离为 人声vocals 和 伴奏accompaniment。4stems分离为 人声、鼓、贝斯 和 其他。5stems分离为 人声、鼓、贝斯、钢琴 和 其他。 高效处理 支持 CPU 和 GPU需 TensorFlow GPU 版本加速。单曲处理仅需数秒至数分钟取决于硬件配置。 开源免费 代码和预训练模型完全开源GitHub MIT 协议。无需商业授权适合个人和学术用途。
三、安装过程
github地址: https://github.com/deezer/spleeter/tree/master
1.创建conda虚拟环境 python使用3.9
conda create -n spleeter python3.9
conda activate spleeter2.安装依赖ffmpeg和libsndfile
conda install ffmpeg libsndfile3.安装最新版spleeter
pip install spleeter4.下载测试文件
wget https://github.com/deezer/spleeter/raw/master/audio_example.mp35.执行
spleeter separate -p spleeter:2stems -o output audio_example.mp3
最后在命令执行路径下生成目录output/audio_example内部有两个文件人声音文件vocals.wav和背景音乐文件accompaniment.wav各种模型下载2stems、4stems、5stems
https://github.com/deezer/spleeter/releases
四、报错处理
报错处理一找不到指定的模块mkl_intel_thread.2.dll
(spleeter) C:\Users\81097864\Downloadsspleeter separate -p spleeter:2stems -o output audio_example.mp3
INTEL oneMKL ERROR: 找不到指定的模块。 mkl_intel_thread.2.dll.
Intel oneMKL FATAL ERROR: Cannot load mkl_intel_thread.2.dll.numpy和mkl的版本不对卸载后重新安装安装方式
解决建议直接下载numpy-1.24.5mkl-cp39-cp39-win_amd64.whl下载地址
https://github.com/cgohlke/numpy-mkl-wheels/releases
(spleeter) C:\Users\81097864\Downloadspip install numpy-1.23.5mkl-cp39-cp39-win_amd64.whl报错处理二github模型2stems.tar.gz下载失败
(spleeter) C:\Users\81097864\Downloadsspleeter separate -p spleeter:2stems -o output audio_example.mp3
INFO:spleeter:Downloading model archive https://github.com/deezer/spleeter/releases/download/v1.4.0/2stems.tar.gz
Traceback (most recent call last):File d:\Miniconda3\envs\spleeter\lib\site-packages\httpx\_transports\default.py, line 61, in map_httpcore_exceptionsyieldFile d:\Miniconda3\envs\spleeter\lib\site-packages\httpx\_transports\default.py, line 106, in __iter__for part in self._httpcore_stream:File d:\Miniconda3\envs\spleeter\lib\site-packages\httpcore\_sync\connection_pool.py, line 57, in __iter__for chunk in self.stream:File d:\Miniconda3\envs\spleeter\lib\site-packages\httpcore\_bytestreams.py, line 56, in __iter__for chunk in self._iterator:File d:\Miniconda3\envs\spleeter\lib\site-packages\httpcore\_sync\http2.py, line 435, in body_iterevent self.connection.wait_for_event(self.stream_id, timeout)File d:\Miniconda3\envs\spleeter\lib\site-packages\httpcore\_sync\http2.py, line 242, in wait_for_eventself.receive_events(timeout)File d:\Miniconda3\envs\spleeter\lib\site-packages\httpcore\_sync\http2.py, line 249, in receive_eventsdata self.socket.read(self.READ_NUM_BYTES, timeout)File d:\Miniconda3\envs\spleeter\lib\site-packages\httpcore\_backends\sync.py, line 61, in readreturn self.sock.recv(n)File d:\Miniconda3\envs\spleeter\lib\contextlib.py, line 137, in __exit__self.gen.throw(typ, value, traceback)File d:\Miniconda3\envs\spleeter\lib\site-packages\httpcore\_exceptions.py, line 12, in map_exceptionsraise to_exc(exc) from None
httpcore.ReadTimeout: The read operation timed outThe above exception was the direct cause of the following exception:2stems.tar.gz模型文件下载失败。可以手动下载https://github.com/deezer/spleeter/releases/download/v1.4.0/2stems.tar.gz后解压到spleeter separate命令执行所在的路径下。
我的命令执行路径如下
(spleeter) C:\Users\81097864\Downloadsspleeter separate -p spleeter:2stems -o output audio_example.mp3模型位置 命令执行路径/pretrained_models/2stems 五、Windows用户注意
命令spleeter在 Windows可能上无法正常工作。这是一个已知问题我们希望很快修复。在命令行中替换spleeter separate为python -m spleeter separate应该可以正常工作。
六、指定模型文件路径
通过环境变量MODEL_PATH指定模型文件所在位置2stems、4stems、5stems这些模型文件夹都是MODEL_PATH的子目录
# 指定模型文件所在位置
(spleeter) D:\big-modelset MODEL_PATHD:\big-model\spleeter-model# 其他参数
#--verbose打印日志
#-c 指定输出文件格式
#-o 指定结果文件目录
#-f : 指定结果文件名称
(spleeter) D:\big-modelspleeter separate --verbose -p spleeter:2stems -c mp3 -o D:\big-model\audio -f {filename}_{instrument}.{codec} D:\big-model\audio_example.mp3
INFO:tensorflow:Using config: {_model_dir: D:\\big-model\\spleeter-model\\2stems, _tf_random_seed: None, _save_summary_steps: 100, _save_checkpoints_steps: None, _save_checkpoints_secs: 600, _session_config: gpu_options {per_process_gpu_memory_fraction: 0.7
}
, _keep_checkpoint_max: 5, _keep_checkpoint_every_n_hours: 10000, _log_step_count_steps: 100, _train_distribute: None, _device_fn: None, _protocol: None, _eval_distribute: None, _experimental_distribute: None, _experimental_max_worker_delay_secs: None, _session_creation_timeout_secs: 7200, _checkpoint_save_graph_def: True, _service: None, _cluster_spec: ClusterSpec({}), _task_type: worker, _task_id: 0, _global_id_in_cluster: 0, _master: , _evaluation_master: , _is_chief: True, _num_ps_replicas: 0, _num_worker_replicas: 1}
WARNING:tensorflow:From d:\Miniconda3\envs\spleeter\lib\site-packages\spleeter\separator.py:146: calling DatasetV2.from_generator (from tensorflow.python.data.ops.dataset_ops) with output_types is deprecated and will be removed in a future version.
Instructions for updating:
Use output_signature instead
WARNING:tensorflow:From d:\Miniconda3\envs\spleeter\lib\site-packages\spleeter\separator.py:146: calling DatasetV2.from_generator (from tensorflow.python.data.ops.dataset_ops) with output_shapes is deprecated and will be removed in a future version.
Instructions for updating:
Use output_signature instead
INFO:tensorflow:Calling model_fn.
INFO:tensorflow:Apply unet for vocals_spectrogram
WARNING:tensorflow:From d:\Miniconda3\envs\spleeter\lib\site-packages\keras\layers\normalization\batch_normalization.py:514: _colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.
Instructions for updating:
Colocations handled automatically by placer.
INFO:tensorflow:Apply unet for accompaniment_spectrogram
INFO:tensorflow:Done calling model_fn.
INFO:tensorflow:Graph was finalized.
INFO:tensorflow:Restoring parameters from D:\big-model\spleeter-model\2stems\model
INFO:tensorflow:Running local_init_op.
INFO:tensorflow:Done running local_init_op.
INFO:spleeter:File D:\big-model\audio\audio_example_accompaniment.mp3 written succesfully
INFO:spleeter:File D:\big-model\audio\audio_example_vocals.mp3 written succesfully(spleeter) D:\big-model
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