2.0 KiB
2.0 KiB
Documentation
- Class name: FL_AudioPreview
- Category: 🏵️Fill Nodes
- Output node: True
- Repo Ref: https://github.com/FilipLe/filips-comfyui-nodes
FL_AudioPreview节点旨在播放音频片段,让用户能够在工作流程中预览音频数据。该节点支持单声道和立体声音频格式,并能处理以PyTorch张量或NumPy数组形式提供的音频数据。
Input types
Required
- audio_segment
- 这是一个包含音频数据和其采样率的元组。此输入对于确定要播放的音频内容及其播放速度至关重要。
- Comfy dtype: AUDIO
- Python dtype: Tuple[Union[torch.Tensor, np.ndarray], int]
Output types
该节点没有输出类型
Usage tips
- Infra type:
CPU - Common nodes: unknown
Source code
class FL_AudioPreview:
@classmethod
def INPUT_TYPES(cls):
return {
"required": {"audio_segment": ("AUDIO", {"description": "Tuple of (audio data tensor, sample rate)"})},
}
FUNCTION = "play_audio_segment"
CATEGORY = "🏵️Fill Nodes"
OUTPUT_NODE = True
RETURN_TYPES = ()
@classmethod
def play_audio_segment(cls, audio_segment):
waveform, sample_rate = audio_segment
# Check if waveform is a PyTorch tensor and convert to numpy array accordingly
if isinstance(waveform, torch.Tensor):
numpy_waveform = waveform.cpu().numpy()
elif isinstance(waveform, np.ndarray):
numpy_waveform = waveform
else:
raise TypeError("Unsupported type for waveform. Expected torch.Tensor or np.ndarray.")
# Check if the audio is stereo or mono and play accordingly
if numpy_waveform.shape[0] > 1:
# If stereo, playing the first channel for simplicity
sd.play(numpy_waveform[0], sample_rate)
else:
# If mono, play as is
sd.play(numpy_waveform, sample_rate)
print ("""
---------
Will resume after audio preview completes
---------
""")
sd.wait()
return []