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import gradio as gr
from msclap import CLAP
clap_model = CLAP(version = 'clapcap', use_cuda=False)
def clap_inference(mic=None, file=None):
if mic is not None:
audio = mic
elif file is not None:
audio = file
else:
return "You must either provide a mic recording or a file"
# Generate captions for the recording
captions = clap_model.generate_caption([audio],
resample=True,
beam_size=5,
entry_length=67,
temperature=0.01)
return captions[0]
def create_app():
with gr.Blocks() as demo:
gr.Markdown(
"""
# CLAP demo for automatic audio captioning
"""
)
gr.Interface(
fn=clap_inference,
inputs=[
gr.Audio(sources="microphone", type="filepath"),
gr.Audio(sources="upload", type="filepath"),
],
outputs="text",
)
return demo
def main():
app = create_app()
app.launch(debug=True)
if __name__ == "__main__":
main()
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