antfraia commited on
Commit
6611bfa
·
1 Parent(s): 3e31d99

Update app.py

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Files changed (1) hide show
  1. app.py +14 -35
app.py CHANGED
@@ -1,41 +1,20 @@
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- import gradio as gr
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- import numpy as np
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- from elevenlabs import voices, generate, set_api_key, UnauthenticatedRateLimitError
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- def pad_buffer(audio):
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- buffer_size = len(audio)
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- element_size = np.dtype(np.int16).itemsize
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- if buffer_size % element_size != 0:
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- audio = audio + b'\0' * (element_size - (buffer_size % element_size))
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- return audio
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-
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- def generate_voice(text, voice_name):
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- model_name = "eleven_multilingual_v1"
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- try:
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- audio = generate(
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- text[:250],
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- voice=voice_name,
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- model=model_name
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- )
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- return (44100, np.frombuffer(pad_buffer(audio), dtype=np.int16))
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- except UnauthenticatedRateLimitError as e:
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- raise gr.Error("Thanks for trying out ElevenLabs TTS! You've reached the free tier limit. Please provide an API key to continue.")
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- except Exception as e:
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- raise gr.Error(str(e))
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-
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- all_voices = voices()
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- desired_voices = ["Antonio"]
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- filtered_voices = [voice.name for voice in all_voices if voice.name in desired_voices]
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-
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- input_text = gr.Textbox(label="Input Text", lines=2)
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- input_voice = gr.Dropdown(choices=filtered_voices, default="Antonio", label="Voice")
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- out_audio = gr.Audio(label="Generated Voice", type="numpy")
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  iface = gr.Interface(
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- fn=generate_voice,
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- inputs=[input_text, input_voice],
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- outputs=out_audio,
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- live=True
 
 
 
 
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  )
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  iface.launch()
 
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+ import gradio as gr
 
 
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+ # Define the function to predict using the model
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+ def predict_image(img):
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+ model = gr.load("models/google/vit-base-patch16-224")
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+ return model.predict(img)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ # Create the interface
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  iface = gr.Interface(
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+ fn=predict_image,
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+ inputs=gr.Image(),
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+ outputs="label",
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+ live=True,
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+ capture_session=True,
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+ title="Image recognition",
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+ description="Upload an image you want to categorize.",
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+ theme="Monochrome"
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  )
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  iface.launch()