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import gradio as gr
from transformers import pipeline,WhisperProcessor, WhisperForConditionalGeneration
import torch
import librosa
checkpoint = "openai/whisper-base"
# checkpoint = "/innev/open-ai/huggingface/openai/whisper-base"
image_to_text_model = pipeline("image-classification")
text_to_audio_model = pipeline("text-to-speech")
def image_to_text(input_image):
# Convertir la imagen a texto
text_output = image_to_text_model(input_image)[0]['label']
return text_output
with gr.Blocks() as demo:
gr.Markdown("Start typing below and then click **Run** to see the output.")
with gr.Row():
inp = gr.Image()
out = gr.Textbox(placeholder=image_to_text(inp))
gr.Interface(fn=image_to_text, inputs=inp, outputs=out,interpretation="default")
demo.launch()
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