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| import gradio as gr | |
| from PIL import Image | |
| from transformers import pipeline | |
| captioner = pipeline("image-to-text", model="Salesforce/blip-image-captioning-large") | |
| def describir(imagen): | |
| if imagen is None: | |
| return "Sube una imagen." | |
| img = Image.fromarray(imagen) | |
| result = captioner(img)[0]["generated_text"] | |
| return result | |
| with gr.Blocks(title="Accesibilidad con Transformers") as demo: | |
| gr.Markdown( | |
| """ | |
| #Accesibilidad con Transformers | |
| Sube una imagen y un modelo Transformer generará una descripción detallada | |
| para mejorar la accesibilidad del contenido visual. | |
| """ | |
| ) | |
| with gr.Row(): | |
| image_input = gr.Image(type="numpy", label="Sube una Imagen") | |
| text_output = gr.Textbox(label="Descripción Generada") | |
| run_button = gr.Button("Generar Descripción") | |
| run_button.click( | |
| fn=describir, | |
| inputs=image_input, | |
| outputs=text_output | |
| ) | |
| demo.launch() |