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| import gradio as gr | |
| from PIL import Image | |
| from image_captioning import caption_image_unconditional, caption_image_conditional | |
| # Gradio interface for unconditional image captioning | |
| def gradio_unconditional_image_caption(image): | |
| return caption_image_unconditional(image) | |
| # Gradio interface for conditional image captioning | |
| def gradio_conditional_image_caption(image, text): | |
| return caption_image_conditional(image, text) | |
| # Define the Gradio interface using the updated syntax | |
| iface_unconditional = gr.Interface(fn=gradio_unconditional_image_caption, | |
| inputs=gr.Image(type="pil"), | |
| outputs="text", | |
| title="Unconditional Image Captioning", | |
| description="Upload an image to get an unconditional caption generated by the BLIP model.") | |
| iface_conditional = gr.Interface(fn=gradio_conditional_image_caption, | |
| inputs=[gr.Image(type="pil"), gr.Textbox(lines=1, placeholder="Enter a prompt")], | |
| outputs="text", | |
| title="Conditional Image Captioning", | |
| description="Upload an image and enter a prompt to get a conditional caption generated by the BLIP model.") | |
| # Combine both interfaces into a single Gradio app | |
| app = gr.TabbedInterface([iface_unconditional, iface_conditional], ["Unconditional", "Conditional"]) | |
| # Launch the app | |
| app.launch() | |