| import gradio as gr | |
| from transformers import pipeline | |
| pipe = pipeline("image-to-text", | |
| model="Salesforce/blip-image-captioning-base") | |
| def captioner(input): | |
| out = pipe(input) | |
| return out[0]['generated_text'] | |
| # iface = gr.Interface(captioner, | |
| # inputs=gr.Image(type='pil'), | |
| # outputs="text") | |
| # iface.launch() | |
| demo = gr.Interface(fn=captioner, | |
| inputs=[gr.Image(label="Upload image", type="pil")], | |
| outputs=[gr.Textbox(label="Caption")], | |
| title="Image Captioning with BLIP", | |
| description="Caption any image using the BLIP model", | |
| allow_flagging="never", | |
| examples=["christmas_dog.jpg"]) | |
| demo.launch() |